Energy Storage Solutions for Electric Bus Fast Charging Stations

Examensarbete 30 hp

Energy storage solutions for electric bus fast charging stations

Cost optimization of grid connection and grid reinforcements

Malin Andersson Abstract Energy storage solutions for electric bus fast charging stations Malin Andersson

Teknisk- naturvetenskaplig fakultet UTH-enheten This study investigates the economic benefits of installing a lithium-ion battery storage (lithium iron phosphate, LFP and lithium Besöksadress: titanate, LTO) at an electric bus fast charging station. It is Ångströmlaboratoriet Lägerhyddsvägen 1 conducted on a potential electric bus system in the Swedish city Hus 4, Plan 0 Västerås, and based on the existing bus schedules and routes as well as the local distribution system. The size of the energy storage as Postadress: well as the maximum power outtake from the grid is optimized in order Box 536 751 21 Uppsala to minimize the total annual cost of the connection. The assessment of the distribution system shows that implementing an electric bus Telefon: system based on opportunity charging in Västerås does not cause over- 018 – 471 30 03 capacity in the 10 kV grid during normal feeding mode. However, grid

Telefax: reinforcement might become necessary to guarantee potential backup 018 – 471 30 00 feeding modes. Batteries are not a cost effective option to decrease grid owner investments in new transformers. However, battery energy Hemsida: storage have the possibility to decrease the annual cost of http://www.teknat.uu.se/student connecting a fast charging station to the low-voltage grid. The main advantage of the storage system is to decrease the fees to the grid owner. Of the studied batteries, LTO is the most cost effective solution because of its larger possible depth-of-discharge for a given cycle life. The most important characteristics, that determine if a fast charging station could benefit economically from an energy storage, is the bus frequency. The longer the time in between buses and the higher the power demand, the more advantageous is the energy storage.

Handledare: Kenny Granath Ämnesgranskare: Juan de Santiago Examinator: Petra Jönsson ISSN: 1650-8300, UPTEC ES 17 002 Executive summary

In Västerås, the possibility to implement electric buses is investigated. The system that is considered is based on high power battery chargers at the end stations. This type of charging would cause a high load on the distribution system and potentially demand expensive reinforcements. In addition, the grid connection constitute a high cost for the charigng station owner. In the investigation, the economic beneﬁts of connecting a lithium-ion battery (lithium titanate, LTO and lithium iron phosphate, LFP) to these charging stations are investigated.

The assessment of Mälarenergi’s distribution grid shows that there is enough available capacity in the 10 kV-grid during normal feeding to support the potential electric bus system. However, the transformer substations that are located close to the bus end stations Bjurhovda, Björnögården, Hälla and Hacksta lacks the capacity to connect the fast charging station in question. The study shows that the most cost eﬀective solution would be to invest in a new transformer substation instead of decreasing the power demand by the use of an energy storage system.

For the charging station owner, the most cost eﬀective solution in all studied cases would be to become high-voltage customers because of the lower fees. Considering a high-voltage connection, lithium-ion batteries of today’s price can not decrease the annual cost of connection. However, at some stations an LTO battery storage can be used to decrease the annual costs of a low-voltage connection, mainly by decreasing the fees. The characteristics of such a station are a low bus frequency and high power demand (Hälla is one example).

The LTO battery is superior to the LFP battery because it can discharge to a deeper level for the same cycle life. The lifetime is the main limiting factor for the battery storage since it is approximately 8 years whereas an grid investment would last for 40 years. The price of the LTO battery is assumed to be 8500 SEK/kWh in this study, but according to the trend, the cost of lithium-ion batteries is decreasing. A decrease in price would mean that more stations beneﬁts from using an energy storage.

3 Acknowledgment

This thesis covers 30 credits (hp) and completes my master’s degree in Energy Systems Engineering at Uppsala University and the Swedish University of Agricultural Sciences (SLU). The project was conducted on behalf of Mälarenergi Elnät in Västerås.

