Wind Power and Its Impact on the Moldovan Electrical System

UPTEC-ES12011 Examensarbete 30 hp April 2012

Joel Eriksson Simon Gozdz Englund Abstract Wind Power and Its Impact on the Moldovan Electrical System Joel Eriksson & Simon Gozdz Englund

Teknisk- naturvetenskaplig fakultet UTH-enheten The master thesis project has been executed with the cooperation of Borlänge Energi, with the aim of reducing the high electric energy dependency which Moldova Besöksadress: has on Ukraine, Transnistria and Russia. Ångströmlaboratoriet Lägerhyddsvägen 1 Hus 4, Plan 0 The project examines what reduction that would be possible by wind power installations on the existing electrical grid of Moldova. The installations should not Postadress: surpass the capacity of the transmission lines or the voltage levels according to Box 536 751 21 Uppsala regulation. The southern regions of Moldova proved to have the best wind conditions and the locations of Besarabeasca, Zarnesti, Leovo, Ciadyr and Cimislia in the Telefon: southern region were chosen for wind power installations. 018 – 471 30 03

Telefax: For the analysis a model over the Moldovan electrical system is constructed. Each of 018 – 471 30 00 the five chosen locations is modelled with a generator symbolizing the wind power installation. The power flow software PSS/E is used to construct the model. To Hemsida: examine possible wind power installations different scenarios are created. The http://www.teknat.uu.se/student scenarios are executed with the southern regions 110 kV system as a focus area. All scenarios are analysed with a contingency analysis, where transmission lines in the focus region are tripped. The contingency analysis and the scenarios are automated using the programming language Python. An economic analysis shows payback periods for wind power investments in Moldova, the analysis also shows the sensitivity of the electricity price and discount rates. The project concludes that wind power installations are possible with the Moldovan electric grid as it looks today. The installations would result in reducing the high dependency of imported electrical energy.

Handledare: Ronny Arnberg Ämnesgranskare: Mikael Bergkvist Examinator: Kjell Pernestål ISSN: 1650-8300, UPTEC ES** *** Sponsor: ÅForsk Sida I Förord (in Swedish)

Bakgrunden till detta spännande examensarbete är att författarna på egen hand sökte en utmaning vad gäller uppbyggnad och utformning av framtida elektriska kraftnät. Deras frågeställning var vad händer i ett kraftnät vid en massiv utbyggnad av t.ex. vindkraft, karakteriserad av stora variationer i effekt? Frågeställningen är höggradigt intressant i länder med lite tillgång på vattenkraft och ur perspektivet av utfasning av fossila bränslen. Ur den synvinkeln var det svenska kraftnätet mindre intressant. Efter kontakter med Ronny Arnberg, Borlänge Energi, kom projektet att fokusera på elförsörjningen i Moldavien vars kraftnät blev modell för studien. Målet är inte att lösa Moldaviens energiförsörjningsproblem.

De ambitioner som författarna hade inledningsvis har sedan modererats på ett förtjänstfullt sätt av ämnesgranskaren Mikael Bergkvist att bättre passa tillgänglighet, tid och resurser. Ronny Arnberg har bistått med mängder med kontakter i Moldavien som öppnat dörrar för författarna. Resultatet på författarnas initiala fråga har kanske inte blivit besvarad men väl gett stora insikter i de utmaningar som väntar.

2012-03-16

Kjell Pernestål Examinator Unv.lekt. Uppsala Universitet

II Acknowledgments

This Master Thesis Project has been financed by a MFS scholarship and a ÅForsk scholarship without which the project could not have been executed.

Technical support was provided by the Technical University of Moldova, Anatolie Boscneanu Main Specialist at the National Agency for Energy Regulation and Lise Toll Project Developer at E.ON Climate & Renewables. Technical support was also provided along with and guidance in times of need throughout the project by our supervisors at Uppsala University; Mikael Bergkvist and Kjell Pernestål.

Special thanks should be directed to Professor Arion Valentin and PhD student Victor Gropa at the Technical University of Moldova who took us in with the true spirit of the Moldovan people; with helping hands wanting nothing in return. Thank you

This project could not have been written without the help of Borläng energi and its enthusiast Ronny Arnberg who provided contacts and a workplace in Moldova.

We would also like to take the chance to express our gratitude for the opportunity to experience Moldova and its truly great people, out of which we now call many friends and whom we will never forget.

III Populärvetenskaplig beskrivning (in Swedish)

Moldavien är ett av de fattigare länderna i Europa. Det finns ett starkt engagemang och en stor vilja för sammarbeten med västländer för att lämna fattigdomen och närma sig Västeuropa. Ett viktigt steg i detta är att bli av med det starka energiberoende gentemot Ukraina och Ryssland som finns idag. Moldaviens interna politiska situation är svår. En del av Moldavien, Transnistrien, existerar idag som en autonom republik och har en långdragen konflikt bakom sig som ännu inte är löst. Transnistrien och situationen där är viktig ur en energisituation då den största kraftanläggningen i hela regionen ligger där.

Moldavien importerar idag mellan 94 och 98 % av sin totala energikonsumtion där de stora importprodukterna är naturgas från Ryssland och el från Ukraina och Transnistrien. Av sin elkonsumtion har Moldavien idag endast möjlighet att producera ca 26 % nationellt, resten importeras från Ukraina och Transnistrien.

I examensarbetet utreds möjligheterna att minska detta starka beroende genom att öka intern elproduktion genom vindkraft. Fokus ligger på elnätet, alltså hur mycket vindkraft som kan installeras till dagens existerande elnät utan att elledningarna blir överbelastade eller att spänningar i elnätet ökar eller sjunker utanför gällande gränsvärden.

Vindpotentialen har undersökts via tidigare studier och den visar på att potentialen är störst i den södra delen av Moldavien. Dessa vindkraftskarteringar är utförda utifrån vindmätningar på meterologiska stationer, ofta på 10 till 12 meters höjd. Genom simuleringsprogram har man sedan kunnat uppskatta vindhastigheter för olika områden och höjd.

Fem platser med bra vindpotential valdes ut för vidare studier över hur mycket vindkraft som kan installeras ur nätets perspektiv. Dessa platser i närheten av städerna; Besarabeasca, Zarnesti, Leovo, Ciadyr och Cimislia ligger alla i södra delen av Moldavien. Den begränsade faktorn för hur mycket vindkraft som kan byggas är elnätet.

För att undersöka effekterna från vindkraftsinstallationerna på elnätet var det nödvändigt att bygga upp en modell i datorprogrammet PSS/E, designat för att beräkna effektflöden i elnät. Datorn kan sedan utföra de komplexa beräkningar som krävs för att räkna ut effekter och spänningar i systemet. Det räcker dock inte att endast se på systemet som det faktiskt ser ut, man måste också undersöka vad som skulle händer då en elledning i systemet kopplas bort i en så kallad n-1 analys. Att en lina kopplas bort kan bero på behov av underhåll eller rena fel som kan uppstå vid till exempel olyckor.

Platserna undersöktes i den färdiga modellen bland annat en och en men även i ett scenario där det på alla platser samtidigt installeras vindkraft. Vindkraftparkerna symboliseras i modellen som generatorer som genererar aktiv effekt.

Resultaten visar att den maximalt möjliga installerade effekten varierar mycket beroende på plats. Cimislia visar sig ha möjlighet för 100 MW, innan överföringskapaciteten blir begränsande. De övriga platserna begränsas på grund av att spänningsnivåer stiger eller sjunker utanför riktlinjerna. Då installation sker på alla platser samtidigt finns det möjlighet att installera omkring 260 MW, även här är höga spänningar en begränsande faktor för ytterligare installation.

iii

Den reaktiva effekten i elnätet har en stark koppling till spänningsnivåer och därav upprepas scenariona då vindkraftparkerna även har möjlighet att producera eller konsumera reaktiv effekt. Då vindkraftparkerna på detta sätt har möjlighet att kompensera med reaktiv effekt hålls spänningen konstant på basspänningsnivån.

De nya resultaten visar att detta ger en möjlighet att öka vindkraftinstallationen per plats. De platser i tidigare scenariot som tidigt fick spänningsproblem begränsas nu, precis som Cimislia, endast av överföringskapaciteten. Installation vid Cimislia minskar dock något då reaktiv effekt även den ”tar upp plats” på elnätet. Maximal produktion är dock fortfarande störst i Cimislia med ca 100 MW. Då vindkraft installeras på alla platser samtidigt ges en ökning till 355 MW, alltså en tydlig ökning av möjlig vindkraftsinstallation.

För att räkna ut den totala minskningen av importerad el bör man ta hänsyn till att en vindkraftpark med installerad effekt med t.ex. 260 MW inte kommer leverera 260 MW hela tiden på grund av att vinden inte blåser hela tiden. För att ta hänsyn till detta används två olika utnyttjandefaktorer för vindkraftparkerna, 0,1 och 0,3 där 0,1 är en relativt låg utnyttjandefaktor och 0,3 är en relativt hög utnyttjandefaktor. Resultaten visar att vindkraftverk som endast levererar aktiv effekt kan minska elimporten med mellan 7 % till 20 % beroende på utnyttjandefaktorerna. Då vindkraftparken har möjligheten att konsumera reaktiv effekt kan elimporten minska med mellan 8 % till 25 %.

I rapporten utförs även en ekonomisk analys där återbetalningstiden för ett vindkraftsprojekt tas fram. Återbetalningstiden beräknas med nettonuvärdesmetoden och återbetalningstiden tas fram för några olika räntesatser. Återbetalningstiden för vindkraftsprojekten varierar från 3 år till att aldrig betala tillbaka sig vid de olika ekonomiska scenarierna.

Slutsatsen är att Moldaviens starka beroende av importerad elektricitet kraftigt kan minskas med en utbyggnad av vindkraft i södra delen av landet.

IV Executive summary

The Moldovan electrical energy imports can be reduced by as much as 25 %. This reduction is possible by wind power installations at the suitable locations of Besarabeasca, Zarnesti, Leovo, Ciadyr and Cimislia.

Assuming a possible good wind resource with a capability factor of 0,3 wind power installations of 355 MW would reduce the electrical energy imports by 25 % according to the model created for the project. The model has not been verified with other models, which is of priority for future work.

For a total installation of 355 MW the installed power needs to be allocated as shown below:

 Besarabasca 56 MW  Zarnesti 68 MW  Leovo 68 MW  Ciadyr 91 MW  Cimislia 72 MW

The strongest site for wind power production, one site at a time, is Cimislia with a total installed power of 102 MW possible. With all sites together the maximum installed power is 260 MW without reactive power compensation and 355 MW with reactive power compensation.

Economic calculations include a sensitivity analysis with different the electricity price and discount rates. The economic analyses shows that the payback time vary from 3 years to never being paid back and conclusions are drawn that further investigations needs to be made.

V List of Acronyms and Abbreviations

ANRE National Agency for Energy Regulation

AVR Automatic Voltage Regulation

CDM Clean Development Mechanism

CER Certified Emission Reduction credits

CHP Combined Heat and Power

DSA Dynamic Security Assessment

EBRD European Banc of Reconstruction and Development

ENTSO-E European Network of Transmission System Operators for Electricity

FACTS Flexible Alternating Current Transmission Systems

HAWT Horizontal Axis Wind Turbine

HPP Hydro Power Plant

IPS Integrated Power System

MAWS Mean Annual Wind Speed

MSSR Moldovan Soviet Socialist Republic

PSS/E Power System Simulator for Engineering p.u Per Unit

SNC Second National Communication

SSA Static Security Assessment

TUM Technical University of Moldova

UNFCCC United Nations Framework Commission of Climate Change

VAWT Vertical Axis Wind Turbine

WAsP Wind Atlas Analysis and Application Program

Table of Contents

I Förord (in Swedish) ______i

II Acknowledgments ______ii

III Populärvetenskaplig beskrivning (in Swedish)______iii

IV Executive summary ______v

V List of Acronyms and Abbreviations ______vi

Chapter 1 Introduction ______1 1.2 Borlänge Energi ______1 1.3 Moldova – Background ______1 1.3.1 Grid History ______2 1.3.2 Energy ______2 1.3.3 Bio Energy Potential ______3 1.3.4 Solar Energy Potential ______3 1.3.5 Wind Energy Potential ______4 1.1.1 Environmental Goals ______4 1.4 Aim and Goals ______5

Chapter 2 Background ______6 2.1 Grid – Theory ______6 2.1.1 Active and Reactive Power ______6 2.1.2 Introduction to the Electrical Power System ______8 2.1.3 Components in the Electrical Power System ______11 2.1.4 Per-Unit System ______15 2.1.5 Equivalents in Electrical Power Systems ______15 2.1.6 Static Modelling ______16 2.2 Wind Power ______19 2.2.1 Moldova´s Wind Resource ______22 2.2.2 Economy ______23 2.3 Method ______24 2.3.1 PSS/E ______24 2.3.2 Building the Model ______24 2.3.3 Scenarios ______29 2.3.4 Economy ______30 Chapter 3 Results ______32 3.1 Base Case______32 3.2 Scenario I ______33 3.2.1 Scenario I, With Reactive Power Compensation ______33 3.3 Scenario II ______34 3.3.1 Scenario II, With Reactive Power Compensation ______35

1.1 Reduction of Imported Electric Energy ______36 3.3.2 Scenario I ______36 3.3.3 Scenario II ______37 3.4 Economy ______37

Chapter 4 Discussion ______40 4.1 Scenarios ______40 4.1.1 Scenario I ______40 4.1.2 Scenario II ______41 4.1.3 Economy ______42 Chapter 5 Conclusion ______43

Chapter 6 Future Work ______44

Appendix A Map of the Moldovan electrical system ______A-1

Appendix B Map over the wind potential in Moldova ______B-1

Appendix C Description of WAsP ______C-1

Appendix D Line diagram and data over the equivalent 330 kV circuit ______D-1

Appendix E Transmission Line Data ______E-1

Appendix F Line diagram and data over the complete model ______F-1

Appendix G General Python Script – executing the contingency analysis ______G-1

Appendix H Python Script – Scenario I ______H-1

Appendix I Python Script – Scenario II, Monte Carlo Simulation______I-1

Appendix J Base Case - Contingency Loading Report ______J-1

Appendix K Base Case – Line Diagram with Line Capacities ______K-1

Appendix L Scenario I – Overload Report ______L-1

Appendix M Scenario I Reactive Power Compensation – Overload Report______M-1

Appendix N Scenario II - Overload Report ______N-2

Appendix O Scenario II Reactive Power Compensation – Overload Report ______O-2

Appendix P Scenario II – Contingency Loading Report ______P-1

Appendix Q Scenario II – Line Diagram for Line Capacities ______Q-1

Appendix R Scenario II All Generators – Results ______R-1

Appendix S The Contingency and Automation Process in PSS/E ______S-1

Appendix T Sub, Mon and Con files for the contingency analysis ______T-1

Appendix U Division of the Work Between the Authors ______U-1

Table of Figures and Tables

Figure 1.1 Regional gropes of ENTSO-E and the IPS electrical systems [8] 2 Figure 2.1 The total power aka. the apparent power, active power and reactive power [18] 7 Figure 2.2 Real power and reactive power plotted against the load angle and voltage [20] 8 Figure 2.3 Structure of an electrical power system [20] 9 Figure 2.4 Showing the basic schematics of an on-load tap changer [20] 12 Figure 2.5 Transmission line equivalent 13 Figure 2.6 The magnetic field H between two conductors 14 Figure 2.7 Electric field E between two conductors 14 Figure 2.8 Busses connected in star and delta with line impedance Z [20] 16 Figure 2.9 An equivalent circuit of a short transmission line 17 Figure 2.10 An equivalent circuit of a medium transmission line 18 Figure 2.11 Schematic scheme over a contingency plan [23] 19 Figure 2.12 A typical arrangement for a HAWT [20] 20

Figure 2.13 A typical Cp/λ curve for a wind turbine [20] 20 Figure 2.14 Turbine power as a function of the wind speed [20] 21 Figure 2.15 An investment and payback curve for a nonspecific project [25] 23 Figure 2.16 One line diagram over the PSS/E model 25 Figure 2.17 Load and generation in Moldova, rectangles represent generation and circles loads 28 Figure 2.18 The algorithm for the contingency analysis where generator G is increased 30 Figure 3.1 The dispersion of voltage levels for the base case contingency analysis 32 Figure 3.2 A histogram of the dispersion of voltage levels with a contingency analysis 34 Figure 3.3 A histogram of the dispersion of voltages levels with a contingency analysis 35 Figure 3.4 Payback time with a capability factor of 0,3 37 Figure 3.5 Payback time with a capability factor of 0,1 38 Figure 3.6 Payback time including CER:s with a capability factor of 0,3 38 Figure 3.7 Payback time including CER:s with a capability factor of 0,1 39 Figure A-1 Map over the Moldovan electrical system [31] A-1 Figure B-1 Wind Potential in Moldova at the height of 70 meters [14] B-1 Figure D-1 Line diagram from PSS/E for the equivalent circuit over the Moldovan electrical system D-1 Figure F-1 Line diagram for the equivalent circuit over the Moldovan electrical system F-1 Figure K-1 One line diagram with line capacities K-1 Figure Q-1 One line diagram with line capacities Q-1 Figure R-1 Shows the iterations with all generators in scenario I. R-1 Figure R-2 Histogram over the maximum generation without reactive power compensation R-2 Figure R-3 Results from the second iteration with a narrow interval for each generator R-2 Figure R-4 F Histogram over the maximum generation with reactive power compensation R-2 Figure S-1 Shows the recorder function within PSS/E S-2 Figure T-1 Contingency file created for the contingency analysis T-1 Figure T-2 Monitor file created for the contingency analysis T-1 Figure T-3 Subsystem file created for the contingency analysis T-1 Table 1.1 Existing transmission lines in Moldova 3 Table 2.1 Load values for the active generation and consumption 28 Table 2.2 Model load values for the active generation and consumption 28

Table 3.1 Maximum generation before violation in the contingency report 33 Table 3.2 Maximum values regarding only line capacities 33 Table 3.3 Extended generation potential until line capacity is reached 33 Table 3.4 Possible generation capacity with reactive power compensation 33 Table 3.5 Maximum generation for each location giving maximum total generation for the region 34 Table 3.6 Maximum generation for each location giving maximum total generation for the region 35 Table 3.7 Imported electrical energy reduction due to wind power installations 36 Table 3.8 Imported electrical energy reduction with reactive power compensation 36 Table 3.9 Imported electrical energy reduction due to wind power installations 37 Table D-1 Bus data for equivalent circuit over the Moldovan electrical system D-2 Table D-2 Plant data for equivalent circuit over the Moldovan electrical system D-2 Table D-3 Machine data for equivalent circuit over the Moldovan electrical system D-2 Table D-4 Load data for equivalent circuit over the Moldovan electrical system D-2 Table D-5 Branch data for equivalent circuit over the Moldovan electrical system D-2 Table E-1 Data over transmission line types E-1 Table E-2 Impedance values for the lines in the 110 kV system E-1 Table E-3 Base impedance values E-1 Table E-4 Per Unit values for the lines in the 110 kV system E-1 Table F-1 Bus Data F-2 Table F-2 Branch Data F-2 Table F-3 Machine Data F-3 Table F-4 Plant Data F-3 Table F-5 Load Data F-3 Table F-6 Switched Shunt Data F-3 Table F-7 Three Winding Data F-3 Table F-8 Winding Data, MGRAS F-4 Table F-9 Winding Data, Vulcanesti F-4 Table F-10 Winding Data, Hancesti-Straseni F-4 Table F-11 Winding Data, Chisinau F-4 Table J-1 The busses with maximum and minimum voltage levels from the loading report J-8

Chapter 1 Introduction The introduction starts by giving a description of the company that the project has been executed in cooperation with. Thereafter follows a short background of Moldova with its electrical system, energy and renewable energy potential. The introduction ends with the aim and the goals of the project.

1.2 Borlänge Energi AB Borlänge Energi is owned by the municipality of Borlänge. Borlänge Energi provides a wide range of services such as electricity, electricity grid, district heating, water, sewage, storm water and waste handling. In addition to these commitments Borlänge Energi also handles the municipality’s streets and parks [1].

Borlänge Energi has had international collaborations since the 1990th, with a primary focus on the environment. In 1998 the local authorities in Borlänge and the Swedish embassy in Bucharest initiated a project to establish links between the Swedish and the Romanian municipalities. This led to collaboration between Borlänge and the Romanian city of Pietsi. In Pietsi Ronny Arnberg from Borlänge Energi and the mayor of Borlänge Nils Persson met with representatives from Chisinau city hall and from APA Canal, the water and wastewater company in Chisinau. This was the start for the cooperation between Borlänge Energi and Moldova with focus on the capital, Chisinau. [2].

The municipality of Chisinau has an interest in understanding “the Swedish way” of thinking. From the cooperation with the municipality of Borlänge they will try to study different ways of spreading information to the society, working with youth and sustainable development. From the start of the cooperation in the year 2009 several projects regarding the environment have been conducted [3]. With the cooperation as a base many master thesis projects have been written together with Borlänge Energi in Chisinau.

1.3 Moldova – Background The Republic of Moldova is a small country situated in the south-eastern part of Europe with a total area of 33 800 m2 and 3,6 million inhabitants. Bordering countries to the north, south and east is Ukraine and to the west Romania. The capital is Chisinau with a population of around 600 000 inhabitants, other important cities are Tiraspol (located in Transnistria, see below) and Baltsi. Around 41 % of the inhabitants live in cities. Moldova became an independent state 1991 with the dissolution of the Soviet Union [4]. With a GDP of 1500 US dollars per capita Moldova is the poorest country of Europe [5].

The population consists of different ethnical groups with the biggest being the Moldavians but there are also large groups of Ukrainians and Russians. The different ethnic groups have contributed to the violent history of the country. In connection with the dissolution of the Soviet Union an armed conflict broke out in the eastern part of Moldova called Transnistria. The majority of the population in Transnistria consists of Russians and Ukrainians who wanted to establish a breakaway republic of Transnistria. The breakaway republic never gained international recognition and the armed conflict ended in 1992. Negotiations between Moldova and Transnistria with help from Russia have ended in a greater sense of autonomy for Transnistria, to this date the conflict is not yet solved. [6]

1.3.1 Grid History Before the dissolution of the Soviet Union the electrical grid and power plants were laid out to jointly optimize the market in the south-western Soviet Union and the other countries in the region e.g. Romania. With the fall of the Soviet Union these countries had to redesign their electrical systems. Moldova and Ukraine stayed with the Eastern European system IPS (Interconnected Power Systems) together with Russia while Romania chose to connect with the Western European system ENTSO-E (European Network of Transmission System Operators for Electricity). ENTSO-E operates at the same frequency as IPS but the two systems do not operate synchronized with each other. [7]

Moldova

Figure 1.1 Regional gropes of ENTSO-E and the IPS electrical systems [8]

The ENTSO-E is the joint European transmission system operator, in Figure 1.1; all marked zones except IPS are part of the ENTSO-E network and thus operate synchronously.

1.3.2 Energy Moldova imports 94 % to 98 % [9] of its consumed energy from Russia, Ukraine and Transnistria. The country thus is very dependent on the eastern countries for energy supply. Striving to align itself with the western part of Europe the energy security is an important issue. The main possibility for improving the energy security is with new power supply within the country.

Today the electric power generation in Moldova and Transnistria consists of three CHP (Combined Heat and Power) plants, two HPP (Hydropower Plants); MGRAS, the biggest power plant in the region, fired with gas, and situated in Transnistria; and other minor power plants. The total capacity in Moldova, incl. Transnistria, is 3008 MW but around 2570 MW is generated by MGRAS and is thus not controlled by the Moldovan government. This means that Moldova only has around 438 MW of generation capacity. This is not enough to supply the demand of baseload in Moldova [10]. The total consumed electric energy in Moldova year 2010 was 4102 GWh out of which 1064 GWh was produced domestically and 3038 GWh was imported i.e. Moldova imported 74 % of all electrical energy consumed within the country. Due to the complex situation with Transnistria electrical energy imports have mainly come from Ukraine, but recently imports from Transnistria have increased and are now dominating. [11]

The transmission grid in Moldova is interconnected with the neighbouring countries; six 330 kV overhead power lines to the Ukrainian power system, the connections to Romania consists of four 110 kV lines and one 400 kV line with which Moldova also gets connection with the Bulgarian power system see Appendix A. Because of the connections to the ENTSO-E system i.e. with a different synchronization than Moldova in Romania and Bulgaria, the transmission lines can only operate in island mode on the Moldavian side, or by using back to back frequency converters. [12]

The backbone in the Moldovan electrical system is the 330 kV line going from north to south, it is the main connection to both Transnistria and Ukraine. Well integrated together with the 330 kV system is the mesh of the 110 kV system which is spread out throughout Moldova. Table 1.1 shows the existing overhead line voltages and the total length of these. [13]

Table 1.1 Existing transmission lines in Moldova

Voltage level [kV] Length of the overhead transmission lines [km] 400 214 330 532,4 110 5231,1 Total: 5977,5

1.3.3 Bio Energy Potential Moldova has no experience of large scale applications of bio energy even though it’s an agricultural country. It has some experience in small scale applications in the rural area. Moldova’s biomass suitable for energy use comes from forestry, agriculture, food industry and waste from households, where agricultural waste has the biggest potential as an energy source. At present Moldova biomass is inefficiently used as many outdated and simple technologies are used to convert the biomass into energy e.g. domestic fires and stoves efficiency rating rarely exceeds 50 %. There is also a lot of biomass that today cannot be used because the lack of new, today already existing, technologies needed for the conversion of biomass into energy. [14]

The technical potential of biomass in Moldova is 5,4TWh, where 2,1TWh comes from agricultural waste, 1,2TWh comes from fuel wood, 1,3TWh comes from wood processing waste and 0,8TWh comes from biogas. The potential for bio fuels is another 0,6TWh, meaning that the total potential of bio energy in Moldova is 6TWh. [15]

Bio energy has the biggest energy potential in Moldova; both in theoretical values and in the potential to include it in today’s already existing social infrastructure and energy system development programs. [14]

1.3.4 Solar Energy Potential There has been research about solar energy utilization in Moldova. The research where performed by the institute of Energy of the academy of Sciences of RSSM (Moldovan Soviet Socialist Republic) in the late 1950s. The research resulted in a greenhouse with solar installations and heat storage in the ground. Because of the low prices for fossil fuel and lack of politic incitements for renewable energy the project was terminated. In the 1980s the work for implementing solar installations where restarted. [14]

Solar energy is received on the earth’s surface all the time, though the amount of energy received on the earth’s surface depends on several different factors. The most important factors are the suns brightness, duration and height above the horizon. In Moldova the theoretical duration of the sun, when it’s shining unimpeded, is 4445-4452 hours per year [14] but the real duration is 2100-2300 hours per year because of clouds concealing the sun. The amount of solar energy received on the surface of Moldova differs from 2300 kWh/ m2 year in south to 2100 kWh/m2 year in the north [14]. Other sources estimate the solar radiation in Chisinau to be 1300 kWh/m2 year. [15]

The solar energy in Moldova is primarily used for heating water using solar panels, secondarily used to dry fruit, vegetables and medicinal plants and tertiary for converting solar energy into electricity via photovoltaic conversion.

1.3.5 Wind Energy Potential Historically, the area that today is called the Republic of Moldova has been appreciated as favourable wind zone for wind energy development. Statistical data from 1901, before the development of steam engines and internal combustion engines, shows that a total of 6208 windmills were registered in the Moldova area and its surroundings. Some of these windmills were even used during the interwar period. During the 1950s even 350 windmills where built, exclusively to pump water for agricultural purposes. These where later replaced by cheaper and more easy to handle electrical systems. The electrification that occurred in Moldova during the 1950s as well as the low prices for electrical energy where factors that wind power could not compete with at the time. Today Moldova doesn’t have any wind power.

At present day Moldova has no wind power installed; however there are plans to install wind power plants in a near future. The south of Moldova is often mentioned as a preferable area to build wind power. The opinions of Moldova’s wind potential differ e.g. the organisation 3tier concluded MAWS (Mean Annual Wind Speed) of 4-6 m/s at the height of 80 m [15] while a feasibility study written by the UNDP Moldova concluded MAWS of 4,5-8,5 m/s at a height of 70 m [14]. Moldova’s technical potential for wind power is up to 1 GW installed power providing approximately 1,1TWh of electrical energy [15]. This correlates to a capability factor of 13 %, which is very low.

1.1.1 Environmental Goals Renewable energy in Moldova would go in accordance with the goals set up in their SNC (Second National Communication) directed to the UNFCCC (United Nations Framework Commission of Climate Change). The national priorities to reach the goals of greenhouse gas reductions include wider use of CDM (Clean Development Mechanism) projects, implementing a more aggressive policy on transfer of the green technologies, intensifying the process of international cooperation. An analysis on the possibilities to construct a wind power plant in Moldova in regards of the wind potential and the stability of the electrical grid would facilitate and work for the Moldavian national goals. The SNC also identifies relevant policies for the energy sector where two out of five directly would be coherence with the intended study, “…assuring energy security of the country by improving the interconnection capacity with the neighbouring countries and construction of new local sources of power generation based of the most recent and advanced environment friendly technologies.” and “…increasing the share of renewable sources of energy in the energy balance of the country”. [16]

1.4 Aim and Goals Moldova has a high dependency of imported electrical energy from Ukraine and Transnistria. To rid this huge dependency Moldova could look to its national resources for domestic production. The national goals in Moldova are angled towards sustainable development with more renewable energy.

This project will investigate how much the dependency of electrical imports could be reduced by wind power installations in the Moldovan electrical system as it looks today.

The goals of the project:

 The project will conclude in how much wind power installations would be possible in Moldova considering limiting factors of the electrical system.  The project will show how much the electrical imports can be reduced by wind power installations in Moldova.  The project will also conclude in potential sites for wind power installation  An economic analysis will show whether it would be profitable to construct wind power in Moldova

Chapter 2 Background The background describes the grid theory important for the project, a section with wind power potential and finally the method with the creation of the model. This is followed with the scenarios used to examine the model.

2.1 Grid – Theory To understand transmission networks active and reactive power are important concepts described below, also described are definitions of terms and components in the electrical system. The section ends with a description of approximations needed for computerize model calculations.

2.1.1 Active and Reactive Power Power is the rate of change of energy with respect to time [17]. It is the amount of energy being absorbed by a load during a time interval. Reactive power cannot be expressed in the same way, it cannot be seen as a constant flow of energy from one point to another, the reactive power is flowing back and forth in the system and when completing a cycle just as much energy that was flowing away has flowed back. The average reactive power in any system is always equal to zero. The reactive power is thus not measured by its average value, being zero, but by its amplitude, its maximum value. This gives a measurement of how much reactive power that is actually flowing through the system. [17]

In an RLC circuit, with inductance L and capacitance C, the voltage before and after the load will have a small angular difference described by the load angle , the current will be shifted from the voltage with the current angle . The difference between and is the power factor angle . With a purely inductive load the current lags the voltage by and in a purely capacitive load the current leads the voltage with . In the following equations the load angle is equal to zero.

Equation 1

Equation 2

With these expressions for voltage and current the instantaneous power can be expressed by:

Equation 3

This expression combined with trigonometric identities gives Equation 2.4.

Equation 2.4

Equation 2.4 consists of one real and one imaginary part; the real power is defined as the average value of the real part.

Equation 2.5

The average value of reactive part, as can be seen below in the Figure 2.1, is always zero; this is the definition of reactive power. Instead the reactive power is measured by its amplitude value, this gives us: [18]

Equation 2.6

Power

Time Figure 2.1 The total power aka. the apparent power, active power and reactive power [18]

P is expressed in Watts and Q in VAr (Volt Ampere reactive) both describing the same quantity but with different units to distinguish them. The power factor angle in the cosine term in Equation 2.5 and Equation 2.6 called the power factor. For inductive loads where the current lags the voltage the load consumes reactive power. With capacitive loads the current leads the voltage and the load creates reactive power. [17]

According to [19] the active and reactive power in a RLC four terminal electric circuit can be described by Equation 2.7 and Equation 2.8 if the resistance R is neglected and assuming that the load angle is small.

| || | Equation 2.7

and

Equation 2.7 describes the dependence the active power has on the differences between the phase voltages and the angle between these. The phase voltages in the power system may not differ much between busses and thus the active power is highly dependent on the load angle which is the angular difference between and . This gives us the characteristics that the active power is strongly dependent on the load. [20]

According to Equation 2.8 even a small change in voltage causes a large change in reactive power. If the reactive power is plotted against the voltage it corresponds to an inverted parabola, the dependency on the reactance gives us that the smaller the reactance the steeper will the parabola be, this means that with a low reactance small changes in voltages causes very large changes to the reactive power. The relationship can be seen in Figure 2.2 together with the sinusoidal characteristics of . [20]

Figure 2.2 Real power and reactive power plotted against the load angle and voltage [20]

In the three phase system the power is increased by a factor of √ as seen in the equations below. [17]

Equation 2.9

Equation 2.10 2.1.2 Introduction to the Electrical Power System The modern society requires energy for use in the industry, agriculture, commerce, transportation, communications, domestic households etc. The total energy required during one year is called total annual energy demand. About 85 % [21] of the total energy demand in the world is today supplied by fossil fuels like coal, oil, and natural gas. A large part of these fuels contribute to the electric energy production. Today the world is switching from these fossil fuels and more electrical energy is produced by renewable sources like wind power, solar power, hydro power, biogas, bio energy and geothermal energy. One of the major reasons for the increase in renewable energy is the global warming. In the future it’s likely that the share of the energy market taken by renewables will increase to high levels and play a more dominant role on the design of electrical power systems. [20]

2.1.2.1 Structure of the Electrical Power System The electrical power system can be divided into three different parts; generation, transmission and distribution.

The transmission network is normally the network with the highest voltage, from 300 kV and above. Transmission networks have the highest transferring capacities and are mostly built as meshed networks to increase the security of the system. To the transmission network only very large electrical energy consumers and producers are connected. The transmission network can also be used as connecting lines to other systems for example tying different countries together. [20]

The sub transmission network is a part of the transmission network. It consists of a high or medium voltage network, with the voltage levels ranging between 100 kV to 300 kV. Unlike the transmission network the sub transmission network is built as a radial network or a weakly coupled network. To the sub transmission network medium producers and consumers can be connected. [20]

Figure 2.3 Structure of an electrical power system [20]

Distribution networks are networks with medium voltages, in the range of 1 kV to 100 kV. The distribution network is often radial built networks. To the distribution network small generation and medium sized customers are connected. Wind power plants are often connected to the distribution network. The classification of the different parts of the system is not a strict classification and can vary depending on who is classifying it. [20]

2.1.2.2 Reliability of Supply One of the most important features of the electrical power system is that electrical energy cannot easily be stored in large quantities. At any instant in time the energy demand has to be met by the corresponding electricity generation. Fortunately the combined load pattern is pretty predictable whilst individual loads may vary quite much. This predictable system demand can thus quite easily be planned allowing scheduling the daily generation to be controlled in a predetermined manor. [17]

The electrical system is designed to operate within certain operational limits governed by grid codes. These operational limits ensure that you avoid major interruption of supply that can lead to life- threatening situations for the normal consumer, and for the industrial consumer may pose severe technical and production problems and thus loss of income. This is why high reliability of supply is of fundamental importance for the electrical system. High reliability can be ensured by: [17]

 High quality of installed elements  The provision of reserve generation  Employing large interconnected power systems capable of supplying each consumer via Alternative routes  A high level of system security [17]

2.1.2.3 Stability and Security of the Power System The stability of the power system is defined as the ability of the power system to regain equilibrium after being subjected to a change. The most common changes that affect the stability of the system are the variables described in the chapter on Active and Reactive Power i.e. the nodal voltage magnitudes, which affect the reactive power, and the nodal load angles, connected with the active power. This gives us the new terms of power angle stability, and voltage stability. [17]

The security of the power system refers to the ability of the power system to survive certain contingencies without affecting the quality of electrical supply to the customers. The stability of the power grid is part of the security but the concept of security is wider and also deals with other issues. The assessment of the power system can be divided into the SSA (Static Security Assessment) and the DSA (Dynamic Security Assessment). The DSA deals with the stability and quality of electrical supply during a change in the system where as the SSA only considers before and after scenario and assumes that there was no breach in stability along the way. [17]

It is in the interest of the TSO to perform the SSA in order to first evaluate the pre contingency state i.e. determine available transfer capability of transmission links and identify network congestions. Secondly to evaluate the post contingency states i.e. verify the bus voltages and power flow limits. Being responsible for the grid security the TSO needs to find ways of controlling the system so that it does not break down. Having no direct control over the generating units the only way to affect power outputs or control settings of the power plants are the grid codes or commercial agreements. [17]

As stated above the DSA deals with problems regarding the system stability and quality of electrical supply, the analysis in this report strictly deals with SSA and will thus not describe the problems regarding the dynamic simulations. A short description of some of the problems that occur follows in the next chapter. [17]

2.1.2.4 Quality of the Electrical Supply It is not just important that there is a high reliability to the system, there also has to be a high quality of the electrical supply. Electrical energy of high quality is provided by:

 Regulated and defined voltage levels with low fluctuations  A regulated and defined value of the frequency with low fluctuations  Low harmonic content  Low content of transients and flicker

To ensure the quality of the electrical supply two basic methods can be used. Firstly the proper uses of automatic voltage control i.e. shunt elements, tap transformers, frequency control methods and AVR (Automatic Voltage Regulation) within the generating units. Secondly by employing large interconnected systems because larger systems are naturally affected by load variations as well as other disturbances. To ensure the quality of electrical supply the TSO set codes that the grid should operate within. A common standard is that the frequency should not deviate from the base value with more than ± 0,1 Hz and the nodal voltages should stay within ± 10 % of its normal value. These regulations vary depending on voltage level but also depending of fault scenario. [17]

2.1.3 Components in the Electrical Power System The most important components of the electrical power system are generating units, transformers, shunt elements and transmission lines. These are described below.

2.1.3.1 Generating Units Generating units are the elements in the electrical power system that produces electrical energy. There are several different types of generators with different properties. Examples of different generators are the synchronous generator and induction generator. The generators are converting kinetic energy into electrical energy. Electrical energy is produced by a generator driven by a kinetic energy source, often a turbine or diesel engine. The turbine is equipped with a turbine governor which controls either the speed or the power output according to a pre-set power-frequency characteristic. The generated power is then fed to the electrical power system. [17]

Traditionally the electrical power system has been operated with relatively few large power plants connected to the transmission network. These large plants are usually either thermal or hydro based. Concerns about global warming and sustainability have increased the interest for renewable generation like thermal power plants which uses bio fuels, wind power and solar. This requires major changes in the electrical power system as the generation will increasingly be based on large amount of small producers often with the generation situated close to the energy source. Renewable energy has lower energy density than non-renewable energy sources and therefore the renewable power plants tend to be smaller, around hundreds of kilowatts to a few megawatts. Plants of this small size are often connected to the distribution level of the power system, rather than the transmission level because of the lower costs for the connection. These plants are called distributed generation. [17]

Wind turbines are a typical example of distributed generation power source. Wind turbines often use induction generators with either fixed speed or doubly fed generators to convert the power in wind into electrical energy. It is important to know that the rotating magnetic field in the induction machine is produced by a magnetizing current, whether it is operating as a generator or a motor. The magnetizing current is always supplied from an outside power source, often from the electrical power system. This means that the induction machine always consumes reactive power and therefore always must be connected to a power system that can provide the induction machine with reactive power for it to function properly. The reactive power can either be provided directly from the electrical power system or via reactive power compensation units installed together with the wind turbine. [17]

2.1.3.2 Transformers Transformers are needed to connect parts of the power system with different voltage levels. Generator step-up transformers are used when connecting generators to the grid. Tap transformers are used when there is a need for voltage regulation. Transformers can also be used for reduction of voltage to suit the low voltages needed by the consumers. This is done with distribution transformers. Connection of different parts of the electrical network with different voltage levels is done with transmission transformers. [20]

Transformers are built up by a magnetic core with windings wrapped around the core. For two winding transformer there are two sets of windings and with the three winding transformer there are three sets of windings. The three winding transformer can thus transform one voltage level into two different to suit several needs at once. The relation between the phasor voltage and the number of turns at each winding is shown in Equation 2.11. [17]

Equation 2.11

Thus the change in number of turns for the windings will affect the voltage levels proportionally. Transformers that can control voltage levels by changing the number of turns of the windings are known as tap changing transformers. The tap changers can operate ether as off load or on load. The off-load tap changers have a regulation rate of generally ± 5 % of voltage levels. The off load tap changers are operated manually and change is normally made to accommodate the seasons. The on- load tap changers have a general operational range of maximum ± 20 % of voltage levels and change is controlled by a regulator and can thus respond directly to disturbances such as a load change. A basic principle of a tap changer is shown in Figure 2.4 where the selectors S1 and S2 can move between the windings to cause small changes to the voltage. [20]

Figure 2.4 Showing the basic schematics of an on-load tap changer [20] 2.1.3.3 Shunt Elements Due to the fact that reactive power causes losses and uses the capacity in electrical lines the optimal operation is reached if reactive power is compensated for close to the point of consumption and not produced at the generation sources far from the consumption. One way to compensate for the reactive power is with shunt compensation i.e. by installation of capacitors or inductors close to the point of interest. Shunt compensation can also be used to stabilize voltage levels and thus strengthening the stability of the electrical power system. [20]

Transmission lines are generally consuming reactive power but if the load is very low the production of reactive power can exceed the consumption. This may lead to very high reactive power levels which in turn may lead to very high voltage levels due to the strong correlation between reactive power and voltages seen in Equation 2.8. Compensation for this effect is generally done for lines longer than 200 km by installation of shunt reactors. In a loaded line, shunt capacitors may be used to produce reactive power and compensate for voltage drops, more commonly series capacitors are connected in series with the conductors to compensate for the reactive power consumed by the line. [20]

Shunt compensation can also be supplied by a synchronous motor or generator running at no load called synchronous compensation. Being rather expensive switched shunt capacitor banks and reactors are often used in addition to the synchronous compensation at substations. Small such compensators, of several MVA, are often used on the tertiary winding of transmission transformers while larger compensation, of up to hundreds MVA, are connected to by individual step-up transformers to high-voltage substations. [20]

2.1.3.4 Transmission Lines There are both overhead and underground transmission lines though the overhead transmission lines are the most common. An overhead transmission line consists of three main components, conductors, insulators and support structures. Transmission lines often also have shield wires placed above the conductor to protect it from lightning.

2.1.3.4.1 Important Parameters The design of the transmission line determines these parameters e.g. conductor type, the space between conductors and the size determines the series impedance and shunt admittance where the series impedance affects the ohmic losses, line-voltage drops and the stability limits. The shunt admittance, which is primarily capacitive, affects the line charging currents. The line charging currents are the currents which increases reactive power in the power system. In light loaded power systems shunt reactors often are installed to absorb this reactive power and thus reducing over voltages. [17]

A transmission line can be described with the equivalent seen in Figure 2.5 where R is the resistance, L is the inductance, G is the conductance and C is the capacitance.

Figure 2.5 Transmission line equivalent 2.1.3.4.2 Resistance in Transmission Lines The DC resistance in the conductors depends on the length, cross sectional area and the conductivity of the conductor. The conductivity also depends on the temperature. The DC resistance is described below:

Equation 2.12

where is the conductivity at temperature T, is the length of the conductor and A is the cross sectional area. The conductivity depends on the material and common materials for conductors are copper and aluminium. Temperature and current magnitude also affect the resistance in conductors with AC current. The resistance is frequency dependent due to the “skin effect” which is the phenomenon that the current distribution tends to be denser at the surface of the conductor. This

13 causes a conductor loss, the effect only occurs with AC currents. The higher the frequency the higher is the real power losses due to the “skin effect”. losses is always bigger than losses [17].

Equation 2.13 | | 2.1.3.4.3 Conductance in Transmission Lines The conductance can be modelled as the shunt admittance in overhead lines. The conductance occurs because of the leaking currents due to the corona effect, damaged insulators and dirt, salt and other contaminants. The corona effect occurs when the electrical field strength at the conductor surface causes the surrounding air to ionize and thereby conduct. The losses from the conductance are much lower than the ohmic losses in the conductor, and are thus normally neglected. [17]

2.1.3.4.4 Inductance in Transmission Lines The inductance in conductors comes from the current flowing in the transmission line.

Figure 2.6 The magnetic field H between two conductors

The inductance depends on the magnetic field intensity H, the magnetic flux density B, the flux linkages , and inductance from flux linkages per ampere as can be seen in Figure 2.6. [17]

2.1.3.4.5 Capacitance in Transmission Lines An electric field is created between two conductors because of the difference in potential between the conductors, represented by ΔV in Figure 2.7.

Figure 2.7 Electric field E between two conductors

The capacitance is defined by the charge divided by the voltage . The charge is dependent on the electrical field and the flux. In an ideal solid cylindrical conductor the flux and electrical field is equal to the area integral of the electric field strength and the electric flux density over the surface area of the conductor. [17]

2.1.4 Per-Unit System Working with electrical systems with different voltages the per-unit system is often introduced. Basically it reduces the risk of making calculation error when going from one voltage level to another. If values are expressed in per-unit there can be a direct comparison from one side of a transformer to another. The expression for calculating the per-unit value is shown in Equation 2.14.