I would like to thank my supervisors at Mälarenergi Elnät, Kenny Granath and Johanna Rosenlind, for your guidance throughout the project. A big thank you also to everyone at the grid planning department for creating a welcoming environment and for answering all my questions and helping me out in various ways. In addition, I want to thank Juan de Santiago at the Division of Electricity at Uppsala University for your involvement and help.

Others that have contributed to this paper include Peter Norrman at Hybricon Bus Systems, Fredrik Persson at Göteborg Energi and David Steen at Chalmers. Thank you for taking the time to discuss and answer my questions.

Lastly, I would like to thank my parents and Sebastian for all your input, advice and encouragement and for reading the whole thesis multiple times without even complaining.

4 Sammanfattning

I takt med att befolkningen i städerna växer, ökar kraven på en hållbar och eﬀektiv kollektivtraﬁk. Flera svenska städer, däribland Umeå, Stockholm och Göteborg, har implementerat snabbladdande elbussar på några av sina busslinjer. Även i Västerås utreds möjligheten att införa den här sortens bussystem.

Systemet bygger på något som kallas Opportunity charging, vilket innebär att bussarna laddas på hög effekt vid ändhållplatserna under den tid som bussen normalt står stilla där. Den här typen av laddning möjliggör mindre bussbatterier och färre bussar än nattlig depåladdning, men den höga laddeffekten in- nebär också en påfrestning på distributionsnätet. Om snabbladdningsstationerna leder till överbelastning på det befintliga distributionsnätet blir det nödvändigt att göra förstärkningar. Laddoperatören, som äger och driver laddstationerna, betalar en avgift till nätägaren för att vara ansluten till nätet och ta ut effekt. Dessutom bekostar laddoperatören själva anslutningen. Denna måste dimensioneras med avseende på termisk kapacitet, spänningsfall och utlösningsvillkor. Laddstationer med högt effektuttag och/eller stort avstånd till en nätstation kan bli kostsamma att ansluta till nätet på grund av höga avgifter och väl tilltagna kablar.

Den här rapporten syftar till att undersöka huruvida ett energilager skulle kunna sänka nätinvester- ingskostnader för nätägaren och/eller nätanslutningskostnader för laddoperatören genom att sänka och jämna ut eﬀektuttaget från laddstationerna. Utredningen är gjort med grund i det elbussytem som övervägs i Västerås samt det lokala distributionsnätet.

Lastprofilerna från de olika tänkta laddstationerna uppskattas med hjälp av bussarnas tidtabeller, körsträckor samt antagen förbrukning om 2.3 kWh/km. Distributionsnätets tillgängliga kapacitet under normalmatning utvärderas med hjälp av data över alla transformatorers högsta effektflöde samt kablarnas, transformatorernas och nätstationernas belastningsförmåga. Det visar sig att existerande 10kV-nät inte löper någon risk att överbelastas vid implementering av snabbladdningsstationer vid någon av bussänd- hållplatserna i Västerås. Däremot räcker inte märkeffekten till hos en del av de transformatorer och nätstationer som ligger närmast den tänkta laddstationen. Investeringskalkylen visar att den lägsta årliga kosntaden, annuiteten, erhålls av att investera i nya transformatorstationer istället för att sänka effektuttaget med hjälp av ett batterilager. En bidragande orsak till detta är batteriernas antagna livslängd på 8 år jämfört med nätkomponenters 40-åriga livslängd.

Nätanslutningskostnaderna minimeras genom att optimera systemet, bestående av laddare, energilager och nätanslutningskomponenter (kablar och säkringar). Nätets kapacitet och storleken på energilagret väljs för minsta möjliga årliga kostnad. Detta görs genom linjärprogrammering i MATLAB på 4 olika platser med olika egenskaper, så som avstånd mellan laddstation och nätstation, bussfrekvenser och laddeffekter. De kostnader som minimeras är dels annuiteten av investeringen och dels de årliga avgifterna. Det visar sig att energilager i vissa fall kan minska kostnaderna för en lågspänningsanslutning då den stora investeringen i ett energilager vägs upp av de minskade årliga avgifterna. Den främsta bidragande faktorn som gör det ekonomiskt fördelaktigt är en låg bussfrekvens. Det lager som visar sig lönsamt är LTO-batteriet (litium-titanat), som klarar djupast urladdning och högst effekt av de studerade batterierna. Högspän- ninganslutning har dock lägst årlig kosntad i alla de studerade fallen, och det är inte kostnadseffektivt att investera i batterilager för att minska effektuttaget vid en sådan anslutning.