Equation 2.14

The resistance and reactance base values are calculated using the base value of the impedance and the base values for the conductance and susceptance is calculated with the base value for the admittance . The connection between the two base values can be seen in Equation 2.15. [17]

Equation 2.15

2.1.5 Equivalents in Electrical Power Systems Electrical systems are generally very large with a lot of components, modelling this as a complete system including all components is often an impossible task if even a desired one. One method of creating an equivalent of parts in an electrical system is called model reduction methods. This method consists first of physical reductions, where suitable models for the system are chosen depending on how influential the system elements are to a disturbance. A component far from a disturbance is not as affected by a disturbance and can thus be modelled more simply. Secondly there is topological reduction where busses can be reduced to limit the size of the equivalent network and number of components in it.

The topological reduction can be achieved by many techniques using matrix operation. The reduction can be done with Gauss-Rutishauser elimination, also called Ward equivalent, which use the admittance matrix as a starting point, se 2.1.6.1 for how to create the bus admittance matrix. Reduction can also be done looking at one specific bus, a typical such reduction is reduction of a centre bus in a star bus system creating a delta connected bus system. Equation 2.16 is describes the new admittance derived from old admittances in the system, k here describing the centre bus in the star system. [20]

Equation 2.16

The directly connected busses i.e. its neighbours will be affected in such a way that the admittance needs to be changed between these busses. Busses in the system not directly connected to the bus being removed will not be affected by the removal. With the star – delta equivalent, a change of impedance needs to be regarded in lines AB, AC and BC. [20]

Figure 2.8 Busses connected in star and delta with line impedance Z [20]

In the case with the star connected bus Equation 2.16 can be written as seen in Equation 2.17. When taking into consideration that the admittance is the inverse of the impedance the equation can be rewritten as seen in Equation 2.18. [20]

Equation 2.17

Equation 2.18

Considering a circuit which consists of only three busses connected in serial Equation 2.18 is simplified and is expressed by Equation 2.19.

Equation 2.19 2.1.6 Static Modelling

2.1.6.1 Bus Based Equations For computing the power flow in an electrical system it is necessary to compute voltage magnitudes and phase angles at each bus in the system. The input data for these calculations are the voltage magnitudes V, the load angle δ, the net real power P and the reactive power Q. Two of these parameters are always input data at each bus in the system and two are calculated by the power flow program. The bus categorization is as follows: [17]

 Swing bus, also known as slack bus o The electrical model can only contain one swing bus being the reference bus for other busses in the system. Input data are the voltage and the load angle, normally as 1 p.u. and 0 . The swing bus is not a real bus. It is only a way to help model the system and perform numerical calculations.  Load bus o Normally the most common bus in a power system where P and Q are input data and V and δ are calculated.  Voltage controlled bus, also known as generator bus o Normally the bus to which a generator is connected. P and V are input data and Q and δ are calculated. With this bus there are also some extra input data, one can here also decide for example which interval a generator can operate between i.e.

QMAX and QMIN. A bus to which a tap-changing transformer is connected to should also be designed this bus type.

Computer programs calculating power flows in electrical system use the bus admittance matrix which forms Equation 2.20 together with the voltage and current. The bus admittance matrix is built up on the diagonal by the sum of admittances connected to the specific bus in question and all off diagonal elements are the negative sum of all admittances between the specific bus and other busses in the system. [17]

Equation 2.20

Equation 2.20 is combined of the bus admittance matrix Y, the column vector of the bus voltages V and the vector of current sources I. The system admittance and the bus connections can be input data for the computations which result in the bus admittance vector. With the bus admittance vector and the current at each bus the bus voltage can be determined. [17]

For one line these calculations can be made manually but for a system with many components this builds up to complex matrix calculations best suited for computer computation. There are many different programs for computing power flow problems e.g. PSS/E, PSCAD, Power World Simulator, Aristo, etc. The solution type used to solve can also vary but the most common is the Newton- Raphson method. [17]

Since power flow bus data consist of the real and reactive power for load busses, and real power and voltages for generator busses. Equation 2.20 has to be rewritten while using Newton-Raphson methods of solving matrix equations, but it is still the base for the calculations. [17]

2.1.6.2 Line Approximations Transmission lines characteristics can be modelled for calculations and depend on the length of the transmission line. A short transmission line, while having a 50 Hz system, shorter than 100 km can be represented as Figure 2.9 i.e. only with series resistance and inductance. The subscript S and R stands for the sending end and receiving end voltage and current and is the length of the line.

Figure 2.9 An equivalent circuit of a short transmission line

For a medium length transmission line the admittance, Y, cannot be neglected, and is represented by the admittance making the equivalent circuit change to a Π-circuit with the admittance connected in parallel with half at each end of the circuit, as seen in Figure 2.10. It is the same equivalent seen in Figure 2.5 but here with the admittance divided between the sending and receiving end. Medium- length lines ranges from 100 to 300 km.

Figure 2.10 An equivalent circuit of a medium transmission line

The admittance is dependent on the conductance and the capacitance by:

Equation 2.21

The conductance is normally small enough to be neglected in transmission line calculations making the admittance in Figure 2.10 and the equations below only dependent on the capacitance.

Equation 2.22 shows the relation between the sending and receiving currents and voltages for the circuits where the parameters A, B, C and D depends on the constants R, L and C and thus changes depending on the different length of the transmission lines.

Equation 2.22

The equation can be written in matrix format:

[ ] [ ] [ ] Equation 2.23

For the short line equivalent circuit the A, B, C, D matrix is as shown below:

[ ] [ ] Equation 2.24

Equation 2.25 shows the relations for a medium length line where the more complex matrix also includes the admittance Y.

[ ] [ ] Equation 2.25

The expressions above are as stated approximations where the impedance and admittance is seen as lumped together. In reality these characteristics of the lines are uniformly distributed along the line. To account for this one can study line section of length Δx which changes the relations. The relations do not change for the short transmission lines but for medium lines with the admittance connected in parallel we get a new A, B, C, D matrix, shown in Equation 2.26. The equation together with Equation 2.23 makes it possible to solve for voltage and currents from one bus to another. [17]

[ ] [ ] Equation 2.26

2.1.6.3 Contingency Analysis Contingency analyses are introduced to make sure that the system maintains a certain system security i.e. with static operation that means; operation without overloads and voltage levels within grid code levels. The contingency refers to changes in the system that might weaken the electrical power system and is thus one way to determine weak points in the power system in need of upgrades. There are different types of contingency analyses from the most basic only considering the outage of a single transmission line to more complex analyses considering multiple line outages or/and loss or change of generators/loads in the system. Even open lines i.e. unused, can be closed in a contingency analysis. [22]

N-0 Base Case

Yes Violations? Report/Fix

N-1 Contingency

Yes Violations? Report/Fix

Final Report

Figure 2.11 Schematic scheme over a contingency plan [23]

The most basic contingency can be described as an N-1 contingency analysis where one component from the model is disconnected; in the electrical system this can either be on purpose, for maintenance, upgrades etc. or by an accident or fault. [23]

2.2 Wind Power There are several ways to extract the power of the wind but there are mainly two different types of wind turbines are used; HAWT (Horizontal Axis Wind Turbine) and VAWT (Vertical Axis Wind Turbines). Today the three bladed HAWT is the most common wind turbine. Three blades are generally favoured because it has lower power pulsations, as the blade passes the tower, than a HAWT with fewer blades. Moreover a three bladed wind turbine is more aesthetically appealing than a wind turbine with fewer blades than three, whilst the turbines are rotating. Any number of blades can be used on HAWT, although if too many blades are used they tend to interfere with each other aerodynamically. Figure 2.12 shows a typical arrangement for a HAWT where Gen stands for generator G/B for gear box and T for transformer. [20]

Figure 2.12 A typical arrangement for a HAWT [20]

The power of the wind is extracted by aerodynamically designed blades that produce a lift force along the length of the blade. This aerodynamic force integrated along the length of the blade produces the torque on the turbine shaft. The turbine shaft is connected to the gearbox which increases the shaft speed. The gearbox and generator is placed in the nacelle at the top of the tower. The generator is connected to the electrical power system via a transformer. [20]

The power in the wind varies with the cube of the wind speed and is described with the following equation.

Equation 2.27

where is the power that can be extracted from the wind, is the air density, is the swept area of the blade, is the coefficient of performance for the turbine and is the wind speed. For the wind turbine to be able to absorb all the kinetic energy in the wind, the wind speed after the turbine has to be zero. This is impossible because the airflow has to be continuous. The theoretical maximum of energy that can be absorbed by the wind turbine is called the Betz limit and defined when Cp is equal to 16/27. The Betz limit is derived from an infinitely thin rotor, which represents the turbine, and a fluid flowing at a certain speed. In reality the coefficient of performance Cp for a wind turbine is lower, because also varies with the tip speed ratio λ. A typical value for Cp is around 0,4. [20]

Figure 2.13 A typical Cp/λ curve for a wind turbine [20]

A curve, as seen in Figure 2.13, for a specific wind turbine helps determent at what tip speed ratio the wind turbine extracts the maximum amount of power in the wind. This is a powerful tool when designing wind turbines. [20]

Figure 2.14 Turbine power as a function of the wind speed [20]

Figure 2.14 shows the wind turbine power as a function of the wind speed. In order for the wind turbine to produce power the wind speed need to be greater than vw1, which is called the cut in speed and lies typically around 3-4 m/s. If the wind speed is lower than the cut in speed the power in the wind is not high enough for the generator to produce energy. With increasing wind speed the turbine produces more power until it reaches point A. At point A the generator produces its maximum power which happens at wind speed which is the rated wind speed, more specifically the wind speed the turbine is designed for. For higher wind speeds than the rated wind speed the turbine is regulated with either pitch regulation or stall regulation to extract the right amount of power from the wind preventing the wind turbine from accelerating. The power output remains constant until the wind speed reaches , typically around 25 m/s, which is called shut down wind speed; where the wind turbine shuts down to prevent it from breaking. [20]

The wind is the most important aspect for wind power. Therefore the wind is measured at a desired location for building a wind power plant over at least one year. Another important aspect of wind power is the capability factor CF that is defined as seen in Equation 2.28 for a period of one year.

Equation 2.28

CF is the ratio between actual energy production and the maximum amount of energy that could have been produced if the plant had operated at full capacity over the designated time period. It can be used to see how efficiently a wind power plant has been operating over one year, a typical value is around 0,2. [20]

2.2.1 Moldova´s Wind Resource In order to decide the wind potential for a specific location, a large amount of data for that specific area is needed. This can be done with a variety of measuring instruments such as anemometers and direction sensors. Especially important to investigate is the wind velocity probabilistic distribution, daily and seasonal variations and prevalent wind directions. These are all important aspects for the efficiency or inefficiency for utilization of the wind power. Another important aspect to account for is the capability factor.

As described in Equation 2.27 the energy in the wind is proportional to the cube of the wind speed. This relation is fundamental in all wind power. Statistical data with a high level of credibility is hard to obtain because it requires systematic observations during a long period of time, at least for one year but preferable longer, and at hub height of the wind turbine. These measurements is often performed by companies who are specialized in determining the wind power potential, this data is very expensive to retrieve. However there are ways to determine the wind power potential with data measured at the lower heights, which means that data from meteorological weather stations, often 10-12 meters above ground level, can be used to determine the wind power potential. These measurements are often influenced by the surroundings such as trees and houses.

Two different methods are mainly used to determine the wind power potential for a certain location. One model is developed in Europe and one in USA. The American model is developed by NASA together with the U.S.A Air Force and is based on the dynamic climate theory which means that the model doesn’t require a lot of meteorological data, but instead requires more computing processing power. The European model is called WAsP (Wind Atlas Analysis and Application Program) and has been used when drawing the European wind atlas. Several European countries such as Austria, Croatia, Slovenia and Czech Republic etc. have used WAsP when drawing their wind atlases. Moldova has several meteorological stations which has recorded the wind direction and the wind velocity every three hours during a period of more than 10 years and have therefore chosen to use WAsP to draw their wind atlas.

From the calculations given by the WAsP program and with the data from weather stations, a wind atlas can be derived. The wind atlas main goal is to present the wind energy resource in the area of the weather station, thus estimate the wind energy potential in the region and with this information you can identify the best locations for building a wind turbine or a wind power park. A wind atlas produced over Moldova can be seen in Appendix B [14]

The wind atlas is not very accurate and cannot be used as reference when deciding exact locations for wind power plants, further investigations must be made. The wind atlas only gives a hint of the wind conditions. According to the wind atlas the southern region is best suited for wind power installations.

There are other publications of the wind potential in Moldova from the beginning of the 1990th; these predictions give a negative picture of the wind power potential in Moldova. However these investigations where based on wind data from the meteorological station in Chisinau, which is located in the centre of Chisinau and is surrounded by a variety of obstacles and cannot be considered as a good reference station. [14]

2.2.2 Economy The payback method is used for determining the time it takes for an investment to repay the sum of the original investment. It’s a useful tool when investigating if an investment is profitable in a reasonable timeframe, or when comparing different investment proposals trying to determine which one is the most profitable. Originally the payback method doesn’t account for other factors such as inflation or discount rate but there is a discounted payback method where these factors are taken into account. It’s described with the following equation:

∑ Equation 2.29

where is the net cash flow; which is the cash inflow minus outflow, is the discount rate and is the time. [24]

Figure 2.15 An investment and payback curve for a nonspecific project [25]

Figure 2.15 shows a typical investment and payback curve. At the start of the project money is invested in the project, this called the investment period. Until the project reaches the self-funding point the project just costs money. Typical cost during the investment period for wind installations can be wind measurements, calculations of wind potential, project management and off course costs for building the wind power plant. At the self-funding point, the investment is starting to earn money and the investors are getting the invested money back. At the breakeven point the investor has got all the invested money back and beyond this point all the money earned is pure profit.

2.3 Method Five potential locations were chosen for wind power installations. To simulate the effects new generation would have on the electrical power system of Moldova a model for power flow simulations is constructed. In the model different scenarios is simulated to show installation capacities for each location separately and for all sites at the same time.

2.3.1 PSS/E Power flow simulations are done by computer programs, with approximations of transmission lines, transformers and other components of the electrical power system. There are a number of different programs on the market, for this project PSS/E (Power System Simulator for Engineering) is used. The software has efficient tools for simulating static power flows, contingency analysis, and it also has the possibility to automate these processes. The automation process in PSS/E can be executed in three different ways, in this project Python programing was used to simulate the different scenarios described later in chapter 2.3.3 . A description over how a contingency analysis can be executed in PSS/E together with the creation of important files needed for the process can be seen in Appendix S. The appendix also describes in more detail the different ways to automat in PSS/E.

2.3.2 Building the Model There were no existing models over the Moldovan electrical power systems that could be used in the project. A model was created with the help of the Technical University of Moldova (TUM), situated in Chisinau, specific for this project. TUM provided an equivalent circuit over the Moldovan electrical power system. The equivalent circuit describes a 330 kV electrical power system, partially seen as the green line in Appendix A, stretching from big cities in Moldova such as Chisinau, Baltsi and Tiraspol in Transnistria, going in to Ukraine and finally back to Moldova again completing a full circle. The equivalent circuit can also be seen as the green part in Figure 2.16. The model is a 7 bus system, out of which 3 busses are situated in Ukraine, it includes 5 branches, 3 generators and 5 loads divided between the two areas; Moldova and Ukraine. The complete model along with its specified data, Table D-1 to Table D-5, can be seen in Appendix D.

Detailed data of the southern parts of Moldovan electrical power system was also provided, the data was provided in the form of schematics over the grid also stating length and type of the transmission lines. The properties of the specific lines are given in Table E-1. With this given data the initial model was extended by 17 busses located in the southern region of Moldova. The line diagram over the complete equivalent model is shown in Figure 2.16, detailed data over the model can be seen in Appendix F.

Load

Generator

Three winding transformer

Switched shunt

400 kV Line

330 kV Line 110 kV Line

Active Power Flow

Reactive Power Flow

Line Offline

Figure 2.16 One line diagram over the PSS/E model

The extended part is the main focus of the report and describes mainly a 110 kV system with the only exception being one 400 kV line, the blue and yellow part in Figure 2.16. The system is connected to the initial equivalent circuit, green in the model, at three locations. The different voltage levels also introduces 4 three winding transformers to the system. Not all busses and thus also not all branches are modelled but all power flow paths in the southern regions 110 kV system are accounted for.

All values in the model are expressed in per-unit values, the voltage values uses respective base voltage value as base value i.e. 110 kV, 330 kV and 400 kV. The impedance values are expressed with the base impedance values given for each voltage levels see Table E-3 in Appendix E. The 400 kV line is also long enough so the admittance needs to be regarded, the relation between base impedance and base admittance can be seen in Equation 2.15. [26]

2.3.2.1 Busses The model consists of 24 busses, the initial 7 have 330 kV as their base voltage, 11 busses are connected within the 110 kV grid and 2 busses are situated on the 400 kV line between Vulcanesti and MGRAS, in Transnistria. There are also 4 busses in the 35 kV system, each connected to a three winding transformer, these busses have no meaning except for modelling the transformer i.e. they have no load or generation connected to them and can thus be seen as a part of the three winding transformer not contributing to any system losses by themselves.

The swing bus is the MGRAS bus, situated in Transnistria and is chosen as such because of the high electrical energy imports from Transnistria. It is also an appropriate swing bus because of the excessive generation capacity of MGRAS. The swing bus input voltage is increased a bit from standard 1 p.u. to 1,0455 to increase the system overall voltages. Also the two generators in Ukraine has an increased voltage to 1,0455 for the same reason.

2.3.2.2 Branches All branches in the 110 kV system are relatively short, the longest is still less than 50 km and as described in section 2.1.6.2 the admittance is thus neglected. The 400 kV line is of medium length type and thus also needs to take into consideration the admittance, this value can be located in Table F-2, under the heading charging, in Appendix F

There is a branch between Tarecklia and Ciadyr that is marked in the model but it is not in use as can be seen in Figure F-1 and Table F-2. The line is an existing one but for reasons unknown to this project is not in use at the moment.

The extended southern system do not account for all transmission lines but all power flows paths are accounted for, thus only transmission lines connected in series are removed. The impedance in these lines has been accounted for by the method of Equation 2.19. Line data can be seen in Appendix EThe total impedance values for the lines are given in Table E-2 and recalculated using Table E-3 and Equation 2.14, the resulting impedance values can be seen in Table E-4. The used rating for the equivalent lines is the thermal level, rate A in PSS/E, and the rating for each equivalent line is the rating of the connected lines with the lowest individual rating

2.3.2.3 Shunt Elements There are two switched shunts connected to the grid, these do not operate on a daily basis, were one is only used during the night, and were thus neglected. This because the fact that the model simulates maximum load flows and shunt compensation should only be included if it is connected for use whenever needed which not is the case here. [26]

2.3.2.4 Transformers The four transformers connected to the system are tap transformers and are simulated to operate as voltage control step transformers with a 15 step interval within plus minus 10 % of base voltage. At each transformer position there are two three winding transformers, due to constraints in the free university edition of PSS/E the model is built up by one transformer at each transformer point. Equivalent values representing two transformers in one were provided by TUM [26] and the ratings were multiplied by two due to the doubled capacity; the transformers at each point are identical.

Three winding transformers in PSS/E are modelled as three two winding transformer connected together in a star bus, this star bus is not visible by the user. The nominal voltage specified for each winding is the base voltage for respective bus each winding is connected to. The nominal voltages for each winding is by default zero and is interpreted by PSS/E as the base voltage for the bus to which the transformer is connected [27]. The tap transformers operate with voltage control for the busses in the models extended system i.e. not for busses in the 330 kV equivalent system provided by TUM.

2.3.2.5 Loads and Generation Loads and generation in the model are based on maximum load data for 2011 [26], they can be seen allocated to important busses for the model in the sketch in Figure 2.17.

Baltsi is the northern metropolitan in Moldova, both in the aspect population and electrical network. In the model all loads in northern Moldova are allocated to Baltsi. The third CHP, CHP 3, in Moldova is located within Baltsi and constitute together with a small HPP, located close to Baltsi at the border to Romania, the generation connected to Baltsi in the model.

Moldova has a small export of energy to Romania made possible by back to back converters. The export is included in the load located at Chisinau. The generation in Chisinau consists of CHP1 and CHP 2.

Straseni is a big electrical hub located just north of Chisinau in the centre of Moldova, as can be seen in Figure A-1 in Appendix A. All loads in central Moldova are allocated to Straseni.

To the MGRAS bus is apart from the huge gas fired electrical complex located in Transnistria also the HPP on the river Nistru allocated. The loads in eastern and southeaster Moldova are allocated to the MGRAS in the model.

The generation and export/import to Ukraine can be seen as divided in two. To the south there is an export of electricity to the Odessa region in Ukraine, the Ubolgr bus in the model, see Figure F-1 in Appendix F. To the north the Ukrainian busses connected to the 330 kV system is represented.

Figure 2.17 Load and generation in Moldova, rectangles represent generation and circles loads

There are some differences between stated values and values in the model as can be seen in Table 2.1 and Table 2.2. The difference is due in order minimize the difference between power flows in this model and more complex models used at TUM.

Table 2.1 Load values for the active generation and consumption

Values Baltsi Straseni Chisinau MGRAS Ukraine Generation (MW) 34 0 231 703 425 Load (MW) 170 87 382 129 438

Table 2.2 Model load values for the active generation and consumption

Model Values Baltsi Straseni Chisinau MGRAS Ukraine Generation (MW) 34 0 234 703 428 Load (MW) 171 87 391 220 444

The reactive power compensation for all generators in the system has a maximum production of reactive power, the maximum is calculated with the power factor equal to 0,8 using Equation 2.5 and Equation 2.6. The biggest source of generation in Ukraine comes from UDSGEC81, which is a HPP. This source gives a lot of reactive power compensation possibilities; positive and negative. The second Ukrainian generator, ULDTEC81, takes into account the balancing capacity of Ukraine and has possibilities to compensate enough reactive power necessary to keep its fixed voltage point.

Five generators were added to the southern region in the model each one representing a connection point for a wind power plant. The exact locations are good from a wind potential perspective as well as from a grid stability perspective [26]. The locations are Besarabeasca, Zarnesti, Leovo, Ciadyr and Cimislia and can be seen marked on the wind potential map in Figure B-1 in Appendix A.