5 Teknisk ordlista balance responsible party: balansansvarig cable loadability: kabelbelastning current collector: strömavtagare electricity supplier: elhandlare feeder: matarkabel ﬂywheel: svänghjul grid concession: nätkosession harmonics: övertoner looped grid structure: maskat nät national grid: stamnät network operator: nätföretag pantograph: pantograf primary substation: fördelningsstation Transmission System Operator, TSO: Systemansvarig trolley bus: linjebus secondary substation: nätstation trigger condition: utlösningsvillkor type curve: typkurva

6 Contents

1 Introduction 12 1.1 Problem and aim of study ...... 12 1.1.1 Aim ...... 13 1.1.2 Limitations and assumptions ...... 14 1.2 Related studies and projects ...... 14 1.3 Structure of report ...... 15

2 Theory 16 2.1 The Swedish power system ...... 16 2.1.1 Actors on the electricity market ...... 16 2.1.2 Grid network ...... 16 2.1.3 Substations ...... 17 2.1.4 Power lines and cables ...... 18 2.2 Electric buses ...... 20 2.2.1 Energy supply and demand ...... 20 2.2.2 Charging of electric buses ...... 20 2.2.3 Grid connection ...... 23 2.2.4 Swedish examples ...... 25 2.3 Energy storage ...... 25 2.3.1 Applications and technologies ...... 25 2.3.2 Battery Energy Storage (BES) ...... 27

3 Method and data 30 3.1 Technical feasibility ...... 30 3.1.1 Electric bus system ...... 30 3.1.2 Evaluation of grid capacity ...... 31 3.1.3 Cable sizing ...... 31 3.1.4 Energy storage system ...... 32 3.2 Cost estimates ...... 33 3.3 Comparison of costs ...... 34 3.4 Optimization of annual grid connection cost ...... 34 3.4.1 Linear programming problem ...... 35 3.4.2 Parameters ...... 35

4 Results 39 4.1 Annual grid connection cost ...... 39 4.1.1 Hällagatan, Hälla ...... 39 4.1.2 Flisavägen, Bjurhovda ...... 44 4.1.3 Forntidsgatan, Bjurhovda ...... 46 4.1.4 Björnögården ...... 47 4.2 Grid owner investments ...... 49 4.2.1 Hälla ...... 51 4.2.2 Forntidsgatan, Bjurhovda ...... 52 4.2.3 Björnögården ...... 53

5 Discussion 54 5.1 Annual grid connection cost ...... 54

7 5.2 Suggested design approach ...... 56 5.3 Grid owner investments ...... 56 5.4 Criticism of the sources ...... 56 5.5 Criticism of the methods ...... 57 5.6 Suggested further studies ...... 57

6 Conclusions 58

List of Figures

1 Map of buss lines in Västerås 12

2 Structure of local electricity grid in Västerås 13

3 Network structures 17

4 Substation 18

5 Underground cable 18

6 Bus energy consumption 20

7 (a) Trolley bus conection (b) Catenary-free dynamic charging 22

8 (a) Hight power pantograph charging station. (b) Ground-based conductive fast charging station 22