2.3.3 Scenarios A contingency analysis is first performed on the model as it is, symbolizing the Moldovan electrical system as it looks today with a maximum load scenario. This base case scenario is later used for comparison to analyse changes in the system when installing wind power.

Two scenarios were developed to examine the wind power potential in the southern region of the Moldovan electrical system. The scenarios were executed with the help of different Python scripts making it possible to automate some processes. One part of the Python script used to automate the contingency analysis in the base case and the scenarios was re-used in all scenarios, se the script in Appendix G.

The contingency analysis takes into account two parameters as limiting factors:

 Transmission line capacities  Voltage level grid codes within ± 10 % of base voltage

The generation at each location is purely active i.e. the reactive power is limited to operate only at 0 MW. As stated under 2.1.6.1 generator busses are designed to keep voltage levels at a specific level, normally at 1 p.u. Designing the generators to have 0 MW output or input of reactive power makes the generator bus operate as a load bus with negative active power output and with varying voltages. The two scenarios are also tested where the generators have the possibility to consume or produce reactive power, thus operating as a “true” generator bus. The reactive power consumption or production occurs to keep the voltage levels at 1 p.u. making generator acting towards stabilizing the system.

There is a natural limit for what is possible to install given by the lines connected to each point of connection. As shown in the figure at Appendix Fone can see that each installation point has exactly two lines connected to it. This means that, with the contingency analysis, the generators can never have a higher installed power than the lowest transfer capacity of any of the two transmission lines connected to the bus i.e. after regards are taken to the loads connected to each bus and the losses in the lines. This gives a definite maximum for the installed power for each of the five sites. A description of each scenario follows below.

2.3.3.1 Scenario I The five points of installation i.e. Besarabeasca, Zarnesti, Leovo, Ciadyr and Cimislia, are tested separately. Installation is increased using a specific Python script for scenario I, see Appendix H, it increases the generation values with one MW at a time. In between each increase the script calls upon the main script to perform the contingency analysis. A separate text file is created containing all values which did not lead to violations in the contingency analysis. The value then needs to be read manually. The script operates according to Figure 2.18 where the generation at generator G is increased as long as no violation is reached in the contingency analysis.

Grid + 1 MW

No violation N-1

Violation

Stop Simulation

Figure 2.18 The algorithm for the contingency analysis where generator G is increased 2.3.3.2 Scenario II The second scenario intends to find the total maximum production possible in the southern region of Moldova. The situation is an optimization problem where the different sites generation is the variable parameters and line capacities and voltage levels are limiting factors. Finding the maximum total potential of generation is highly difficult only testing manually; that is to which level of generation the different generators should operate with in order to find a maximum total generation. There are too many parameters to easily optimize this problem; the level of unpredictability is too high. To optimize this problem a Monte Carlo simulation was used. The concept of the Monte Carlo simulation is working with random numbers, in this case using the built in random generator of Python. A new script was written to give each generator a random number from 0 to maximum value, given by line capacities, the results are then saved in text files for further processing in Excel. The algorithm is basically the same as in Figure 2.18 if a random generator replaces the plus 1 MW and working with all five generators at the same time. The script can be seen in Appendix I

To find a maximum value a high amount of iterations needs to be made, the script is run with 100000 iterations. The solution1 is then tested and if increase is possible a new simulation is made with ±5 MW of given maximum value. The solution provides a maximum; it cannot be proved to be the absolute maximum. The maximum is tested by increasing each generator one by one by one MW separately.

2.3.4 Economy The payback method is used to determine the payback time for wind power plant installation in Moldova. This was done by plotting the capital value in relation to time and determining at what year the capital value reached the breakeven point. The capital value is determined with Equation 2.29. Assumptions made are as follows. The investment cost for a wind power plant used in this report is 1,1 million €/MW installed capacity, this number also include costs for maintenance during a lifespan of a wind power plant. This cost can differ around 1,0 to 1,5 million €/MW depending on the location for the wind power plant, type of wind power plant, reactive power compensation

30 devices, etc. [28]. A life time for a wind power plant is ca. 20 years. Two different capacity factors,

and were used, this because the capacity factor of a wind power plant differs from location to location and year. The different capacity factors give an interval of the payback time instead of one definite value. In this report three different discount rates of 6, 8 and 10 % were used in the analysis. The electricity price used was 0,11 €/kWh [29] with the sensitivity analysis of ± 20 %. The payback time is also compared between including and excluding income from CERs. The cost for

CER:s which was used in the calculations was 4 €/tonne CO2 [30].

Chapter 3 Results The results from the different scenarios are described in this chapter. The Base case, Scenario I and Scenario II are described in detail. After follows the reduced electrical imports possible from the results in Scenario I and Scenario II. The chapter ends with the economic results.

3.1 Base Case Running a contingency with the Base Case scenario does not give any violations in the systems i.e. the voltage levels are kept within voltage limits and the lines supply sufficient capacity to transfer the power. One can also note that the lines are not used close to rated values i.e. there is a lot of potential for new generation in the system, see Appendix Jfor a loading table report for the contingency which show the usage of lines in comparison to capacity and voltage reports for each bus at all contingencies and the line diagram in Appendix Kwhich also show how much each line is loaded.

Table J-1 in Appendix J shows the highest and lowest values for the loading report for the base case. It shows that the highest voltage is at the Vulcanesti bus, throughout the entire contingency analysis. For low voltages with a contingency the Ciadyr bus and the Comrat bus are dominating; where they represent the lowest voltage in the system. The Zarnesti and Cimislia busses have the lowest voltages at one contingency each. The overall lowest voltage can be found at the Ciadyr bus with 0,933 p.u. when the line between Ciadyr and Vulcanesti is tripped.

A histogram is created showing the dispersion for the voltage levels throughout the contingency analysis; it can be seen in Figure 3.1. All voltage levels at all busses in the focus area, the 110 kV system, are sampled and then stored in the bins making up the frequency in the histogram. The histogram shows that the majority of voltage levels lie close to one p.u.

45 40 Base Case 35

30 25

20 Frequency 15 10 5 0 0,93 0,94 0,95 0,96 0,97 0,98 0,99 1 1,01 1,02 1,03 Voltage [per unit]

Figure 3.1 The dispersion of voltage levels for the base case contingency analysis

3.2 Scenario I The results from scenario I where the generation at each location is increased separately are shown in Table 3.1.

Table 3.1 Maximum generation before violation in the contingency report

Besarabeasca Zarnesti Leovo Ciadyr Cimislia Maximum Generation [MW] 60 25 30 84 102

If generation is increased by 1 MW at each location the contingency analysis results in violations. These violations can be seen in the contingency report in Appendix L. The report shows that for Besarabeasca, Zarnesti, Leovo the limiting factor is high voltage levels and for Ciadyr the limiting factor is low voltage levels. For Cimislia the limiting factor is the capacity on the transmission lines.

The violations are spread out; no contingency of any single line causes violations for more than one location and no contingency causes the same violation. Comparing the generated values with the maximum generation possible before the line capacity is reached, Table 3.2, we get the extra generation potential in Table 3.3 i.e. if voltage faults were to be compensated for.

The maximum generation at each point due to capacities of the transmission lines is shown in Table 3.2.

Table 3.2 Maximum values regarding only line capacities

Besarabeasca Zarnesti Leovo Ciadyr Cimislia Values in MW 84 87 83 96 102

If no regard is taken to the voltage limits i.e. when the only limiting factor is the capacity of the transmission lines, the extended generation potential is increased and can be seen in the table below.

Table 3.3 Extended generation potential until line capacity is reached

Besarabeasca Zarnesti Leovo Ciadyr Cimislia Generation potential [MW] 24 62 53 12 0

3.2.1 Scenario I, With Reactive Power Compensation For the scenario using one generator at the time with reactive power compensation gives us results shown in Table 3.4.

Table 3.4 Possible generation capacity with reactive power compensation

Besarabeasca Zarnesti Leovo Ciadyr Cimislia New Generation [MW] 74 78 74 91 98 Produced Reactive Power [MVAr] -19,7 -19,3 -22,8 -16,8 -19,6 Increased Generation [MW] 14 53 44 7 -3

When generation, as in scenario I, is increased by 1 MW the resulting overload report can be seen in Appendix M. According to the report the only limiting factor for further generation is the line capacity; faults occur only at lines directly connected to the busses that is generating and only when the other line directly connected to the bus is tripped. One exception can be seen in Besarabeasca where only the tripping of the line going to Chisinau results in breach of capacity for the other line connected to Besarabeasca. The extra generation does not reach values given by Table 3.4 because the reactive power produced also uses line capacity.

3.3 Scenario II The first iteration process with 100000 iteration can be seen visualized in Appendix R, it shows a line diagram with all outcomes that did not reach violation, Figure R-2 in the appendix shows a histogram over the outcome for the simulation. The first Iteration method was followed by an iteration method with an interval close to values given for maximum generation in the first step. The second iteration was then followed by a ±5 MW iteration, se Figure R-3, giving the results shown in Table 3.5.

Table 3.5 Maximum generation for each location giving maximum total generation for the region

Besarabeasca Zarnesti Leovo Ciadyr Cimislia Maximum Generation [MW] 29 14 31 84 102 Total Maximum Generation [MW] 260

An increase of 1 MW for each generator separately results in voltage violations for all points except for Cimislia, where the capacity once again is the limiting factor. The violations can be seen in Appendix Lwhere voltage violations occur with the contingency analysis when lines represented by single 7 and 11 are removed; single 7 is the line between Zarnesti and Vulcanesti and single 11 is the line between Comrat and Cimislia. In total there are violations at five occasions caused by high voltage, out of these five; one is at the Zarnesti bus, three at the Ciadyr bus and one at the Besarabeasca bus. A histogram showing the dispersion for the voltage levels throughout the contingency and can be seen in Figure 3.2.The histogram shows that voltage levels, compared to the base case as seen in histogram in Figure 3.1, has increased and several voltage levels are almost as high as 1,1 p.u. which is the maximum voltage limit according to grid codes.

40 35 Scenario II 30 25 20

Frequency 15 10 5

1,1

0,93 0,94 0,95 0,96 0,97 0,98 0,99 1,01 1,02 1,03 1,04 1,05 1,06 1,07 1,08 1,09 1,11 Voltage [per unit]

Figure 3.2 A histogram of the dispersion of voltage levels with a contingency analysis

3.3.1 Scenario II, With Reactive Power Compensation To derive the results using generator busses with variable reactive power output the iterations from earlier have to be repeated. Due to the Monte Carlo method the values derived cannot be used for direct comparison but rather a general view that there is a high increase of the total production. Histograms showing the two different cases in scenario II can be seen in Appendix R

Table 3.6 Maximum generation for each location giving maximum total generation for the region

Besarabeasca Zarnesti Leovo Ciadyr Cimislia Maximum Generation [MW] 56 68 68 91 72 Produced Reactive Power [MVAr] -8,3 -9,7 -14,7 -6,1 -6,5 Increased Generation [MW] 27 54 37 7 -30 Increased Total Generation [MW] 95

The overload reports in Appendix O for the contingency analysis where each generators generation is increased by one MW separately shows that the voltage values is a problem only at one location and only when one line is tripped. The voltage levels sink below grid code values for the Tarecklia bus when the line between Chisinau and Cimislia is tripped. This occur no matter which generators generation is increased by 1 MW. The bus voltage levels through a contingency analysis are shown below.

Scenario II - Reactiv Power Compensation 100

40 Frequency 20

0,9 1,1

1,04 0,91 0,92 0,93 0,94 0,95 0,96 0,97 0,98 0,99 1,01 1,02 1,03 1,05 1,06 1,07 1,08 1,09 1,11 Voltage [per unit]

Figure 3.3 A histogram of the dispersion of voltages levels with a contingency analysis

Comparing the results with Figure 3.1 and Figure 3.2 one can see a decrease in voltage levels with some values lying close to 0,9 which is the lowest value allowed according to grid codes. Overall voltage levels are close to 1 p.u. showing a stable system.

The line capacity is also a limiting factor when the Ciadyr generation is increased; line capacity is surpassed on the line between Ciadyr and Vulcanesti as well as for the line between Comrat and Ciadyr. As can be seen in Appendix Kthe loading of the lines has increased by much from the base case.

1.1 Reduction of Imported Electric Energy The reduction of electric energy depends on the capability factor of the wind power park. Reduction will be reduced from the imported electrical energy in Moldova as it was in 2010 i.e. 3038 GWh which stood for 74 % of the total consumed electrical energy. The reduced imports are not equal to the generated power from the wind power plants but rather the reduced production from the swing buss in MGRAS.

3.3.2 Scenario I The first scenario gives two different reduction possibilities; one with the generators producing a net zero reactive power contribution, Table 3.7, and one where the generators can compensate with reactive power, Table 3.8.

Table 3.7 Imported electrical energy reduction due to wind power installations

Besarabeasca Zarnesti Leovo Ciadyr Cimislia Installed Power [MW]: 60 25 30 84 102 Reduced Power at MGRAS [MW] 57 25 30 77 95 Capability factor 0,1 Reduced Production at MGRAS [GWh] 50 22 26 67 83 Reduced Electrical Imports [%] 1,6 0,7 0,9 2,2 2,7 Capability factor 0,3 Reduced Production at MGRAS [GWh] 57 25 30 77 95 Reduced Electrical Imports [%] 4,9 2,2 2,6 6,6 8,2

Without the possibility to produce or consume reactive power the reduced electrical energy imports vary depending on location between 1 to 8 % of total imported electrical energy. The reduction is highly dependent on the specific location of installation where installations in Cimislia give the highest reduction.

Table 3.8 Imported electrical energy reduction with reactive power compensation

Besarabeasca Zarnesti Leovo Ciadyr Cimislia Installed Power [MW]: 74 78 74 91 98 Reduced Power at MGRAS [MW] 66 67 55 79 90 Capability factor 0,1 Reduced Production at MGRAS [GWh] 58 59 48 69 79 Reduced Electrical Imports [%] 1,9 1,9 1,6 2,3 2,6 Capability factor 0,3 Reduced Production at MGRAS [GWh] 173 176 144 207 236 Reduced Electrical Imports [%] 5,7 5,8 4,7 6,8 7,8

In the case where the generators are able to consume or produce reactive power the reductions increase to between 2 to 8 % of total imported electrical energy. The location with reactive power compensation the location does not matter as much as without reactive power compensation.

3.3.3 Scenario II Scenario II gives as scenario I two different electrical energy reduction possibilities both seen in Table 3.9.

Table 3.9 Imported electrical energy reduction due to wind power installations

All generators without All Generators with reactive reactive power power compensation compensation Installed Power [MW] 260 355 Reduced Power at MGRAS [MW] 234 293 Capability factor 0,1 Produced Electricity at MGRAS [GWh] 204 256 Reduced Electrical Imports [%] 6,7 8,4 Capability factor 0,3 Produced Electricity [GWh] 613 768 Reduced Electrical Imports [%] 20,2 25,3

The electrical reduction without voltage production or consumption can reduce the electrical energy imports for Moldova by between 7 to 20 % depending on the capability factor of the wind power park. With the possibility to produce or consume reactive power this value increases to between 8 to 25 %.

3.4 Economy This section contains an economic analysis of the economic potential for building wind power plants in Moldova. The payback time is determined for two different capability factors and is compared with three different prices of electricity and three different discount rates. The results are presented below. EP stands for electricity price.

Payback time, capability factor = 0,3 2000000 EP=0,09€/kWh, r=6% 1500000 EP=0,09€/kWh, r=8% 1000000 EP=0,09€/kWh, r=10%

500000 EP=0,11€/kWh, r=6%

Euro 0 EP=0,11€/kWh, r=8% 0 1 2 3 4 5 6 7 8 9 10 EP=0,11€/kWh, r=10% -500000 EP=0,13€/kWh, r=6% -1000000 EP=0,13€/kWh, r=8% -1500000 EP=0,13€/kWh, r=10% Years

Figure 3.4 Payback time with a capability factor of 0,3

In Figure 3.4 the payback time when the wind power plant has a capability factor of 0,3 is shown. The payback time varies from ca. 3 to 7 years depending on the electricity price and interest. The graph also shows that the price of electricity has bigger impact on the payback time than the interest.

Payback time, capability factor = 0,1 800000 600000 EP=0,09€/kWh, r=6% 400000 EP=0,09€/kWh, r=8% 200000 EP=0,09€/kWh, r=10% 0 EP=0,11€/kWh, r=6% -200000 0 2 4 6 8 10121416182022242628303234363840

Euro EP=0,11€/kWh, r=8% -400000 EP=0,11€/kWh, r=10% -600000 -800000 EP=0,13€/kWh, r=6% -1000000 EP=0,13€/kWh, r=8% -1200000 EP=0,13€/kWh, r=10% Years

Figure 3.5 Payback time with a capability factor of 0,1

In Figure 3.5 the payback time when the wind power plant has a capability factor of 0,1 is shown. The payback time varies from 14 years to never. In this case there is no significant difference on who has the biggest impact on the payback time. However with high electricity price the investment reaches the breakeven point with all the three different interests while with low electricity price only reaches the breakeven point in one case. The lifespan of a wind power plant is usually around twenty years and in this case only three scenarios pays back before twenty years.

Paybacktime including CER, capability factor = 0,3 2000000 EP=0,09€/kWh, r=6% 1500000 EP=0,09€/kWh, r=8% 1000000 EP=0,09€/kWh, r=10%

500000 EP=0,11€/kWh, r=6%

Euro 0 EP=0,11€/kWh, r=8% 0 1 2 3 4 5 6 7 8 9 10 EP=0,11€/kWh, r=10% -500000 EP=0,13€/kWh, r=6% -1000000 EP=0,13€/kWh, r=8% -1500000 EP=0,13€/kWh, r=10% Years

Figure 3.6 Payback time including CER:s with a capability factor of 0,3

In Figure 3.6 the payback time when the wind power plant has a capability factor of 0,3 and including income from CERs is shown. In this graph the payback time is reduced from 3 to 7 years to 3 to 6 years. It’s also shown that the electricity price has bigger impact on the payback time than the interest.

Paybacktime including CER, capability factor = 0,1 800000 600000 EP=0,09€/kWh, r=6% 400000 EP=0,09€/kWh, r=8% 200000 EP=0,09€/kWh, r=10% 0 EP=0,11€/kWh, r=6% -200000 0 2 4 6 8 10121416182022242628303234363840

Euro EP=0,11€/kWh, r=8% -400000 EP=0,11€/kWh, r=10% -600000 -800000 EP=0,13€/kWh, r=6% -1000000 EP=0,13€/kWh, r=8% -1200000 EP=0,13€/kWh, r=10% Years

Figure 3.7 Payback time including CER:s with a capability factor of 0,1

In Figure 3.7 the payback time when the wind power plant has a capability factor of 0,3 and including income from CERs is shown. In this graph the payback time is reduced from 14 years to never to 13 years to never. Still there is no significant difference on which parameter that has the biggest impact on the payback time.

Chapter 4 Discussion Throughout the project many assumptions have been made, this affects the validity of the model. The results derived in this project have the model as base i.e. the results are true for this model but before the model has been verified with other models the results cannot be seen as true for the Moldovan electrical system. Because the model has been designed with real data over the Moldovan electrical system the results can give us a good indication of what possibilities and problems exists with wind power installations in the southern region of Moldova.

4.1 Scenarios All results are based on the model created in the project and all results thus have the same accuracy as data used to construct the model. The model does not have exact data and is much generalized with many parts as equivalents. Loads and generation are not exact and sometimes allocated to locations in the model far from actual locations. This means that the results do not have exact relevance but merely gives the possibilities for a general overview over possibilities regarding new installations in the southern region in Moldova.

The scenarios consider installations of power for one specific location or at all locations at once. Some sites could be optimized to have more power but this is not investigated in the project.

The scenarios are based on the model with maximum load flows and contingencies on the 110 kV lines only, it does thus not consider the low load scenario or changes that might occur with loads and generators within the system. These changes are likely to affect the maximum values possible to install.

All Scenarios are designed to stay within ± 10 % of base voltage. Using ±10 % of base voltage levels as limiting factors might seem high and it is true that for normal operations the grid code for the Moldovan electrical system states that the voltage levels should lie within ±5 % of base voltage levels, but extreme cases such as for a contingency where lines are tripped is here seen as extreme scenarios where ±10 % of base voltage levels are used [26].

4.1.1 Scenario I To upgrade the generation capacity for Besarabeasca one would have to build new transmission lines to upgrade the capacity, for the other locations cheaper solution could be found with the installation of shunt elements to consume reactive power in order to decrease the voltage levels in the busses. It would make most sense to upgrade the grid with such installations where most potential exists before line capacity is reached. According to Table 3.3 the locations of Zarnesti and Leovo would be best suited for such installations, regarding voltage stability.

The results in Table 3.4 shows that generation potential is highly increased at some busses when the generators are given the potential to produce or consume reactive power. The results are built on the fact that the voltage levels are kept at 1 p.u, this proves to be effective in increasing generation potential at some busses and also makes the specific bus a strong point regarding voltage in the region. For Besarabeasca the fact that the voltage is kept at 1 p.u. result in decreasing the generation capacity; the apparent power increases even though the active power decreases i.e. the Besarabeasca bus becomes very stable out of a voltage but on the other hand reduces possible active power output.

4.1.2 Scenario II The introduction of generation and the effect it has on voltage and capacity levels can be seen as stochastic but is not, it just depends on many factors that make it very difficult to predict what generation would be optimal at each location to generate a total maximum production for the region. To try to introduce generation at all five locations at the same time raises many questions about reliability. Our method of finding a maximum generation cannot be proven to give the absolute maximum, but a value close to maximum.

The result does thus only give a guiding value of how much new generation that would be possible in the southern region of Moldova. It also shows quite clear that some sites are more sensible for change and would thus suit better out of a grid upgrade perspective. Cimislia is already limited by the capacities of the lines connected to the bus; upgrades to increase generation in Cimislia would be dependent on constructing new transmission lines. Ciadyr, Zarnesti and Besarabeasca are the weakest points in the grid according to voltage limits where Ciadyr would not benefit much from grid upgrades in form of voltage compensators being very close to its maximum value. Ciadyr and Zarnesti are far from maximum generation and would thus benefit most from reactive power compensation.

The results from looking at where violations are given by increasing each generators generation with one MW shows that Zarnesti Besarabeasca and Ciadyr are the weakest point according to high voltage violations where upgrades are likely to give a high value of further generation possibilities.