9 Wireless charging station principle. 23

10 System without ESS 24

11 System layout with energy storage system. 24

12 Applications for energy storage systems 26

13 Charging characteristics of batteries 27

14 Available battery capacity for diﬀerent C-rates 27

15 Past and estimated future cost of li-ion batteries 29

16 Relationship between battery cycle-life and depth-of-discharge 29

17 Calculation of available capacity during normal feeding 31

18 Calculation of trigger condition 32

19 Suitable of energy storage technologies 33

20 Model with system parameters. 36

21 The substations at Hälla. 39

8 22 Annual cost for the Hälla station connection. 40

23 The expected power consumption from the potential charging station at Hälla. 41

24 Optimization of 5000 randomized loadproﬁles at Hälla, low-voltage, LTO. 42

25 The annual connection costs achieved by certain grid capacities and storage sizes at Hälla. 43

26 Battery sizes obtained when optimizing 5000 randomized load proﬁles with a ﬁxed grid capacity of 554 kW. 43

27 The substations at Bjurhovda. 44

28 The expected power consumption from the potential charging station at Bjurhovda. 45

29 Optimization of 5000 randomized load proﬁles at Flisavägen, low-voltage, LTO. 46

30 The substations at Björnön. 47

31 Optimal battery size in relation to battery cost. 48

32 The expected power consumption from the potential charging station at Björnögården. 49

33 Relationship between battery cycle-life and depth-of-discharge for LTO battery. 64

34 Sensitivity analysis Björnögården, LTO 68

35 Optimization of 5000 randomized load proﬁles at Björnögården, low-voltage, LTO. 68

36 Optimization of 5000 randomized load proﬁles at Björnögården, high-voltage, LTO. 68

37 Sensitivity analysis, Björnögården, LFP. 69

38 Optimization of 5000 randomized load proﬁles at Hälla, high-voltage, LTO. 69

39 Sensitivity analysis, Hälla, LFP. 69

40 Sensitivity analysis, Flisavägen, LTO. 70

41 Optimization of 5000 randomized load proﬁles at Flisavägen, low-voltage, LTO. 70

42 Sensitivity analysis, Flisavägen, LFP. 70

43 Sensitivity analysis, Forntidsgatan, LTO. 71

44 Optimization of 5000 randomized load proﬁles at Forntidsgatan, low-voltage, LTO. 71

45 Optimization of 5000 randomized load proﬁles at Forntidsgatan, high-voltage, LTO. 71

46 Sensitivity analysis, Forntidsgatan, LFP. 72

9 List of Tables

1 Fast charging stations for electric buses, operated in Sweden 25

2 Battery characteristics 28

3 Details about bus routes in the study 30

4 Battery model parameters 33

5 Optimization of the connection cost at the Hälla station. 39

6 Sensitivity analysis for LTO battery at Hälla. 42

7 Optimization of the connection cost at the Flisavägen, Bjurhovda station. 44

8 Optimization of the connection cost at the Forntidsgatan, Bjurhovda station. 46

9 Optimization of the connection cost at the Björnögården station. 47

10 Available capacity in primary substations. 50

11 Available capacity for connection at suitable secondary substations. 51

12 Transformer investments at the Hälla station. 52

13 Transformer investments at the Forntidsgatan, Bjurhovda station. 52

14 Transformer investments at the Björnögården station. 53

15 Normal values of cables, substations and other grid components as estimated by Ei. 63

16 Maximum cable loading. 63

17 Low-voltage connection prices. 64

18 High-voltage connection prices. 64

19 Flywheel characteristics. 65

20 SMES characteristics. 65

21 Capacitor and supercapacitor characteristics. 65

10 List of Symbols and Acronyms

APS Aesthic Power Supply BEB Battery Electric Bus BES Battery Energy Storage CAES Compressed Air Energy Storage CPT Capacitive Power Transfer DoD Depth-of-discharge EAC Equivalent Annual Cost Ei Swedish Energy Markets Inspectorate (Energimarknadsinspektionen) ERS Electric Road Systems EV Electric Vehicle FCEB Fuel Cell Electric Bus FES Flywheel Energy Storage HEB Hybrid Electric Bus LFP Lithium iron phosphate battery LTO Lithium titanate battery NPV Net Present Value PHS Pumped Hydroelectric Storage RIPT Resonant Inductive Power Transfer RPT Resonant Power Transfer SMES Superconducting Magnetic Energy Storage SRS technology by Alstom TSO Transmission System Operator WPT Wireless Power Transfer A Area (m2) CL Maximum power drawn from the grid E Energy EB Size of the energy storage I Current (A) φ Phase shift kESS Battery interest rate kg Grid interest rate L Lenght (m) n Lifetime η Eﬃciency Pc (t) Charging power of the storage Pd (t) Discharge power of the storage Pg (t) Power drawn from the grid Ploss Resistive power loss r rate of interest R Resistance ρ Resistivity () S Salvage value U Voltage YESS Battery life time Yg Grid life time Z Impedance