Looking at the histograms in Figure 3.1 and Figure 3.2 we can quite clearly see that the general voltage levels are increased and several busses in Scenario II are very close to the maximum value. This shows that if reactive power compensation would be used, it would support the system by consuming reactive power and thus decreasing the voltage levels. This is proven to be a correct assumption when generators can vary in reactive power because maximum generation is increased from 260 MW to 355 MW. This is good for wind power installations because wind generators usually consume reactive power and in this case some of the reactive power can be fed from the grid. In this case where generators can produce or consume reactive power Tarecklia is clearly the limiting factor for further installation of wind power. This due to low voltage levels, but line capacities are likely to become a big problem if generation were to be increased further, meaning that the whole 110 kV system would be in need of upgrades to increase line capacity’s. Looking at the histogram in Figure 3.3 most voltage levels lay close to 1 p.u. i.e. the system is relatively stable, but some voltage levels are very low. The problem with low voltage levels lie at the Tarecklia bus and even though reactive power compensation would not increase possible wind power installations by much it would increase the stability of the system.

Alternatively constructing new lines connecting the wind plants directly to the 330 kV system that is likely to have a higher capacity for new generation, this would of course bring forth new questions of economic aspects in constructing long new lines.

4.1.3 Economy Moldova’s has a difficult economic situation, being one of the poorest countries in Europe with inflation rates that are very high. We believe that the most likely scenario is that big wind power plants would not be constructed without investors from other countries; here the CDM projects could play a major roll.

The economical calculations made in this project can only be seen as vague approximation without secure data. We can see in the economical results that the payback time for investments vary by much, strongly influenced by the capability factor and discount rates. The curves in the economic analysis are only accurate until the brake-even point.

With Moldova’s economic situation the inflation is high; this tends to increase the discount rates if a loan for the investment is taken within the country.

Generally concerning wind power a capability factor as low as 10 % is not realistic and payback times for the investment will become extremely long if even possible making investments unrealistic; with such a low capability factor a new location should be found examined. For wind turbine investments the payback time should not exceed 20 years which is the general life expectancy of a wind turbine, it should rather be some years below 20 to make the investment profitable. Setting the limit to 15 years all scenarios are possible with capability factor of 0,3 but with the capability factor of 0,1 only one scenario would be possible i.e. with high electricity price and low discount rates at 6 %. Predictions of a future electricity price tend to lean towards higher electricity prices rather than lower prices thus making investment of wind power plants more profitable.

Incentives for renewable energy projects such as CDM are helpful for wind power investments but in our scenarios it does not have as strong influence as the capability factor, discount rates and the electricity price.

Chapter 5 Conclusion The conclusions drawn by this report are based on the model constructed in the report where wind power installations are made in the southern region of Moldova where wind conditions are satisfying.

The Moldovan electrical system in the southern region is constructed with high amounts of unused transmission line capacity, giving the southern region in Moldova a high potential for wind power installations.

With wind power installations at only one location the report conclude that Cimislia has the highest potential for wind power installations with 102 MW. This would reduce the electrical energy imports by 8 %.

With wind power installations at all sites generation can reach 260 MW of installed power if the wind power plant does not produce or consume reactive power. If the plants are able to consume reactive power a further 95 MW can be installed.

The electrical energy imports can be highly reduced by wind power installation at busses; Besarabeasca, Zarnesti, Leovo, Ciadyr, Cimislia at the same time. Total potential electrical energy can be reduced by as much 8 % to 25 % depending on the capability factor of the wind power plants.

The economic results suggest that payback periods for wind power installations in Moldova stretches from 3 years to never reaching the breakeven point. Further studies are necessary.

Chapter 6 Future Work

 The Model should be extended to regard a low flow scenario as well as contingency analysis where generators, loads and transformers are tripped.  Wind potential, wind data should be sampled over the period, at specified locations, of at least one year at planned hub height of the wind.  Further investigations of suggested wind power plant locations from environmental aspects as well as NiMBY (Not in My Back Yard) aspects.  More specific aspects for the needed investments; such as site-specific costs, inflation, electricity price, CER:s and future renewable energy incentives.  Aspects regarding balancing the wind power output within Moldova should be considered  The project does not consider power quality and the project should be extended to include such considerations.

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Appendix A Map of the Moldovan electrical system

Figure A-1 Map over the Moldovan electrical system [31]

A-1

Appendix B Map over the wind potential in Moldova

Figure B-1 Wind Potential in Moldova at the height of 70 meters [14]

B-1

Appendix C Description of WAsP

WAsP is a computer program used for predicting wind climates, wind resources and power productions from wind turbines and wind power parks. The predictions are based on wind data from meteorological stations. WAsP uses bi-dimensional extrapolation of the wind measured parameters and also accounts for the obstacles in the neighbourhood of the data collecting point, in this case a meteorological station. WAsP is developed by the Wind Energy Division at the technical university of Denmark at Risö. The program WAsP contains four basic computing modules. [32]

 Analysis of ”raw” measured data  Elaborating wind atlas  Wind climatological estimation  Estimation of wind potential

Analysis of raw measured data can be used as a separate tool and with it is possible to investigate the statics of the collected wind data. For example the module can provide a wind rose diagram and the Weibull distribution curve from data for a specific meteorological station or from data for several meteorological stations.

The elaborating wind atlas modulus creates a wind atlas. From the data given by the meteorological stations the WAsP program can calculate the new values, for the analysis, desired parameters and thereby create a data set. This can be done for the desired height. This data set represents the wind atlas from which an analysis of the wind conditions in the area can be made.

The wind climatological estimation modulus can estimate the wind value in any far-off emplacement, thus underlining possible emplacements. In other words the modulus permits the estimation of the real wind parameters on the interesting emplacement for a wind turbine or a wind power park.

The estimation of wind potential modulus calculates the wind energy potential from the annual average wind speed at the right height and also the annual energy production for a wind turbine or a wind power park. This modulus also can estimate the annual energy production for different types of wind turbines.

C-1

Appendix D Line diagram and data over the equivalent 330 kV circuit

Load

Generator

Figure D-1 Line diagram from PSS/E for the equivalent circuit over the Moldovan electrical system

D-1

Table D-1 Bus data for equivalent circuit over the Moldovan electrical system

Bus Number Bus Name Base kV Area Number/Name Code Voltage (kV) Angle (deg) 1 UDSGEC81 330 2 UKRAINA 2 350,10 -4,27 2 BALTSI 330 1 MOLDOVA 1 331,46 -8,74 3 STRASENI 330 1 MOLDOVA 1 319,50 -11,15 4 KISHINAU 330 1 MOLDOVA 1 318,18 -11,01 5 UKOTOVSK 330 2 UKRAINA 1 336,92 -7,34 6 MGRAS 330 1 MOLDOVA 2 323,14 -8,98 7 ULDTEC81 330 2 UKRAINA 3 363,00 0,00

Table D-2 Plant data for equivalent circuit over the Moldovan electrical system

Bus Number Bus Name Code PGen QGen QMax QMin VSched (kV) Voltage (kV) 1 UDSGEC81 330,00 2 97,60 103,70 103,70 103,70 363,00 350,10 6 MGRAS 330,00 2 147,80 -5,20 -5,20 -5,20 330,00 323,14 7 ULDTEC81 330,00 3 622,30 293,70 9999,00 -9999,00 363,00 363,00

Table D-3 Machine data for equivalent circuit over the Moldovan electrical system

Pmax Pmin Qgen Qmax Qmin Mbase Bus Number Bus Name Code VSched (pu) Pgen (MW) (MW) (MW) (Mvar) (Mvar) (Mvar) (MVA) 1 UDSGEC81 330,00 2 363,0 97,6 0,0 0,0 103,7 103,7 103,7 100 6 MGRAS 330,00 2 330,0 147,8 0,0 0,0 -5,2 -5,2 -5,2 100 7 ULDTEC81 330,00 3 363,0 622,3 9999,0 -9999,0 293,7 9999,0 -9999,0 100

Table D-4 Load data for equivalent circuit over the Moldovan electrical system

Bus Number Bus Name Area Number/Name Pload (MW) Qload (Mvar) 2 BALTSI 330,00 1 MOLDOVA 115,0 31,9 3 STRASENI 330,00 1 MOLDOVA 151,1 51,4 4 KISHINAU 330,00 1 MOLDOVA 209,4 94,4 5 UKOTOVSK 330,00 2 UKRAINA 374,7 76,3

Table D-5 Branch data for equivalent circuit over the Moldovan electrical system

From Bus Number From Bus Name To Bus Number To Bus Name Line R (ohms) Line X (ohms) 1 UDSGEC81 330,00 2 BALTSI 330,00 4,5411 37,6903 1 UDSGEC81 330,00 7 ULDTEC81 330,00 7,6775 61,4087 2 BALTSI 330,00 3 STRASENI 330,00 5,5539 35,6974 3 STRASENI 330,00 4 KISHINAU 330,00 2,2107 14,2332 4 KISHINAU 330,00 6 MGRAS 330,00 2,0038 16,9666 5 UKOTOVSK 330,00 6 MGRAS 330,00 8,0042 49,2990 5 UKOTOVSK 330,00 7 ULDTEC81 330,00 4,4976 36,1984

D-2

Appendix E Transmission Line Data

Table E-1 Data over transmission line types

AS Conductor nr: r0(Ohm\100km) x0(Ohm\100km) r0(Ohm\km) x0(Ohm\km) 35 77,23 0 0,77 0 50 59,20 0 0,59 0 70 42,00 41,00 0,42 0,41 95 31,40 42,90 0,31 0,43 120 24,90 42,30 0,25 0,42 150 19,50 41,60 0,12 0,42 185 15,60 40,90 0,16 0,41 240 12,00 40,10 0,12 0,40

Table E-2 Impedance values for the lines in the 110 kV system

Line ID kV R (1 phase) X (1phase) R (3 phase) X (3 phase) 1 110 17,5578 40,8323 52,6734 122,4969 2 110 6,4896 17,0144 19,4688 51,0432 3 110 5,382 11,4816 16,146 34,4448 4 110 7,9929 13,5783 23,9787 40,7349 5 110 5,772 15,133 17,316 45,399 6 110 19,0734 32,4018 57,2202 97,2054 7 110 8,8395 15,0165 26,5185 45,0495 8 110 13,3575 28,496 40,0725 85,488 9 110 10,9746 23,8011 32,9238 71,4033 10 110 18,55125 35,94048 55,65375 107,82144 111 110 9,048 19,3024 27,144 57,9072 12 110 13,104 27,9552 39,312 83,8656 13 110 6,006 12,8128 18,018 38,4384 14 110 17,28405 32,65825 51,85215 97,97475 15 400 0 0 3,5 46,99

Table E-3 Base impedance values

ZBase 110 kV ZBase 330 kV ZBase 400 kV 121 1089 1600

Table E-4 Per Unit values for the lines in the 110 kV system

Line ID R (3 phase) p.u X (3 phase) p.u 1 0,435317355 1,012371074 2 0,160899174 0,421844628 3 0,133438017 0,284667769 4 0,198171074 0,336652066 5 0,143107438 0,375198347 6 0,472894215 0,803350413 7 0,219161157 0,372309917 8 0,331177686 0,706512397 9 0,272097521 0,590109917 10 0,459948347 0,891086281 11 0,224330579 0,478571901 12 0,324892562 0,693104132 13 0,148909091 0,317672727 14 0,428530165 0,809708678 15 0,0021875 0,02936875

1 Line 11 is out of use 2 1 stands for load bus, 2 for generator bus and 3 is the swing bus E-1

Appendix F Line diagram and data over the complete model

Load

Generator

Three winding transformer

Switched shunt

400 kV Line

330 kV Line 110 kV Line

Active Power Flow

Reactive Power Flow

Line Offline

Figure F-1 Line diagram for the equivalent circuit over the Moldovan electrical system

F-1

Table F-1 Bus Data

Bus Number Bus Name Base kV Area Number/Name Code 2 Voltage (pu) Angle (deg) 1 35 1 MOLDOVA 1 0,9990 -1,51 30100 MGRAS 330 1 MOLDOVA 3 1,0455 0 30120 MGRAS 400 1 MOLDOVA 1 1,0390 -1,2 30195 MGRAS 35 1 MOLDOVA 1 1,0423 -0,57 32049 BALTSI 330 1 MOLDOVA 2 1,0079 -0,34 34057 CHISINAU 110 1 MOLDOVA 2 1,0115 1,64 34060 HANCESTI 110 1 MOLDOVA 1 0,9990 -1,5 34061 CHISINAU 330 1 MOLDOVA 1 1,0045 -1,55 34062 STRASENI 330 1 MOLDOVA 1 1,0004 -1,6 34112 CHISINAU 35 1 MOLDOVA 1 1,0107 1,64 36005 BESARABEASCA 110 1 MOLDOVA 2 0,9831 -3,81 36012 ZARNESTI 110 1 MOLDOVA 1 0,9911 -6,89 36023 COMRAT 110 1 MOLDOVA 1 0,9809 -4,94 36025 LEOVO 110 1 MOLDOVA 1 0,9785 -4,29 36028 TARECKLIA 110 1 MOLDOVA 1 1,0065 -5,34 36031 CIADYR 110 1 MOLDOVA 2 0,9808 -6,42 36032 CIMISLIA 110 1 MOLDOVA 2 0,9910 -2,05 36038 VULCANESTI 110 1 MOLDOVA 1 1,0180 -5,36 36046 VULCANESTI 400 1 MOLDOVA 1 1,0294 -2,8 36110 VULCANESTI 35 1 MOLDOVA 1 1,0184 -5,36 70530 UKOTOVSK 330 2 UKRAINE 1 0,9966 -3,79 70544 UBOLGR 110 2 UKRAINE 1 1,0180 -5,36 70805 UDSGEC81 330 2 UKRAINE 2 1,0455 3,39 70822 ULDTEC81 330 2 UKRAINE 2 1,0455 -0,11

Table F-2 Branch Data

From Bus To Bus In Rate A (I as Number From Bus Name Number To Bus Name Id Line R (pu) Line X (pu) Charging (pu) Service3 MVA) 30100 MGRAS 330,00 34061 CHISINAU 330,00 1 0,0018 0,0156 0,000 1 0 30100 MGRAS 330,00 70530 UKOTOVSK 330,00 1 0,0074 0,0453 0,000 1 0 30120 MGRAS 400,00 36046 VULCANESTI 400,00 15 0,0022 0,0294 0,011 1 1964 32049 BALTSI 330,00 34062 STRASENI 330,00 1 0,0051 0,0328 0,000 1 0 32049 BALTSI 330,00 70805 UDSGEC81 330,00 1 0,0042 0,0346 0,000 1 0 34057 CHISINAU 110,00 34060 HANCESTI 110,00 3 0,1334 0,2847 0,000 1 84,8 34057 CHISINAU 110,00 36005 BESARABEASCA110,00 1 0,4353 1,0124 0,000 1 84,8 34057 CHISINAU 110,00 36032 CIMISLIA 110,00 2 0,1609 0,4218 0,000 1 97,2 34060 HANCESTI 110,00 36025 LEOVO 110,00 6 0,4729 0,8034 0,000 1 72,4 34061 CHISINAU 330,00 34062 STRASENI 330,00 1 0,0020 0,0131 0,000 1 0 36005 BESARABEASCA110,00 36023 COMRAT 110,00 4 0,1982 0,3367 0,000 1 72,4 36012 ZARNESTI 110,00 36023 COMRAT 110,00 10 0,4599 0,8911 0,000 1 72,4 36012 ZARNESTI 110,00 36038 VULCANESTI 110,00 14 0,4285 0,8097 0,000 1 72,4 36023 COMRAT 110,00 36025 LEOVO 110,00 7 0,2192 0,3723 0,000 1 72,4 36023 COMRAT 110,00 36028 TARECKLIA 110,00 9 0,2721 0,5901 0,000 1 85,8 36023 COMRAT 110,00 36031 CIADYR 110,00 8 0,3312 0,7065 0,000 1 84,8 36023 COMRAT 110,00 36032 CIMISLIA 110,00 5 0,1431 0,3752 0,000 1 97,2 36028 TARECKLIA 110,00 36031 CIADYR 110,00 11 0,2243 0,4786 0,000 0 84,8 36028 TARECKLIA 110,00 36038 VULCANESTI 110,00 13 0,1489 0,3177 0,000 1 84,8 36031 CIADYR 110,00 36038 VULCANESTI 110,00 12 0,3249 0,6896 0,000 1 84,8 36038 VULCANESTI 110,00 70544 UBOLGR 110,00 1 0,0000 0,0001 0,000 1 0 70530 UKOTOVSK 330,00 70822 ULDTEC81 330,00 1 0,0041 0,0332 0,000 1 0 70805 UDSGEC81 330,00 70822 ULDTEC81 330,00 1 0,0071 0,0564 0,000 1 0

2 1 stands for load bus, 2 for generator bus and 3 is the swing bus 3 1 states in service and 0 out of service F-2

Table F-3 Machine Data

Pmax Pmin Qmax Qmin Mbase Bus Number Bus Name Id Code VSched (pu) Pgen (MW) (MW) (MW) Qgen (Mvar) (Mvar) (Mvar) (MVA) 30100 MGRAS 330,00 1 3 1,0455 703,054 2520 0 442,6036 2000 50 100 32049 BALTSI 330,00 1 2 1 34 40 0 5 50 5 100 34057 CHISINAU 110,00 1 2 1 234 240 0 20 180 20 100 36005 BESARABEASCA110,00 1 2 1 0 9999 -9999 0 0 0 100 36012 ZARNESTI 110,00 1 1 1 0 9999 -9999 0 0 0 100 36025 LEOVO 110,00 1 1 1 0 9999 -9999 0 0 0 100 36031 CIADYR 110,00 1 2 1 0 9999 -9999 0 0 0 100 36032 CIMISLIA 110,00 1 2 1 0 9999 -9999 0 0 0 100 70805 UDSGEC81 330,00 1 2 1,0455 326 0 0 83,6194 200 -200 100 70822 ULDTEC81 330,00 1 2 1,0455 102 9999 -9999 151,1422 9999 -9999 100

Table F-4 Plant Data

Bus Number Bus Name Code PGen QGen QMax QMin VSched (pu) Voltage (pu) RMPCT 30100 MGRAS 330,00 3 703,1 442,6 2000 50 1,0455 1,0455 100 32049 BALTSI 330,00 2 34 5 50 5 1 1,0079 100 34057 CHISINAU 110,00 2 234 20 180 20 1 1,0115 100 36005 BESARABEASCA110,00 2 0 0 0 0 1 0,9831 100 36012 ZARNESTI 110,00 1 0 0 0 0 1 0,9911 100 36025 LEOVO 110,00 1 0 0 0 0 1 0,9785 100 36031 CIADYR 110,00 2 0 0 0 0 1 0,9808 100 36032 CIMISLIA 110,00 2 0 0 0 0 1 0,991 100 70805 UDSGEC81 330,00 2 326 83,6 200 -200 1,0455 1,0455 100 70822 ULDTEC81 330,00 2 102 151,1 9999 -9999 1,0455 1,0455 100

Table F-5 Load Data

Bus Number Bus Name Id Area Number/Name Pload (MW) Qload (Mvar) 30100 MGRAS 330,00 1 1 MOLDOVA 220 70 32049 BALTSI 330,00 1 1 MOLDOVA 171 70 34060 HANCESTI 110,00 1 1 MOLDOVA 6 0,6 34061 CHISINAU 330,00 1 1 MOLDOVA 391 220 34062 STRASENI 330,00 1 1 MOLDOVA 87 36 36005 BESARABEASCA110,00 1 1 MOLDOVA 4,2 0,5 36012 ZARNESTI 110,00 1 1 MOLDOVA 6,4 -1,3 36023 COMRAT 110,00 1 1 MOLDOVA 13,8 1,5 36025 LEOVO 110,00 1 1 MOLDOVA 3,5 0,9 36028 TARECKLIA 110,00 1 1 MOLDOVA 0,6 -1 36031 CIADYR 110,00 1 1 MOLDOVA 7,1 1,9 36032 CIMISLIA 110,00 1 1 MOLDOVA 2,4 0,4 36038 VULCANESTI 110,00 1 1 MOLDOVA 29,2 -12,4 70530 UKOTOVSK 330,00 1 2 UKRAINE 380 189 70544 UBOLGR 110,00 1 1 UKRAINE 64 24,2

Table F-6 Switched Shunt Data

Blk 1 Bus In Adjustment Contribute Blk 1 Bstep Number Bus Name Service Control Mode Method Vhi (pu) Vlo (pu) d Vars (%) VSC Name Steps (Mvar) MGRAS Discrete, cntr Sequential input 30195 35,000 0 voltage (1) order (0) 1,1 0,95 100 None 6 -30 VULCANESTI Discrete, cntr Sequential input 36046 400,00 0 voltage (1) order (0) 1,1 0,95 100 None 3 -55

Table F-7 Three Winding Data

From Bus To Bus Last Bus Magnetizin Numbe From Bus Numbe To Bus Numbe Last Bus W1-2 W1-2 W2-3 W2-3 W3-1 W3-1 g G (pu or Magnetizin r Name r Name r Name R (pu) X (pu) R (pu) X (pu) R (pu) X (pu) watts) g B (pu)

F-3

MGRAS MGRAS MGRAS 0,000 0,022 0,000 0,039 0,000 0,040 30120 400,00 30100 330,00 30195 35,000 4 2 1 4 1 3 0,0003 -0,0030 VULCANEST VULCANEST VULCANEST 0,000 0,036 0,001 0,082 0,001 0,045 36038 I 110,00 36110 I 35,000 36046 I 400,00 8 9 3 5 3 7 0,0010 -0,0050 HANCESTI STRASENI 0,000 0,029 0,001 0,093 0,001 0,064 34060 110,00 34062 330,00 1 35 8 7 5 9 5 3 0,0010 -0,0050 CHISINAU CHISINAU CHISINAU 0,000 0,029 0,001 0,093 0,001 0,064 34057 110,00 34061 330,00 34112 35,000 8 7 5 9 5 3 0,0010 -0,0050

Table F-8 Winding Data, MGRAS

Bus Rate A Control Auto Rmax (ratio Rmin (ratio Vmax (pu, kV Vmin (pu, kV Tap Number Bus Name Winding (MVA) Mode Adjust or angle) or angle) MW, or Mvar) MW, or Mvar) Positions 30120 MGRAS 400,00 1 420 Voltage 1 1,1 0,9 1,05 0,95 15 30100 MGRAS 330,00 2 420 Voltage 1 1,1 0,9 1,05 0,95 15 30195 MGRAS 35,000 3 420 Voltage 1 1,1 0,9 1,05 0,95 15

Table F-9 Winding Data, Vulcanesti

Bus Rate A Control Auto Rmax (ratio Rmin (ratio Vmax (pu, kV Vmin (pu, kV Tap Number Bus Name Winding (MVA) Mode Adjust or angle) or angle) MW, or Mvar) MW, or Mvar) Positions 36038 VULCANESTI 110,00 1 500 Voltage 1 1,1 0,9 1,05 0,95 15 36110 VULCANESTI 35,000 2 500 Voltage 1 1,1 0,9 1,05 0,95 15 36046 VULCANESTI 400,00 3 500 Voltage 1 1,1 0,9 1,05 0,95 15