11 1 Introduction

In 2014, 54 % 1 of the world’s population lived in urban areas [1]. For Europe, the number was 73 % [1] and for Sweden 85 % (2010) [2]. The urbanization is expected to continue in all continents during the first half of the century and the urban residents are estimated to increase with 3 billion people between 2014 and 2050 [3]. Sweden is no exception from the trend and about 70 % of the country’s population increase is expected to take place in the three largest cities [4]. Stockholm county, with 2.2 million inhabitants (2016), grows with 35,000 new residents each year [5]. The increasing urbanization seen in the world puts strains on infrastructure as well as the environment [1, 5]. To decrease the traffic density and air pollution experienced in many urban areas, an efficient and sustainable public transport system is one important puzzle piece [6]. Electrification of buses shows promise to reduce the fossil fuel dependency of the transportation sector as well as create a healthier urban environment [7].

Electric buses are nothing new, but have been around for over 100 years in the shape of trolley buses [8]. In recent years, there has been a major development in battery electric buses that are charged either overnight in the depot or in fast charging stations at selected bus stops. In Sweden, several bus routes are being electriﬁed. Volvo, Siemens and Vattenfall together carry out the project ElectriCity in Gothenburg and since 2015 run a 7.5 km long bus route with electric and hybrid buses charged in high power charging stations at the end stops [9]. In Umeå, the company Hybricon has developed electric buses that charge in only three minutes and can run for about an hour [8]. Scania and Vattenfall are conducting trials with wireless charging of electric buses and in December of 2016 their ﬁrst buses were taken into operation in Södertälje [10].

1.1 Problem and aim of study In Västerås, Sweden, the local public transportation company Västmanlands Länstrafik is investigating the possibility to convert part of the bus fleet from biogas buses to battery electric buses. All seven urban bus lines, viewed in figure 1, are considered. The proposed concept is to charge the bus batteries at the end stations during idling, a strategy that requires high power fast charging stations.

Depending on the bus line, the scheduled time at the end station is 1-10 minutes and the bus frequency 2-8 buses/hour. The bus routes have one-way distances of 6-14 km and the estimated power demand is in the range 250-1000 Figure 1: Västerås with its seven urban bus lines that kW. all pass through the central station (Centralen) [11]. The distribution network operator in Västerås is Mälarenergi Elnät,which are the owners of the 10 kV and 400 V grid. The general structure of the local grid is presented in figure 2. It consists of medium- and low-voltage networks as well as primary and secondary substations. The main flow of power is from the overlying transmission grid via the primary substations and out to the customers and the end of the 400 V/230 V grid. The grid is dimensioned for a high power flow close to the primary substations but have

1based on various national deﬁnitions of urban area.

12 less capacity further away. The electric bus fast charging stations can be connected to the grid either on the 10 kV-side or on the 400 V-side of a secondary substation.

Figure 2: The local grid in Västerås is owned by Mälarenergi Elnät and consist of the 10 kV and the 400 V networks. Power from the overlying grid is transformed into medium-voltage level in the primary substations. It is distributed in the 10 kV grid that consists mainly of underground cables. In secondary substations the voltage is transformed to 3-phase 400 V and in the cable cabinets the phases, being 230 V each, are separated. Dotted lines illustrate customer owned feeders that connects the customers to the grid. They can be connected at diﬀerent voltage levels.