Table F-10 Winding Data, Hancesti-Straseni

Bus Rate A Control Auto Rmax (ratio Rmin (ratio Vmax (pu, kV Vmin (pu, kV Tap Number Bus Name Winding (MVA) Mode Adjust or angle) or angle) MW, or Mvar) MW, or Mvar) Positions 34060 HANCESTI 110,00 1 400 Voltage 1 1,1 0,9 1,05 0,95 15 34062 STRASENI 330,00 2 400 Voltage 1 1,1 0,9 1,05 0,95 15 1 35 3 400 Voltage 1 1,1 0,9 1,05 0,95 15

Table F-11 Winding Data, Chisinau

Bus Rate A Control Auto Rmax (ratio Rmin (ratio Vmax (pu, kV Vmin (pu, kV Tap Number Bus Name Winding (MVA) Mode Adjust or angle) or angle) MW, or Mvar) MW, or Mvar) Positions 34057 CHISINAU 110,00 1 400 Voltage 1 1,1 0,9 1,05 0,95 15 34061 CHISINAU 330,00 2 400 Voltage 1 1,1 0,9 1,05 0,95 15 34112 CHISINAU 35,000 3 400 Voltage 1 1,1 0,9 1,05 0,95 15

F-4

Appendix G General Python Script – executing the contingency analysis

#mainScript takes five inputs; each representing a generator output in MW. mainScript also returns a value #stating if violations have occurred def mainScript(genA, genB, genC, genD, genE):

#Generator names and power outputs windBusA = 36005 windBusB = 36012 windBusC = 36025 windBusD = 36031 windBusE = 36032 runNum=('#',genA,' & ', genB, ' [MW] at Wind Generators ', windBusA, windBusB) outNum = str(runNum) #outNum is the output text defineing the increase

#Changing the wind generator output (MW) id = "1" #Machine identifier intgar = [] #Owner number, array of 4 elements i.e. 4 different #owner (no input) realarA = genA #Array of 16 elements where the first element is the #machine active power output realarB = genB realarC = genC realarD = genD realarE = genE ierr = psspy.machine_data(windBusA,id,intgar,realarA) ierr = psspy.machine_data(windBusB,id,intgar,realarB) ierr = psspy.machine_data(windBusC,id,intgar,realarC) ierr = psspy.machine_data(windBusD,id,intgar,realarD) ierr = psspy.machine_data(windBusE,id,intgar,realarE)

#Creating a file to store the ac-reports islct = 2 #Virtual devic selector; 1-standard destination, 2,3,4,5- #output to file, printer, progress device, report device, 6- #no output filarg = "reportTemp.txt" #Report file name (output) options = [] options.append(0) #1: 0-open with carriage control format and overwrite #existing files, 1-open with list format, 2-open file for #append options.append(0) #2: 0-printer option only, number of copies ierr = psspy.report_output(islct, filarg, options) if ierr>0: f = open('testIerr.txt','a') out = 'Error with creating the the temporary report file with generator levels: ',genA, genB, genC, genD, genE, ' error num: ', ierr f.write(str(out)) f.write('\n') f.close() a=2 return a

#Solution for the new base case options = [] options.append(1) #1: Tap adjustment; 0-disabled, 1-enable, 2-direct adjustment options.append(0) #2: Area interchange adjustment; 0-disabled, 1-enabled using tie line flows, 2- enabled using tie line flows and loads options.append(0) #3: Phase shift adjustment; 0-disabled, 1-enable options.append(1) #4: Dc tap adjustment; 0-disabled, 1-enable options.append(0) #5: Switched shunt adjustment; 0-disabled, 1-enable options.append(1) #6: Flat start; 0-no flat start, 1-flat start

G-1 options.append(0) #7: Var limit; 0-apply var limits immediatly, >0-apply var limits on iteration n, -1-ignor var limits options.append(0) #8: Non-divergent solution; 0-disable, 1-enable ierr = psspy.fnsl(options) if ierr>0: f = open('testIerr.txt','a') out = 'Error with solving the new base case at generator levels: ',genA, genB, genC, genD, genE, ' error num: ', ierr f.write(str(out)) f.write('\n') f.close() a=2 return a

#Creates a .dfx output file based on existing .sub, .mon and .con files ierr = psspy.dfax(1, 'Sub', 'Mon', 'Cont', 'Dfx') if ierr>0: f = open('testIerr.txt','a') out = 'Error with creating the .dfx file at generator levels: ',genA, genB, genC, genD, genE, ' error num: ', ierr f.write(str(out)) f.write('\n') f.close() a=2 return a

#Executes a accc Contingency analys with the output file Accc.acc tol = None # Mismatch tolerance TOLN by default options = [] # Seven array element for specifying solution options options.append(0) #1: Tap adjustment; 0-disable, 1-enable, 2-direct adjustment options.append(0) #2: Area interchange adjustment; 0-disabled, 1-enabled using tie line flows, 2- enabled using tie line flows and loads options.append(0) #3: Phase shift adjustment; 0-disabled, 1-enable options.append(0) #4: Dc tap adjustment; 0-disabled, 1-enable options.append(0) #5: Switched shunt adjustment; 0-disabled, 1-enable, 2-enable continuous mode, disable discrete mode options.append(1) #6: Solution method; 0-FDNS, 1-FNSL, 2-optimized FDNS options.append(1) #7: Non-divergent solution; 0-disable, 1-enable dfxfile = 'Dfx' # Imports .dfx file accfile = 'Accc' # Output file ierr = psspy.accc(tol,options,dfxfile,accfile) if ierr>0: f = open('testIerr.txt','a') out = 'Error with the contingency solution at generator levels: ',genA, genB, genC, genD, genE, ' error num: ', ierr f.write(str(out)) f.write('\n') f.close() a=2 return a

#Executes the ac-report based on the contingency and stores it in the report file STATUS=[] STATUS.append(0) #1: Report form; 0-spreadsheet overload report, 1-spreadsheet loading table, 2-avaiable capacity table, 4,5 #and 6-non-spreadsheet reports STATUS.append(1) #2: Base case rating; 1-rate A, 2-rate B, 3-rate C STATUS.append(1) #3: Contingency case rating; 1-rate A, 2-rate B, 3-rate C STATUS.append(0) #4: Exclude interfaces from report; 0-no, 1-yes STATUS.append(1) #5: Run voltage limit check; 0-no, 1-yes STATUS.append(0) #6: Only if #1 = 0 or 3; 0-no, 1-yes STATUS.append(0) #7: Only if #1 = 0 or 3; 0-no, 1-yes STATUS.append(0) #8: Exclude cases with no overloads from non-spreadsheet reports; only if #1 = 3,4,5 or 6; 0-no, 1-yes STATUS.append(0) #9: Report post-tripping action solutions; 0-no, 1-yes interval=[] # Filtering criterias interval.append(0) #1: Number of low voltage range violations interval.append(0) #2: Number of high voltage range violations interval.append(0) #3: Number of voltage deviation violations interval.append(0) #4: Number of buses in the largest disconnected island

G-2 realval=[] realval.append(0.5) #1: Bus mismatch converged tolerance (MW or MVA) realval.append(0.5) #2: Ssystem mismatch converged tolerandce (MVA) realval.append(100) #3: % of flow rating, use only when STATUS#1 is 0,3 or 4 realval.append(0) #4: Minimum contingency case flow change realval.append(0) #5: Minimum contingency case percent loading increas realval.append(0) #6: Minimum contingency case voltage change acccOutFile='Accc.acc' ierr = psspy.accc_single_run_report_2(STATUS,interval, realval,acccOutFile) if ierr>0: f = open('testIerr.txt','a') out = 'Error with writing the report file for contingency solution at generator levels: ',genA, genB, genC, genD, genE, ' error num: ', ierr f.write(str(out)) f.write('\n') f.close() a=2 return a

#Checking violations and returning true or false f = open('reportTemp.txt','r') data_list = f.readlines() a = len(data_list[27]) b = len(data_list[30]) f.close() if a==1 and b==1: return a else: a=2 return a

G-3

Appendix H Python Script – Scenario I

#oneByOne increases one specific generator's output and #stores values not generating violation in a report file def oneByOne(): file = open('Run1GenA.txt','w') #Change file name to get separate reports for different generators genA = 0 genB = 0 genC = 0 genD = 0 genE = 0 generators = [genA, genB, genC, genD, genE] for i in range (0,103,1): violation = mainScript(genA, genB, genC, genD, genE) if violation == 1: genA = i #Change to other generators to check their maximum value else: break violation = mainScript(genA, genB, genC, genD, genE) file.write('Violation with generators set at: \n\n') out = 'genA = ',genA,' genB = ',genB,' genC = ',genC,' genD = ',genD,' genE = ',genE file.write(str(out)) file.write('\n') fTemp = open('reportTemp.txt','r') flag = False fTemp.close() fTemp = open('reportTemp.txt','r') for line in fTemp: if "MULTI-SECTION LINE" in line: file.write('\n') file.write(line) flag = True elif flag: file.write(line.strip()) file.write('\n') if "CONTINGENCY LEGEND" in line: flag = False fTemp.close() file.close()

H-1

Appendix I Python Script – Scenario II, Monte Carlo Simulation def allTogether(): #f = open('Run1Random.txt','w') #f2 = open('Run1Max.txt','w') #fA = open('Run1MaxGenA.txt','w') #fB = open('Run1MaxGenB.txt','w') #fC = open('Run1MaxGenC.txt','w') #fD = open('Run1MaxGenD.txt','w') #fE = open('Run1MaxGenE.txt','w') n = open('testall.txt','w') n1 = open('testallA.txt','w') n2 = open('testallB.txt','w') n3 = open('testallC.txt','w') n4 = open('testallD.txt','w') n5 = open('testallE.txt','w') maxGen=0 for i in range (1,1000): count = open('testRaknare.txt','w') #counter to folow the iterations count.write(str(i)) count.write('\n') count.close genA = 28+random.randrange(0,5) #The random generator, genB = 10+random.randrange(0,5) #values needs to be changed genC = 28+random.randrange(0,5) #to use different intervals. genD = 83+random.randrange(0,5) genE = 98+random.randrange(0,5)

violation = mainScript(genA, genB, genC, genD, genE) if violation == 1: #if=1 there is no violation maxGen = genA+genB+genC+genD+genE out = 'genA = ',genA,' genB = ',genB,' genC = ',genC,' genD = ',genD,' genE = ',genE n.write(str(maxGen)) n.write('\n') n1.write(str(genA)) n1.write('\n') n2.write(str(genB)) n2.write('\n') n3.write(str(genC)) n3.write('\n') n4.write(str(genD)) n4.write('\n') n5.write(str(genE)) n5.write('\n')

I-1

Appendix J Base Case - Contingency Loading Report

ACCC LOADING REPORT: MONITORED BRANCHES AND INTERFACES USING RATING SET A % LOADING VALUES ARE % MVA FOR TRANSFORMERS AND % CURRENT FOR NON-TRANSFORMER BRANCHES INCLUDES VOLTAGE REPORT

AC CONTINGENCY RESULTS FILE: C:\Users\Joel\Desktop\Testfiler\CONTINGENCYBACECASE.acc DISTRIBUTION FACTOR FILE: C:\Users\Joel\Desktop\Testfiler\Dfx.dfx SUBSYSTEM DESCRIPTION FILE: C:\Users\Joel\Desktop\Testfiler\Sub.sub MONITORED ELEMENT FILE: C:\Users\Joel\Desktop\Testfiler\Mon.mon CONTINGENCY DESCRIPTION FILE: C:\Users\Joel\Desktop\Testfiler\Cont.con

**PERCENT LOADING UNITS** %MVA FOR TRANSFORMERS % I FOR NON-TRANSFORMER BRANCHES

**OPTIONS USED IN CONTINGENCY ANALYSIS** Solution engine: Full Newton-Raphson (FNSL) Solution options Tap adjustment: Stepping Area interchange control: Disable Phase shift adjustment: Disable Dc tap adjustment: Enable Switch shunt adjustment: Enable all Non diverge: Disable Mismatch tolerance (MW ): 0.5 Dispatch mode: Disable

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW % 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 BASE CASE 84.8 18.2 21.1 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 BASE CASE 84.8 9.1 10.5 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 BASE CASE 97.2 15.1 15.4 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 BASE CASE 72.4 5.9 8.1 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 BASE CASE 72.4 4.9 6.9 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 BASE CASE 72.4 3.5 4.8 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 BASE CASE 72.4 4.1 5.6 36023 COMRAT 110.00 36025*LEOVO 110.00 7 BASE CASE 72.4 2.5 3.5 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 BASE CASE 85.8 3.9 4.5 36023*COMRAT 110.00 36031 CIADYR 110.00 8 BASE CASE 84.8 3.2 3.9 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 BASE CASE 97.2 12.5 12.9 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 BASE CASE 84.8 3.1 3.6 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 BASE CASE 84.8 5.4 6.3 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 1 84.8 0.0 0.0 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 1 84.8 9.3 10.8 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 1 97.2 15.5 15.8 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 1 72.4 5.6 7.6 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 1 72.4 5.2 7.2 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 1 72.4 3.5 4.9 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 1 72.4 4.1 5.6 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 1 72.4 2.0 2.8 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 1 85.8 4.0 4.6 36023*COMRAT 110.00 36031 CIADYR 110.00 8 SINGLE 1 84.8 3.3 3.9 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 1 97.2 12.9 13.4 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 1 84.8 3.2 3.7 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 1 84.8 5.4 6.3

J-1

34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 2 84.8 18.8 21.9 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 2 84.8 0.0 0.0 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 2 97.2 18.1 18.4 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 2 72.4 7.6 10.4 36005 BESARABEASCA110.00 36023*COMRAT 110.00 4 SINGLE 2 72.4 4.0 5.7 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 2 72.4 2.7 3.7 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 2 72.4 5.1 6.9 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 2 72.4 4.2 5.9 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 2 85.8 4.4 5.1 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 2 84.8 2.0 2.4 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 2 97.2 15.3 15.9 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 2 84.8 4.1 4.8 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 2 84.8 6.4 7.4 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 3 84.8 19.5 22.7 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 3 84.8 12.4 14.5 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 3 97.2 0.0 0.0 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 3 72.4 9.4 12.8 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 3 72.4 8.0 11.4 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 3 72.4 2.2 3.1 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 3 72.4 6.1 8.3 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 3 72.4 5.7 8.2 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 3 85.8 5.8 6.8 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 3 84.8 1.2 1.4 36023*COMRAT 110.00 36032 CIMISLIA 110.00 5 SINGLE 3 97.2 2.4 2.6 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 3 84.8 5.9 6.8 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 3 84.8 7.6 8.8 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 4 84.8 17.3 20.1 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 4 84.8 10.1 11.8 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 4 97.2 17.0 17.3 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 4 72.4 0.0 0.0 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 4 72.4 5.9 8.3 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 4 72.4 2.9 4.1 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 4 72.4 4.8 6.6 36023*COMRAT 110.00 36025 LEOVO 110.00 7 SINGLE 4 72.4 3.5 4.9 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 4 85.8 4.3 5.0 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 4 84.8 2.4 2.9 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 4 97.2 14.2 14.8 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 4 84.8 3.9 4.5 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 4 84.8 6.2 7.1 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 5 84.8 18.5 21.6 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 5 84.8 4.2 4.9 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 5 97.2 16.7 17.0 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 5 72.4 6.8 9.3

J-2

36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 5 72.4 0.0 0.0 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 5 72.4 2.9 4.1 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 5 72.4 4.6 6.2 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 5 72.4 3.5 4.9 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 5 85.8 3.8 4.4 36023*COMRAT 110.00 36031 CIADYR 110.00 8 SINGLE 5 84.8 2.5 3.0 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 5 97.2 14.1 14.6 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 5 84.8 3.3 3.9 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 5 84.8 5.8 6.7 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 6 84.8 18.2 21.2 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 6 84.8 8.6 10.1 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 6 97.2 14.4 14.6 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 6 72.4 5.5 7.6 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 6 72.4 4.4 6.2 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 6 72.4 0.0 0.0 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 6 72.4 6.7 9.0 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 6 72.4 2.0 2.8 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 6 85.8 4.5 5.2 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 6 84.8 3.8 4.5 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 6 97.2 11.7 12.2 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 6 84.8 3.6 4.1 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 6 84.8 5.4 6.2 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 7 84.8 18.1 21.1 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 7 84.8 9.6 11.2 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 7 97.2 16.1 16.3 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 7 72.4 6.6 9.0 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 7 72.4 5.3 7.5 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 7 72.4 6.5 9.2 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 7 72.4 0.0 0.0 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 7 72.4 3.1 4.3 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 7 85.8 4.5 5.3 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 7 84.8 2.6 3.2 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 7 97.2 13.3 13.9 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 7 84.8 4.0 4.6 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 7 84.8 6.2 7.1 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 8 84.8 17.8 20.7 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 8 84.8 9.5 11.1 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 8 97.2 15.9 16.1 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 8 72.4 3.7 5.0 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 8 72.4 5.4 7.5 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 8 72.4 3.2 4.4 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 8 72.4 4.4 5.9 36023*COMRAT 110.00 36025 LEOVO 110.00 7 SINGLE 8 72.4 0.0 0.0

J-3

36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 8 85.8 3.8 4.4 36023*COMRAT 110.00 36031 CIADYR 110.00 8 SINGLE 8 84.8 2.8 3.4 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 8 97.2 13.3 13.7 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 8 84.8 3.2 3.7 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 8 84.8 5.6 6.5 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 9 84.8 18.2 21.2 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 9 84.8 9.1 10.6 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 9 97.2 15.1 15.3 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 9 72.4 6.1 8.4 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 9 72.4 4.7 6.7 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 9 72.4 3.8 5.3 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 9 72.4 4.6 6.2 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 9 72.4 2.4 3.5 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 9 85.8 0.0 0.0 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 9 84.8 3.4 4.1 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 9 97.2 12.3 12.9 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 9 84.8 1.2 1.4 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 9 84.8 6.1 7.1 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 10 84.8 18.2 21.2 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 10 84.8 8.6 10.0 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 10 97.2 14.3 14.5 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 10 72.4 5.4 7.4 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 10 72.4 4.4 6.2 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 10 72.4 3.9 5.5 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 10 72.4 3.8 5.1 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 10 72.4 2.0 2.8 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 10 85.8 4.2 4.9 36023*COMRAT 110.00 36031 CIADYR 110.00 8 SINGLE 10 84.8 0.0 0.0 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 10 97.2 11.7 12.1 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 10 84.8 3.3 3.8 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 10 84.8 7.6 8.8 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 11 84.8 19.3 22.5 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 11 84.8 11.9 13.8 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 11 97.2 2.1 2.1 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 11 72.4 8.7 11.9 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 11 72.4 7.5 10.6 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 11 72.4 2.2 3.1 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 11 72.4 5.7 7.8 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 11 72.4 5.2 7.4 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 11 85.8 5.2 6.0 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 11 84.8 1.4 1.6 36023*COMRAT 110.00 36032 CIMISLIA 110.00 5 SINGLE 11 97.2 0.0 0.0 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 11 84.8 5.1 5.9

J-4

36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 11 84.8 7.1 8.2 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 12 84.8 18.2 21.2 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 12 84.8 9.2 10.7 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 12 97.2 15.3 15.6 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 12 72.4 6.2 8.5 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 12 72.4 4.9 6.9 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 12 72.4 3.6 5.0 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 12 72.4 4.6 6.2 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 12 72.4 2.6 3.6 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 12 85.8 1.2 1.4 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 12 84.8 3.2 3.8 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 12 97.2 12.6 13.1 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 12 84.8 0.0 0.0 36031 CIADYR 110.00 36038*VULCANESTI 110.00 12 SINGLE 12 84.8 6.0 7.0 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 13 84.8 18.1 21.1 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 13 84.8 9.6 11.2 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 13 97.2 16.1 16.3 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 13 72.4 6.7 9.2 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 13 72.4 5.2 7.4 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 13 72.4 3.3 4.6 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 13 72.4 5.0 6.8 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 13 72.4 3.0 4.3 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 13 85.8 5.2 6.0 36023*COMRAT 110.00 36031 CIADYR 110.00 8 SINGLE 13 84.8 7.4 8.9 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 13 97.2 13.3 13.8 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 13 84.8 4.6 5.4 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 13 84.8 0.0 0.0

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE BASE CASE 34057 CHISINAU 110.00 1.01261 1.01261 1.10000 0.90000 'SUB ' RANGE BASE CASE 34060 HANCESTI 110.00 1.01153 1.01153 1.10000 0.90000 'SUB ' RANGE BASE CASE 36005 BESARABEASCA110.00 0.98540 0.98540 1.10000 0.90000 'SUB ' RANGE BASE CASE 36012 ZARNESTI 110.00 0.99257 0.99257 1.10000 0.90000 'SUB ' RANGE BASE CASE 36023 COMRAT 110.00 0.98351 0.98351 1.10000 0.90000 'SUB ' RANGE BASE CASE 36025 LEOVO 110.00 0.98433 0.98433 1.10000 0.90000 'SUB ' RANGE BASE CASE 36028 TARECKLIA 110.00 1.00767 1.00767 1.10000 0.90000 'SUB ' RANGE BASE CASE 36031 CIADYR 110.00 0.98233 0.98233 1.10000 0.90000 'SUB ' RANGE BASE CASE 36032 CIMISLIA 110.00 0.99294 0.99294 1.10000 0.90000 'SUB ' RANGE BASE CASE 36038 VULCANESTI 110.00 1.01844 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 1 34057 CHISINAU 110.00 1.01040 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 1 34060 HANCESTI 110.00 1.01401 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36005 BESARABEASCA110.00 0.98447 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36012 ZARNESTI 110.00 0.99227 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36023 COMRAT 110.00 0.98303 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36025 LEOVO 110.00 0.98489 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36028 TARECKLIA 110.00 1.00742 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36031 CIADYR 110.00 0.98202 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36032 CIMISLIA 110.00 0.99152 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36038 VULCANESTI 110.00 1.01831 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 2 34057 CHISINAU 110.00 1.01241 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 2 34060 HANCESTI 110.00 1.01146 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36005 BESARABEASCA110.00 0.96797 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36012 ZARNESTI 110.00 0.98971 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36023 COMRAT 110.00 0.97764 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36025 LEOVO 110.00 0.97997 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36028 TARECKLIA 110.00 1.00561 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36031 CIADYR 110.00 0.97939 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36032 CIMISLIA 110.00 0.98902 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36038 VULCANESTI 110.00 1.01842 1.01844 1.10000 0.90000