There is a limit to the amount of power you can input or output to a point in the grid, constrained by the required voltage quality and the thermal capacity of the grid components [12]. In addition, it is of impor- tance to fulﬁll electrical installation criteria. All these factors must be taken into account when designing a grid connection based on the estimated power demand. Every customer that connects to the electric grid pay the cost price of the connection as well as fees to the grid owner that are based on the subscribed power. Fast charging stations are expensive to connect to the grid due to the short and high power peaks that occur only when a bus is there to charge. Because of these load characteristics, the implementation of electric vehicles also gives rise to some concern about the load on the power distribution network [6]. If the power outtake exceeds the available grid capacity, costly reinforcements must be made by the grid owner.

An energy storage system is a promising solution to make fast charging stations more cost effective since it can decrease and even out its power demand [13]. A large storage can affect the cost both positively and negatively since it enables a weaker grid and lower fees but is costly in itself. Because of this, there is a trade-off between the size of the energy storage and the strength of the grid. For each system, there exists an ideal combination of storage and grid capacity that minimizes the costs for the charging station owner or the grid owner.

1.1.1 Aim The aim of this study is to determine whether an energy storage system connected to an electric bus fast charging station can decrease the grid connection costs for the charging station owner or grid reinforcement costs for the grid owner. In addition, the objective is to propose a design approach for the system that consists of the charging station, the energy storage and the grid connection components.

The study is conducted on the electric bus system that is considered in Västerås and four grid connection cases, with diﬀerent characteristics, are analyzed in more detail. In each case, the cost of the connection is evaluated in terms of the annuity and minimized by optimally sizing the energy storage system in relation to the grid components. Diﬀerent lithium-ion batteries are considered. The optimization is done by use of Integer linear programming in MATLAB.

13 1.1.2 Limitations and assumptions This study focuses only on the Västerås case, and the bus lines and substations that exist there. Only fast charging at the end stations is considered. It is assumed that there will be no changes to the present bus schedules nor the routes. The charging station design load proﬁle uses the weekday schedule and a bus energy consumption of 2.3 kWh/km (as estimated by VL).

In the investigation of potential grid reinforcements, only the design (normal) feeding mode as well as primary and secondary substations are considered. The available power is evaluated based on a worst case scenario. Costs considered are the investment costs of 10 kV- cables, transformers and substations.

When analyzing the grid connection, the costs taken into account are the investment costs of the energy storage and the grid connection cables as well as the fees that are payed by the customer to the grid owner. The cost of the charger and the bus is not considered. It is assumed that the price of electricity does not change enough with time for the yearly electricity cost to change if the consumption pattern changes.

It is assumed that the lifetime of the electric buses as well as the battery storage system is 8 years. The grid investment has an expected lifetime of 40 years, even though it is not certain that it will be used for the same purpose, or at all, during that whole time.

No regard has been taken to the question of ownership of the potential energy storage. Grid owners are prohibited from producing and trading electricity and there is a disagreement whether operating an energy storage falls into that category.

1.2 Related studies and projects In the recent years, several Swedish master’s thesis projects have been conducted that concerns electric buses. Zisimopoulos [14] investigates the electrification of internal buses at Arlanda and evaluates charging systems, costs and CO2 emissions. Lindberg [15] studies the power quality of the two fast charging stations in Umeå and concludes that the stations emit harmonics that might affect grid connected consumers nearby. Karlsson [16] evaluates the total cost of electrifying a whole bus system and compares various charging strategies. The thesis concludes that end-station fast charging combined with depot charging is most cost effective and that the grid connection cost is a main component of the total cost.

At Chalmers in Gothenburg a project is currently being conducted that aims to analyze the eﬀect that electric bus fast charging stations have on the distribution grid [17]. Energy storage solutions are being investigated as well as the possibility to use the charging stations to stabilize the grid voltage. Another Chalmers study, conducted by Grauers et. al. [18], evaluates the cost eﬀectiveness of various charging systems for electric buses. The study concludes that opportunity charging (fast charging during scheduled idle time) is the least costly option.