J-5

'SUB ' RANGE SINGLE 3 34057 CHISINAU 110.00 1.01240 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 3 34060 HANCESTI 110.00 1.01128 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36005 BESARABEASCA110.00 0.97301 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36012 ZARNESTI 110.00 0.98392 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36023 COMRAT 110.00 0.96711 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36025 LEOVO 110.00 0.97217 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36028 TARECKLIA 110.00 1.00111 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36031 CIADYR 110.00 0.97340 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36032 CIMISLIA 110.00 0.96196 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36038 VULCANESTI 110.00 1.01739 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 4 34057 CHISINAU 110.00 1.01251 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 4 34060 HANCESTI 110.00 1.01185 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36005 BESARABEASCA110.00 0.98078 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36012 ZARNESTI 110.00 0.98935 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36023 COMRAT 110.00 0.97730 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36025 LEOVO 110.00 0.96630 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36028 TARECKLIA 110.00 1.00524 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36031 CIADYR 110.00 0.97901 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36032 CIMISLIA 110.00 0.98916 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36038 VULCANESTI 110.00 1.01804 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 5 34057 CHISINAU 110.00 1.01239 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 5 34060 HANCESTI 110.00 1.01154 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36005 BESARABEASCA110.00 0.98951 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36012 ZARNESTI 110.00 0.99281 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36023 COMRAT 110.00 0.98342 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36025 LEOVO 110.00 0.98410 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36028 TARECKLIA 110.00 1.00800 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36031 CIADYR 110.00 0.98258 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36032 CIMISLIA 110.00 0.99238 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36038 VULCANESTI 110.00 1.01900 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 6 34057 CHISINAU 110.00 1.01232 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 6 34060 HANCESTI 110.00 1.01129 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36005 BESARABEASCA110.00 0.98395 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36012 ZARNESTI 110.00 1.00146 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36023 COMRAT 110.00 0.98168 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36025 LEOVO 110.00 0.98308 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36028 TARECKLIA 110.00 1.00767 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36031 CIADYR 110.00 0.98191 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36032 CIMISLIA 110.00 0.99203 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36038 VULCANESTI 110.00 1.01943 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 7 34057 CHISINAU 110.00 1.01222 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 7 34060 HANCESTI 110.00 1.01127 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36005 BESARABEASCA110.00 0.98009 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36012 ZARNESTI 110.00 0.95722 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36023 COMRAT 110.00 0.97650 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36025 LEOVO 110.00 0.97933 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36028 TARECKLIA 110.00 1.00579 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36031 CIADYR 110.00 0.97927 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36032 CIMISLIA 110.00 0.98885 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36038 VULCANESTI 110.00 1.01933 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 8 34057 CHISINAU 110.00 1.01264 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 8 34060 HANCESTI 110.00 1.01130 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36005 BESARABEASCA110.00 0.98560 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36012 ZARNESTI 110.00 0.99286 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36023 COMRAT 110.00 0.98374 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36025 LEOVO 110.00 0.98722 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36028 TARECKLIA 110.00 1.00798 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36031 CIADYR 110.00 0.98263 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36032 CIMISLIA 110.00 0.99288 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36038 VULCANESTI 110.00 1.01879 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 9 34057 CHISINAU 110.00 1.01182 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 9 34060 HANCESTI 110.00 1.01094 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36005 BESARABEASCA110.00 0.97796 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36012 ZARNESTI 110.00 0.98920 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36023 COMRAT 110.00 0.97381 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36025 LEOVO 110.00 0.97749 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36028 TARECKLIA 110.00 1.02336 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36031 CIADYR 110.00 0.97872 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36032 CIMISLIA 110.00 0.98749 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36038 VULCANESTI 110.00 1.02092 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 10 34057 CHISINAU 110.00 1.01253 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 10 34060 HANCESTI 110.00 1.01144 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36005 BESARABEASCA110.00 0.98608 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36012 ZARNESTI 110.00 0.99323 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36023 COMRAT 110.00 0.98446 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36025 LEOVO 110.00 0.98505 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36028 TARECKLIA 110.00 1.00825 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36031 CIADYR 110.00 0.98133 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36032 CIMISLIA 110.00 0.99361 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36038 VULCANESTI 110.00 1.01882 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 11 34057 CHISINAU 110.00 1.01268 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 11 34060 HANCESTI 110.00 1.01154 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36005 BESARABEASCA110.00 0.97789 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36012 ZARNESTI 110.00 0.98755 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36023 COMRAT 110.00 0.97328 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36025 LEOVO 110.00 0.97681 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36028 TARECKLIA 110.00 1.00402 1.00767 1.10000 0.90000

J-6

'SUB ' RANGE SINGLE 11 36031 CIADYR 110.00 0.97715 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36032 CIMISLIA 110.00 1.00893 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36038 VULCANESTI 110.00 1.01831 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 12 34057 CHISINAU 110.00 1.01200 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 12 34060 HANCESTI 110.00 1.01108 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36005 BESARABEASCA110.00 0.97931 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36012 ZARNESTI 110.00 0.98973 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36023 COMRAT 110.00 0.97555 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36025 LEOVO 110.00 0.97870 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36028 TARECKLIA 110.00 0.98042 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36031 CIADYR 110.00 0.97929 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36032 CIMISLIA 110.00 0.98843 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36038 VULCANESTI 110.00 1.02033 1.01844 1.10000 0.90000 'SUB ' RANGE SINGLE 13 34057 CHISINAU 110.00 1.01180 1.01261 1.10000 0.90000 'SUB ' RANGE SINGLE 13 34060 HANCESTI 110.00 1.01096 1.01153 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36005 BESARABEASCA110.00 0.97618 0.98540 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36012 ZARNESTI 110.00 0.98786 0.99257 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36023 COMRAT 110.00 0.97140 0.98351 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36025 LEOVO 110.00 0.97573 0.98433 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36028 TARECKLIA 110.00 1.00483 1.00767 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36031 CIADYR 110.00 0.93289 0.98233 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36032 CIMISLIA 110.00 0.98598 0.99294 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36038 VULCANESTI 110.00 1.02059 1.01844 1.10000 0.90000

CONTINGENCY LEGEND: LABEL EVENTS SINGLE 1 : OPEN LINE FROM BUS 34057 [CHISINAU 110.00] TO BUS 34060 [HANCESTI 110.00] CKT 3 SINGLE 2 : OPEN LINE FROM BUS 34057 [CHISINAU 110.00] TO BUS 36005 [BESARABEASCA110.00] CKT 1 SINGLE 3 : OPEN LINE FROM BUS 34057 [CHISINAU 110.00] TO BUS 36032 [CIMISLIA 110.00] CKT 2 SINGLE 4 : OPEN LINE FROM BUS 34060 [HANCESTI 110.00] TO BUS 36025 [LEOVO 110.00] CKT 6 SINGLE 5 : OPEN LINE FROM BUS 36005 [BESARABEASCA110.00] TO BUS 36023 [COMRAT 110.00] CKT 4 SINGLE 6 : OPEN LINE FROM BUS 36012 [ZARNESTI 110.00] TO BUS 36023 [COMRAT 110.00] CKT 10 SINGLE 7 : OPEN LINE FROM BUS 36012 [ZARNESTI 110.00] TO BUS 36038 [VULCANESTI 110.00] CKT 14 SINGLE 8 : OPEN LINE FROM BUS 36023 [COMRAT 110.00] TO BUS 36025 [LEOVO 110.00] CKT 7 SINGLE 9 : OPEN LINE FROM BUS 36023 [COMRAT 110.00] TO BUS 36028 [TARECKLIA 110.00] CKT 9 SINGLE 10 : OPEN LINE FROM BUS 36023 [COMRAT 110.00] TO BUS 36031 [CIADYR 110.00] CKT 8 SINGLE 11 : OPEN LINE FROM BUS 36023 [COMRAT 110.00] TO BUS 36032 [CIMISLIA 110.00] CKT 5 SINGLE 12 : OPEN LINE FROM BUS 36028 [TARECKLIA 110.00] TO BUS 36038 [VULCANESTI 110.00] CKT 13 SINGLE 13 : OPEN LINE FROM BUS 36031 [CIADYR 110.00] TO BUS 36038 [VULCANESTI 110.00] CKT 12

J-7

Table J-1 The busses with maximum and minimum voltage levels from the loading report

Line Tripped Buss Name Voltage [p.u.] No line tripped Vulcanesti 1,018 Ciadyr 0,982 Chisinau-Hancesti Vulcanesti 1,018 Ciadyr 0,982 Chisinau -Besarabeasca Vulcanesti 1,018 Ciadyr 0,968 Chisinau-Cimislia Vulcanesti 1,017 Cimislia 0,962 Hancesti-Leovo Vulcanesti 1,018 Comrat 0,977 Besarabeasca-Comrat Vulcanesti 1,019 Ciadyr 0,983 Zarnesti-Comrat Vulcanesti 1,019 Comrat 0,981 Zarnesti-Vulcanesti Vulcanesti 0,019 Zarnesti 0,957 Comrat-Leovo Vulcanesti 1,019 Ciadyr 0,982 Comrat-Tarecklia Vulcanesti 1,021 Comrat 0,973 Comrat-Ciadyr Vulcanesti 1,018 Ciadyr 0,981 Comrat-Cimislia Vulcanesti 1,018 Comrat 0,973 Tarecklia-Vulcanesti Vulcanesti 1,02 Comrat 0,976 Ciadyr-Vulcanesti Vulcanesti 1,021 Ciadyr 0,933

J-8

Appendix K Base Case – Line Diagram with Line Capacities

Load

Generator

Three winding transformer

Switched shunt

400 kV Line

330 kV Line 110 kV Line

Active Power Flow

Reactive Power Flow

Line Offline

Figure K-1 One line diagram with line capacities

K-1

Appendix L Scenario I – Overload Report

ACCC OVERLOAD REPORT: MONITORED BRANCHES AND INTERFACES LOADED ABOVE 100.0 % OF RATING SET A % LOADING VALUES ARE % MVA FOR TRANSFORMERS AND % CURRENT FOR NON-TRANSFORMER BRANCHES INCLUDES VOLTAGE REPORT

AC CONTINGENCY RESULTS FILE: Accc.acc DISTRIBUTION FACTOR FILE: Dfx.dfx SUBSYSTEM DESCRIPTION FILE: Sub.sub MONITORED ELEMENT FILE: Mon.mon CONTINGENCY DESCRIPTION FILE: Cont.con

**PERCENT LOADING UNITS** %MVA FOR TRANSFORMERS % I FOR NON-TRANSFORMER BRANCHES

**OPTIONS USED IN CONTINGENCY ANALYSIS** Solution engine: Full Newton-Raphson (FNSL) Solution options Tap adjustment: Stepping Area interchange control: Disable Phase shift adjustment: Disable Dc tap adjustment: Disable Switch shunt adjustment: Lock all Non diverge: Enable Mismatch tolerance (MW ): ************************** Dispatch mode: Disable

Violation with generators set at:

('genA = ', 61, ' genB = ', 0, ' genC = ', 0, ' genD = ', 0, ' genE = ', 0)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 2 36005 BESARABEASCA110.00 1.10054 1.07221 1.10000 0.90000

Violation with generators set at:

('genA = ', 0, ' genB = ', 26, ' genC = ', 0, ' genD = ', 0, ' genE = ', 0)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 6 36012 ZARNESTI 110.00 1.10092 1.05221 1.10000 0.90000

Violation with generators set at:

('genA = ', 0, ' genB = ', 0, ' genC = ', 31, ' genD = ', 0, ' genE = ', 0)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 8 36025 LEOVO 110.00 1.10125 1.03956 1.10000 0.90000

Violation with generators set at:

('genA = ', 0, ' genB = ', 0, ' genC = ', 0, ' genD = ', 85, ' genE = ', 0)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN

L-1

'SUB ' RANGE SINGLE 13 36023 COMRAT 110.00 0.89329 1.00134 1.10000 0.90000

Violation with generators set at:

('genA = ', 0, ' genB = ', 0, ' genC = ', 0, ' genD = ', 0, ' genE = ', 103)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW % 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 3 97.2 100.6 102.6

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN

L-2

Appendix M Scenario I Reactive Power Compensation – Overload Report

AC CONTINGENCY RESULTS FILE: Accc.acc DISTRIBUTION FACTOR FILE: Dfx.dfx SUBSYSTEM DESCRIPTION FILE: Sub.sub MONITORED ELEMENT FILE: Mon.mon CONTINGENCY DESCRIPTION FILE: Cont.con

**PERCENT LOADING UNITS** %MVA FOR TRANSFORMERS % I FOR NON-TRANSFORMER BRANCHES

**OPTIONS USED IN CONTINGENCY ANALYSIS** Solution engine: Full Newton-Raphson (FNSL) Solution options Tap adjustment: Stepping Area interchange control: Disable Phase shift adjustment: Disable Dc tap adjustment: Disable Switch shunt adjustment: Lock all Non diverge: Enable Mismatch tolerance (MW ): ************************** Dispatch mode: Disable

Violation with generators set at:

('genA = ', 75, ' genB = ', 0, ' genC = ', 0, ' genD = ', 0, ' genE = ', 0)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW % 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 2 72.4 72.5 100.2

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN

Violation with generators set at:

('genA = ', 0, ' genB = ', 79, ' genC = ', 0, ' genD = ', 0, ' genE = ', 0)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW % 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 6 72.4 73.0 100.9 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 7 72.4 72.6 100.2

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN

Violation with generators set at:

('genA = ', 0, ' genB = ', 0, ' genC = ', 75, ' genD = ', 0, ' genE = ', 0)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW % 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 4 72.4 72.9 100.7 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 8 72.4 72.5 100.2

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN

Violation with generators set at:

('genA = ', 0, ' genB = ', 0, ' genC = ', 0, ' genD = ', 92, ' genE = ', 0)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW % 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 10 84.8 85.1 100.4

M-1

36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 13 84.8 84.9 100.1

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN

Violation with generators set at:

('genA = ', 0, ' genB = ', 0, ' genC = ', 0, ' genD = ', 0, ' genE = ', 99)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW % 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 3 97.2 97.3 100.1 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 11 97.2 97.6 100.4

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN

Appendix N Scenario II - Overload Report

AC CONTINGENCY RESULTS FILE: Accc.acc DISTRIBUTION FACTOR FILE: Dfx.dfx SUBSYSTEM DESCRIPTION FILE: Sub.sub MONITORED ELEMENT FILE: Mon.mon CONTINGENCY DESCRIPTION FILE: Cont.con

**PERCENT LOADING UNITS** %MVA FOR TRANSFORMERS % I FOR NON-TRANSFORMER BRANCHES

**OPTIONS USED IN CONTINGENCY ANALYSIS** Solution engine: Full Newton-Raphson (FNSL) Solution options Tap adjustment: Stepping Area interchange control: Disable Phase shift adjustment: Disable Dc tap adjustment: Disable Switch shunt adjustment: Lock all Non diverge: Enable Mismatch tolerance (MW ): ************************** Dispatch mode: Disable

Violation with generators set at: ('genA = ', 30, ' genB = ', 14, ' genC = ', 28, ' genD = ', 84, ' genE = ', 102)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN

N-2

'SUB ' RANGE SINGLE 2 36005 BESARABEASCA110.00 1.10031 1.06269 1.10000 0.90000

Violation with generators set at: ('genA = ', 29, ' genB = ', 15, ' genC = ', 28, ' genD = ', 84, ' genE = ', 102)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 7 36012 ZARNESTI 110.00 1.10294 1.04131 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36031 CIADYR 110.00 1.10011 1.09693 1.10000 0.90000

Violation with generators set at: ('genA = ', 29, ' genB = ', 14, ' genC = ', 29, ' genD = ', 84, ' genE = ', 102)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 11 36031 CIADYR 110.00 1.10006 1.09685 1.10000 0.90000

Violation with generators set at: ('genA = ', 29, ' genB = ', 14, ' genC = ', 28, ' genD = ', 85, ' genE = ', 102)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 11 36031 CIADYR 110.00 1.10027 1.09717 1.10000 0.90000

Violation with generators set at: ('genA = ', 29, ' genB = ', 14, ' genC = ', 28, ' genD = ', 84, ' genE = ', 103)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW % 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 3 97.2 100.6 100.6

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN

AC CONTINGENCY RESULTS FILE: Accc.acc DISTRIBUTION FACTOR FILE: Dfx.dfx SUBSYSTEM DESCRIPTION FILE: Sub.sub MONITORED ELEMENT FILE: Mon.mon

O-2

CONTINGENCY DESCRIPTION FILE: Cont.con

**PERCENT LOADING UNITS** %MVA FOR TRANSFORMERS % I FOR NON-TRANSFORMER BRANCHES

**OPTIONS USED IN CONTINGENCY ANALYSIS** Solution engine: Full Newton-Raphson (FNSL) Solution options Tap adjustment: Stepping Area interchange control: Disable Phase shift adjustment: Disable Dc tap adjustment: Disable Switch shunt adjustment: Lock all Non diverge: Enable Mismatch tolerance (MW ): ************************** Dispatch mode: Disable

Violation with generators set at: ('genA = ', 57, ' genB = ', 68, ' genC = ', 68, ' genD = ', 91, ' genE = ', 72)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 3 36028 TARECKLIA 110.00 0.89946 0.94045 1.10000 0.90000

Violation with generators set at: ('genA = ', 56, ' genB = ', 69, ' genC = ', 68, ' genD = ', 91, ' genE = ', 72)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 3 36028 TARECKLIA 110.00 0.89942 0.94036 1.10000 0.90000

Violation with generators set at: ('genA = ', 56, ' genB = ', 68, ' genC = ', 69, ' genD = ', 91, ' genE = ', 72)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 3 36028 TARECKLIA 110.00 0.89951 0.94047 1.10000 0.90000

Violation with generators set at: ('genA = ', 56, ' genB = ', 68, ' genC = ', 68, ' genD = ', 92, ' genE = ', 72)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW % 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 10 84.8 84.9 100.1 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 13 84.8 84.9 100.1

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 3 36028 TARECKLIA 110.00 0.89942 0.94036 1.10000 0.90000

Violation with generators set at: ('genA = ', 56, ' genB = ', 68, ' genC = ', 68, ' genD = ', 91, ' genE = ', 73)

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW %

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE SINGLE 3 36028 TARECKLIA 110.00 0.89934 0.94057 1.10000 0.90000

O-2

O-3

Appendix P Scenario II – Contingency Loading Report

ACCC LOADING REPORT: MONITORED BRANCHES AND INTERFACES USING RATING SET A % LOADING VALUES ARE % MVA FOR TRANSFORMERS AND % CURRENT FOR NON-TRANSFORMER BRANCHES INCLUDES VOLTAGE REPORT

AC CONTINGENCY RESULTS FILE: CONTINGENCYALLA.acc DISTRIBUTION FACTOR FILE: C:\Users\Joel\Desktop\Testfiler\Dfx.dfx SUBSYSTEM DESCRIPTION FILE: C:\Users\Joel\Desktop\Testfiler\Sub.sub MONITORED ELEMENT FILE: C:\Users\Joel\Desktop\Testfiler\Mon.mon CONTINGENCY DESCRIPTION FILE: C:\Users\Joel\Desktop\Testfiler\Cont.con

**PERCENT LOADING UNITS** %MVA FOR TRANSFORMERS % I FOR NON-TRANSFORMER BRANCHES

<------MULTI-SECTION LINE ------> <------MONITORED BRANCH ------> CONTINGENCY RATING FLOW % 34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 BASE CASE 84.8 23.3 27.3 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 BASE CASE 84.8 19.4 21.5 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 BASE CASE 97.2 69.7 66.5 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 BASE CASE 72.4 28.4 36.8 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 BASE CASE 72.4 5.4 7.1 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 BASE CASE 72.4 11.1 14.5 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 BASE CASE 72.4 17.9 23.8 36023 COMRAT 110.00 36025*LEOVO 110.00 7 BASE CASE 72.4 3.9 5.0 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 BASE CASE 85.8 27.8 30.8 36023 COMRAT 110.00 36031*CIADYR 110.00 8 BASE CASE 84.8 19.4 20.9 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 BASE CASE 97.2 30.0 28.7 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 BASE CASE 84.8 26.0 30.2 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 BASE CASE 84.8 57.5 61.8 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 1 84.8 0.0 0.0 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 1 84.8 19.1 21.2 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 1 97.2 69.1 66.0 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 1 72.4 29.1 37.8 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 1 72.4 5.8 7.5 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 1 72.4 11.2 14.6 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 1 72.4 18.0 23.9 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 1 72.4 4.6 6.0 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 1 85.8 28.0 31.0 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 1 84.8 19.3 20.8 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 1 97.2 30.7 29.3 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 1 84.8 26.1 30.4 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 1 84.8 57.6 62.0

P-1

34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 SINGLE 2 84.8 21.9 25.7 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 2 84.8 0.0 0.0 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 2 97.2 76.0 72.5 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 2 72.4 32.0 41.4 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 2 72.4 24.8 31.2 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 2 72.4 13.2 17.3 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 2 72.4 20.0 26.6 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 2 72.4 6.1 7.9 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 2 85.8 32.1 35.3 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 2 84.8 16.7 18.0 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 2 97.2 23.7 22.6 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 2 84.8 29.8 34.7 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 2 84.8 60.2 64.8 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 3 84.8 18.0 21.2 34057*CHISINAU 110.00 36005 BESARABEASCA110.00 1 SINGLE 3 84.8 34.0 40.1 34057*CHISINAU 110.00 36032 CIMISLIA 110.00 2 SINGLE 3 97.2 0.0 0.0 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 3 72.4 42.4 58.8 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 3 72.4 11.1 15.7 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 3 72.4 19.4 27.7 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 3 72.4 25.6 36.8 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 3 72.4 18.1 25.3 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 3 85.8 43.2 52.1 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 3 84.8 9.5 11.0 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 3 97.2 99.6 99.1 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 3 84.8 41.8 51.4 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 3 84.8 68.0 79.0 34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 SINGLE 4 84.8 27.2 31.9 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 4 84.8 24.2 27.1 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 4 97.2 78.5 75.5 34060*HANCESTI 110.00 36025 LEOVO 110.00 6 SINGLE 4 72.4 0.0 0.0 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 4 72.4 1.5 1.9 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 4 72.4 14.4 19.0 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 4 72.4 21.1 28.3 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 4 72.4 27.5 34.7 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 4 85.8 34.3 38.1 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 4 84.8 15.2 16.5 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 4 97.2 21.1 20.3 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 4 84.8 31.9 37.6 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 4 84.8 61.7 67.1 34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 SINGLE 5 84.8 23.6 27.8 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 5 84.8 24.9 27.4 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 5 97.2 67.9 64.9 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 5 72.4 27.3 35.5

P-2

36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 5 72.4 0.0 0.0 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 5 72.4 10.5 13.8 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 5 72.4 17.3 23.0 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 5 72.4 3.7 4.9 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 5 85.8 26.6 29.5 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 5 84.8 20.2 21.7 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 5 97.2 31.8 30.4 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 5 84.8 24.8 28.9 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 5 84.8 56.7 61.0 34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 SINGLE 6 84.8 23.4 27.5 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 6 84.8 20.9 23.3 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 6 97.2 72.5 69.3 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 6 72.4 30.1 39.1 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 6 72.4 3.9 5.1 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 6 72.4 0.0 0.0 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 6 72.4 7.7 10.2 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 6 72.4 4.9 6.3 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 6 85.8 30.9 34.2 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 6 84.8 17.4 18.7 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 6 97.2 27.2 26.0 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 6 84.8 28.9 33.6 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 6 84.8 59.6 64.1 34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 SINGLE 7 84.8 23.5 27.6 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 7 84.8 22.0 24.3 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 7 97.2 74.2 70.8 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 7 72.4 31.3 40.5 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 7 72.4 2.9 3.7 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 7 72.4 7.8 9.8 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 7 72.4 0.0 0.0 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 7 72.4 5.5 7.1 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 7 85.8 33.1 36.4 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 7 84.8 16.0 17.2 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 7 97.2 25.5 24.3 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 7 84.8 30.8 35.9 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 7 84.8 60.9 65.5 34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 SINGLE 8 84.8 23.4 27.5 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 8 84.8 19.5 21.8 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 8 97.2 70.0 67.2 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 8 72.4 27.5 34.6 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 8 72.4 5.4 7.1 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 8 72.4 11.2 14.9 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 8 72.4 18.0 24.0 36023*COMRAT 110.00 36025 LEOVO 110.00 7 SINGLE 8 72.4 0.0 0.0

P-3

36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 8 85.8 28.0 31.2 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 8 84.8 19.3 20.8 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 8 97.2 29.6 28.4 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 8 84.8 26.2 30.6 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 8 84.8 57.7 62.3 34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 SINGLE 9 84.8 23.7 27.9 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 9 84.8 24.0 26.5 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 9 97.2 77.8 74.0 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 9 72.4 33.6 43.3 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 9 72.4 0.8 1.1 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 9 72.4 15.9 20.6 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 9 72.4 22.5 29.8 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 9 72.4 7.2 9.3 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 9 85.8 0.0 0.0 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 9 84.8 13.4 14.4 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 9 97.2 22.1 21.1 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 9 84.8 1.2 1.4 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 9 84.8 63.5 68.2 34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 SINGLE 10 84.8 23.0 27.0 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 10 84.8 16.5 18.4 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 10 97.2 64.7 61.9 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 10 72.4 25.1 32.7 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 10 72.4 8.3 10.8 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 10 72.4 8.3 11.0 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 10 72.4 15.4 20.6 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 10 72.4 4.4 5.8 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 10 85.8 22.7 25.3 36023*COMRAT 110.00 36031 CIADYR 110.00 8 SINGLE 10 84.8 0.0 0.0 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 10 97.2 35.0 33.5 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 10 84.8 21.0 24.7 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 10 84.8 76.9 84.4 34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 SINGLE 11 84.8 25.4 29.8 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 11 84.8 13.2 14.7 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 11 97.2 99.6 96.0 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 11 72.4 21.8 28.3 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 11 72.4 11.8 15.4 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 11 72.4 7.1 9.4 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 11 72.4 14.0 18.6 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 11 72.4 6.2 8.0 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 11 85.8 20.1 22.4 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 11 84.8 24.5 26.3 36023*COMRAT 110.00 36032 CIMISLIA 110.00 5 SINGLE 11 97.2 0.0 0.0 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 11 84.8 18.7 21.7

P-4

36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 11 84.8 52.4 56.2 34057 CHISINAU 110.00 34060*HANCESTI 110.00 3 SINGLE 12 84.8 23.7 27.8 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 12 84.8 23.9 26.4 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 12 97.2 77.6 73.7 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 12 72.4 33.5 43.2 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 12 72.4 0.9 1.2 36012 ZARNESTI 110.00 36023*COMRAT 110.00 10 SINGLE 12 72.4 15.8 20.4 36012*ZARNESTI 110.00 36038 VULCANESTI 110.00 14 SINGLE 12 72.4 22.4 29.7 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 12 72.4 7.0 9.1 36023 COMRAT 110.00 36028*TARECKLIA 110.00 9 SINGLE 12 85.8 1.1 1.2 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 12 84.8 13.5 14.5 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 12 97.2 22.3 21.2 36028*TARECKLIA 110.00 36038 VULCANESTI 110.00 13 SINGLE 12 84.8 0.0 0.0 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 12 84.8 63.4 68.0 34057*CHISINAU 110.00 34060 HANCESTI 110.00 3 SINGLE 13 84.8 23.8 28.0 34057 CHISINAU 110.00 36005*BESARABEASCA110.00 1 SINGLE 13 84.8 25.9 30.5 34057 CHISINAU 110.00 36032*CIMISLIA 110.00 2 SINGLE 13 97.2 82.3 81.9 34060 HANCESTI 110.00 36025*LEOVO 110.00 6 SINGLE 13 72.4 35.4 48.5 36005*BESARABEASCA110.00 36023 COMRAT 110.00 4 SINGLE 13 72.4 6.1 8.4 36012*ZARNESTI 110.00 36023 COMRAT 110.00 10 SINGLE 13 72.4 18.5 25.9 36012 ZARNESTI 110.00 36038*VULCANESTI 110.00 14 SINGLE 13 72.4 24.7 34.4 36023 COMRAT 110.00 36025*LEOVO 110.00 7 SINGLE 13 72.4 12.3 16.9 36023*COMRAT 110.00 36028 TARECKLIA 110.00 9 SINGLE 13 85.8 40.9 48.5 36023 COMRAT 110.00 36031*CIADYR 110.00 8 SINGLE 13 84.8 76.8 85.3 36023 COMRAT 110.00 36032*CIMISLIA 110.00 5 SINGLE 13 97.2 19.3 19.2 36028 TARECKLIA 110.00 36038*VULCANESTI 110.00 13 SINGLE 13 84.8 40.3 47.9 36031*CIADYR 110.00 36038 VULCANESTI 110.00 12 SINGLE 13 84.8 0.0 0.0

MONITORED VOLTAGE REPORT: SYSTEM CONTINGENCY <------B U S ------> V-CONT V-INIT V-MAX V-MIN 'SUB ' RANGE BASE CASE 34057 CHISINAU 110.00 1.00253 1.00253 1.10000 0.90000 'SUB ' RANGE BASE CASE 34060 HANCESTI 110.00 1.00370 1.00370 1.10000 0.90000 'SUB ' RANGE BASE CASE 36005 BESARABEASCA110.00 1.06186 1.06186 1.10000 0.90000 'SUB ' RANGE BASE CASE 36012 ZARNESTI 110.00 1.03927 1.03927 1.10000 0.90000 'SUB ' RANGE BASE CASE 36023 COMRAT 110.00 1.05257 1.05257 1.10000 0.90000 'SUB ' RANGE BASE CASE 36025 LEOVO 110.00 1.06497 1.06497 1.10000 0.90000 'SUB ' RANGE BASE CASE 36028 TARECKLIA 110.00 1.01340 1.01340 1.10000 0.90000 'SUB ' RANGE BASE CASE 36031 CIADYR 110.00 1.09688 1.09688 1.10000 0.90000 'SUB ' RANGE BASE CASE 36032 CIMISLIA 110.00 1.07797 1.07797 1.10000 0.90000 'SUB ' RANGE BASE CASE 36038 VULCANESTI 110.00 1.00080 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 1 34057 CHISINAU 110.00 1.00000 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 1 34060 HANCESTI 110.00 1.00734 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36005 BESARABEASCA110.00 1.06102 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36012 ZARNESTI 110.00 1.03871 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36023 COMRAT 110.00 1.05190 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36025 LEOVO 110.00 1.06508 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36028 TARECKLIA 110.00 1.01289 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36031 CIADYR 110.00 1.09629 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36032 CIMISLIA 110.00 1.07667 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 1 36038 VULCANESTI 110.00 1.00049 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 2 34057 CHISINAU 110.00 1.00239 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 2 34060 HANCESTI 110.00 1.00297 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36005 BESARABEASCA110.00 1.09945 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36012 ZARNESTI 110.00 1.03792 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36023 COMRAT 110.00 1.05905 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36025 LEOVO 110.00 1.06659 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36028 TARECKLIA 110.00 1.01085 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36031 CIADYR 110.00 1.09560 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36032 CIMISLIA 110.00 1.07896 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 2 36038 VULCANESTI 110.00 0.99682 1.00080 1.10000 0.90000

P-5

'SUB ' RANGE SINGLE 3 34057 CHISINAU 110.00 1.00000 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 3 34060 HANCESTI 110.00 0.99584 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36005 BESARABEASCA110.00 0.98041 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36012 ZARNESTI 110.00 0.96062 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36023 COMRAT 110.00 0.96774 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36025 LEOVO 110.00 0.98874 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36028 TARECKLIA 110.00 0.93988 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36031 CIADYR 110.00 1.01574 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36032 CIMISLIA 110.00 1.03389 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 3 36038 VULCANESTI 110.00 0.95769 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 4 34057 CHISINAU 110.00 1.00000 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 4 34060 HANCESTI 110.00 1.00587 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36005 BESARABEASCA110.00 1.05313 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36012 ZARNESTI 110.00 1.02777 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36023 COMRAT 110.00 1.04769 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36025 LEOVO 110.00 1.09532 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36028 TARECKLIA 110.00 1.00139 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36031 CIADYR 110.00 1.08521 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36032 CIMISLIA 110.00 1.07052 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 4 36038 VULCANESTI 110.00 0.99118 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 5 34057 CHISINAU 110.00 1.00206 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 5 34060 HANCESTI 110.00 1.00367 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36005 BESARABEASCA110.00 1.07127 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36012 ZARNESTI 110.00 1.03886 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36023 COMRAT 110.00 1.04945 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36025 LEOVO 110.00 1.06352 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36028 TARECKLIA 110.00 1.01345 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36031 CIADYR 110.00 1.09641 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36032 CIMISLIA 110.00 1.07671 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 5 36038 VULCANESTI 110.00 1.00165 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 6 34057 CHISINAU 110.00 1.00119 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 6 34060 HANCESTI 110.00 1.00266 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36005 BESARABEASCA110.00 1.06048 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36012 ZARNESTI 110.00 1.04270 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36023 COMRAT 110.00 1.05290 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36025 LEOVO 110.00 1.06365 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36028 TARECKLIA 110.00 1.01305 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36031 CIADYR 110.00 1.09609 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36032 CIMISLIA 110.00 1.07653 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 6 36038 VULCANESTI 110.00 1.00278 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 7 34057 CHISINAU 110.00 1.00084 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 7 34060 HANCESTI 110.00 1.00236 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36005 BESARABEASCA110.00 1.06380 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36012 ZARNESTI 110.00 1.09994 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36023 COMRAT 110.00 1.05864 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36025 LEOVO 110.00 1.06666 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36028 TARECKLIA 110.00 1.01242 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36031 CIADYR 110.00 1.09649 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36032 CIMISLIA 110.00 1.07877 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 7 36038 VULCANESTI 110.00 1.00050 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 8 34057 CHISINAU 110.00 1.00222 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 8 34060 HANCESTI 110.00 1.00553 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36005 BESARABEASCA110.00 1.05441 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36012 ZARNESTI 110.00 1.03317 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36023 COMRAT 110.00 1.04280 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36025 LEOVO 110.00 1.09759 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36028 TARECKLIA 110.00 1.00816 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36031 CIADYR 110.00 1.09058 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36032 CIMISLIA 110.00 1.07250 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 8 36038 VULCANESTI 110.00 0.99846 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 9 34057 CHISINAU 110.00 1.00000 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 9 34060 HANCESTI 110.00 1.00156 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36005 BESARABEASCA110.00 1.06717 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36012 ZARNESTI 110.00 1.04055 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36023 COMRAT 110.00 1.06587 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36025 LEOVO 110.00 1.06962 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36028 TARECKLIA 110.00 1.00455 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36031 CIADYR 110.00 1.09818 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36032 CIMISLIA 110.00 1.08077 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 9 36038 VULCANESTI 110.00 1.00228 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 10 34057 CHISINAU 110.00 1.00395 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 10 34060 HANCESTI 110.00 1.00485 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36005 BESARABEASCA110.00 1.05693 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36012 ZARNESTI 110.00 1.03083 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36023 COMRAT 110.00 1.04255 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36025 LEOVO 110.00 1.06047 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36028 TARECKLIA 110.00 1.00435 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36031 CIADYR 110.00 1.07383 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36032 CIMISLIA 110.00 1.07482 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 10 36038 VULCANESTI 110.00 0.98853 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 11 34057 CHISINAU 110.00 1.00000 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 11 34060 HANCESTI 110.00 1.00407 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36005 BESARABEASCA110.00 1.05946 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36012 ZARNESTI 110.00 1.04276 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36023 COMRAT 110.00 1.04423 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36025 LEOVO 110.00 1.06307 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36028 TARECKLIA 110.00 1.01872 1.01340 1.10000 0.90000

P-6

'SUB ' RANGE SINGLE 11 36031 CIADYR 110.00 1.10000 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36032 CIMISLIA 110.00 1.06764 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 11 36038 VULCANESTI 110.00 1.00823 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 12 34057 CHISINAU 110.00 1.00006 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 12 34060 HANCESTI 110.00 1.00171 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36005 BESARABEASCA110.00 1.06915 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36012 ZARNESTI 110.00 1.04179 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36023 COMRAT 110.00 1.06836 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36025 LEOVO 110.00 1.07148 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36028 TARECKLIA 110.00 1.07314 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36031 CIADYR 110.00 1.09949 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36032 CIMISLIA 110.00 1.08224 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 12 36038 VULCANESTI 110.00 1.00194 1.00080 1.10000 0.90000 'SUB ' RANGE SINGLE 13 34057 CHISINAU 110.00 1.00000 1.00253 1.10000 0.90000 'SUB ' RANGE SINGLE 13 34060 HANCESTI 110.00 0.99793 1.00370 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36005 BESARABEASCA110.00 1.00193 1.06186 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36012 ZARNESTI 110.00 0.98936 1.03927 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36023 COMRAT 110.00 0.98218 1.05257 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36025 LEOVO 110.00 1.00819 1.06497 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36028 TARECKLIA 110.00 0.97160 1.01340 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36031 CIADYR 110.00 1.06273 1.09688 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36032 CIMISLIA 110.00 1.03284 1.07797 1.10000 0.90000 'SUB ' RANGE SINGLE 13 36038 VULCANESTI 110.00 0.99314 1.00080 1.10000 0.90000

P-7

Appendix Q Scenario II – Line Diagram for Line Capacities

Load

Generator

Three winding transformer

Switched shunt

400 kV Line

330 kV Line 110 kV Line

Active Power Flow

Reactive Power Flow

Line Offline

Figure Q-1 One line diagram with line capacities

Q-1

Appendix R Scenario II All Generators – Results

300

250

200

Cimislia Ciadyr 150 Total Generation Power[MW] Besarabeasca Leovo 100 Zarnesti

331 111 166 221 276 386 441 496 551 606 661 716 771 826 881 936 991

1046 1706 1101 1156 1211 1266 1321 1376 1431 1486 1541 1596 1651 1761 1816 1871 1926 1981 2036 2091 2146 Iteration

Figure R-1 Shows the iterations with all generators in scenario I.

R-1

Generation without reactive Generation with reactive

power compensation power compensation

600 10000 8000 400 6000 200 4000

2000 Frequency

0 Frequency 0

0-20

20-40 40-60 60-80

60-100

100-120 120-140 140-160 160-180 180-200 200-220 220-240 240-260 260-280 280-300 300-320 320-340 340-360 Power [MW] Power [MW]

Figure R-2 Histogram over the maximum generation without reactive power Figure R-4 F Histogram over the maximum generation with reactive power compensation compensation

300 250

Total Generation 200 Besarabeasca 150 Zarnesti 100 Power[MW] Leovo 50 Ciadyr 0 Cimislia 1 6 11 16 21 26 31 36 41 46 51 Iteration

Figure R-3 Results from the second iteration with a narrow interval for each generator

R-2

Appendix S The Contingency and Automation Process in PSS/E

The Contingency and Automation Process in PSS/E

S-1 Contingency Analysis

PSS/E has an effective way of performing a contingency analysis without having to trip each line by itself manually. To execute a contingency analysis in PSS/E you will first have to create files of three different file types; one that describe the subsystem concerned by the analysis (.sub), one that describes what changes should be mad in the system (.con) and finally one that controls which values that should be monitored (.mon). These files then combine in the Distribution Factor Data File (.dfx) which in turn is used to create the Contingency Solution Output file (.acc) which gives you the contingency report with the specified data given. The .sub, .con and .mon files can be automatically created within PSS/E or manually.

Different kind of reports can be given but the main ones are the Spreadsheet Overload report, the Spreadsheet Load report and the Available Capacity report, all these reports are spreadsheet compatible. The overload report names branches that have been overloaded during the contingency analysis and/or busses whose voltage levels deviate from the given levels in the monitor file. The load report shows voltage values and used capacity for all busses and branches defined in the subsystem file. The capacity report shows the contingency worst case run; it shows you all the busses in the subsystem file together with the highest usage of line capacity during the entire contingency study, which line that was tripped for each worst case scenario is also given. There are also non spreadsheet reports for the first two stated and also a Non-converged network report which is important to find solutions that have not converged aka “blown ups”.

For the creation of the Subsystem Description Data File one have to choose a specific area (busses, branches etc.) of which to study, the area can be selected in several ways using the program description of area, zones, by owners, by base kV or by simply hand picking the specific busses needed for the intended contingency analysis. Several subsystems can be defined and studied at once, up to one hundred different subsystems can be included in one .sub file. The default code created by PSS/E is as follows:

COM SUBSYSTEM description file entry created by PSS®E Config File Builder SUBSYSTEM 'example' 'Bus nr' 'Bus nr' END

Busses are entered by the command BUS followed by the bus number before the end statements, the same true for areas (AREA), zones (ZONE), owners (OWNER), per kV level (KV) followed by the specified kV level. The COM statement is followed by a comment to the sub, mon and con files.

When creating the Monitored Element Data File in PSS/E options are given for which voltage range that is to be monitored as maximum and minimum, also it is possible to specify a specific voltage deviation. The default code created by the PSS/E with all branches and busses specified in the subsystem monitored is as follows:

S-1

COM MONITORED element file entry created by PSS®E Config File Builder MONITOR VOLTAGE RANGE SUBSYSTEM 'example' 0.950 1.050 MONITOR BRANCHES IN SUBSYSTEM 'example' END

If any specific branch, bus, transformer etc. would need extra supervision it can be added before the end statement.

The Automatic Contingency File given by PSS/E looks as follows: COM CONTINGENCY description file entry created by PSS®E Config File Builder SINGLE BRANCH IN SUBSYSTEM 'example' END

This is done with the assumption that only the tripping of a single branches are under interest and thus the only selected criteria while creating the file in PSS/E. Other branches can be included by using the statement 'branch nr' TO 'branch nr ' See Appendix Tfor sub, mon and con files used in the simulations. [33]

S-2 The Automation Process

There are several ways to automate a process with PSS/E; the main methods are connected to the creation of response files. The response files can be created using the PSS/E recorder function where the basic principle is that the recorder, after started, records your actions within PSS/E and saves the “commands” in a response file.

Figure S-1 Shows the recorder function within PSS/E

The basic response file with the file extension .idv creates a response file with the PSS/E batch commands. This makes it a viable option for basic automations such as changing bus values or generator output but for more advance operations. For more advance operations where it is necessary to directly write new commands within the response file it is necessary to be familiar with the PSSE batch commands. [33]

To facilitate the automation process IPLAN has been developed as a direct programing language design for PSS/E. With IPLAN it is not possible to create a response file directly with the recorder i.e. the file or script has to be written manually in a text editor. Being developed specifically for PSS/E it does not have the diversity of a modern programing language. [33]

From version PSS/E-30 the program comes with an interface making it possible to implement Python programing in the automation process [34]. Python is a modern, powerful, dynamic, interpreted

S-2 object-oriented program language often compared to Tcl, Perl, Ruby, Scheme or Java [35]. The Python script can be created through the recorder function in PSS/E, as were the case for the idv files, but now with the Python extension .py. Python programing language makes editing of the produced script much easier. It is of course also possible to create the script from scratch in a text editor to grasp each function fully. [33]

To run a response file or a Python script file one can go through the recorder function; pressing play gives you the option to open a file which if opened automatically runs it. The main module, psspy, is a wrapper function for the PSS/E Application Program Interface (API). PSS/E also comes with a built in Python interpreter, the IDLE interactive interpreter Python Shell, this shell opens by running the RunIdle.py file which is included in the EXAMPLE directory in the PSS/E folder. The IDLE shell is a platform making it possible to edit and run the Python script. It also has an extensive help function clarifying built in modules in the API. [36]

S-3

Appendix T Sub, Mon and Con files for the contingency analysis

Figure T-1 Contingency file created for the contingency analysis

Figure T-2 Monitor file created for the contingency analysis

Figure T-3 Subsystem file created for the contingency analysis

T-1

Appendix U Division of the Work Between the Authors

The report has two authors where some of the work has been performed together and some parts are the responsibility of a single author. Below follows a description dividing the responsibilities.

 The background to the project was necessary for a joint discussion leading up to the aim and goals of the project, in this part all necessary contacts were made. This section is not possible to divide between the two authors.  The theory can be divided as parts written by one single author: o Active and reactive power – Joel Eriksson o Introduction to the electrical system – Simon Gozdz Englund o Components in the grid – Simon Gozdz Englund o Per-Unit system – Joel Eriksson o Equivalents in electrical system – Joel Eriksson o Static Modelling – Joel Eriksson  The wind power research was the responsibility of Simon Gozdz Englund  The method with constructing the model was based on an iterative process where parts were successively created; the process cannot be divided between the two authors.  The automation process, using Python programming, within PSS/E was the responsibility of Joel Eriksson  The scenarios were jointly decided and executed by Joel Eriksson  The economic aspects were the responsibility of Simon Gozdz Englund  The discussion was a carried out between the two authors and must thus be the responsibility of both of the authors.

U-1