Fusco et. al. [6] has modeled average energy consumption of electric buses as a function of average speed during the route. The paper proposes a methodology for optimal design of a transit system that includes electric buses and charging stations. Ding et. al. [13] suggests an optimal control strategy for fast charging stations combined with energy storage systems as well as the optimal storage sizing. The article also evaluates how much the investment cost and the charging cost can be decreased by the use of a lithium-ion battery. In the study, the costs considered are the investment in cables, transformer and battery as well as the cost of the electricity, that varies substantially throughout the day. It is evaluated on load data from a real system where several buses are charged by the same charger. The conclusion of the study is that the two lithium based batteries LFP and LTO can decrease the costs associated with a fast charging

14 station, mostly due to the varying electricity price. The model in the study does not take into account the diﬀerence in lifetime between the grid components and the energy storage.

1.3 Structure of report The report is structured as follows. Section 2 presents the background theory necessary to understand the study and its results. It gives a general overview of the Swedish power system and also provides a more thorough description of the distribution grid and distribution grid planning. Furthermore, section 2 gives insight in the area of technology that is electric buses and go over possible charging strategies, present manufacturers and ongoing projects. Section 2 also describes various energy storage technologies and compare their characteristics.

In section 3, the general methods of the study are described and the data presented. In addition, the section describes the model that was created to optimize the system, consisting of the bus, the charger, the grid connection and the energy storage.

The results of the optimization are compiled in section 4, discussed in section 5 and in section 6 the conclusions drawn from the study are presented.

15 2 Theory

2.1 The Swedish power system 2.1.1 Actors on the electricity market The Nordic countries share a common electricity market that was deregulated in 1996 [19]. Players on the market are producers, consumers, suppliers, network operators, a Transmission System Operator as well as the authorities Swedish Energy Markets Inspectorate (Ei) and Swedish Energy Agency.

The Transmission System Operator (TSO) is Svenska Kraftnät, a state-owned authority that has the overall system responsibility. They own and operate the national grid, maintain power balance in the system and procures a power reserve before each winter [19].

Network operators own the grid and are responsible for the transport of electricity. There are about 160 network operators in Sweden and Mälarenergi Enlät AB is one of them [20]. Because of natural mo- nopolies there can be only one actor providing electric grid at each location. According to the electricity law(2013:207) 2 chap. §1, a network operator must have permission, so called grid concession, from Ei to build and operate a grid in a certain area [21]. To ensure a well-functioning market as well as reasonable prices, competition is simulated through rules and regulations managed by Ei [20]. As established in the electricity market reform in 1996, Swedish network operators are not allowed to produce or trade electricity other than to cover up for their grid losses or secure operation in case of faults (law(2011:712) 3 chap. §1) [21]. They are obliged to maintain a high power quality and make sure the right amount of power is delivered to the consumers despite losses in the grid (law(2005:1110) 3 chap. §9 [21]). Any producer or consumer that so wishes, must be connected to the local network, although the connection is payed for by the connecting actor (law(2005:404) 3 chap. §6) [22].

Electricity suppliers buy electricity, commonly on the market Nord Pool Spot, and sell it to their customers. As opposed to grid owners, they compete with each other, which gives the consumer the option to choose supplier company and deal. Every electricity supplier is obliged to, at every instant, deliver the same amount of power as their customers consume, which makes them the Balance responsible party. In case of imbalance, the TSO trades electricity on the balance market with short notice and charges the Balance responsible party that failed to keep the balance. This motivates all actors responsible for the balance to perform good estimates of their customer’s consumption [20].

Producers sell electricity directly to customers or to electricity suppliers on the spot market. They pay a fee to the network operator to connect to the grid and feed it with power. Consumers are charged for the used power and electricity both by the local network operator and the electricity supplier as well as pay electricity tax [20].

2.1.2 Grid network The electric grid consists of a high-voltage transmission system and a low-voltage distribution system. Traditionally, power is generated at large plants connected to the national grid, transported further through the regional grid and lastly distributed to consumers in the local low-voltage grid. With the implementation of renewable power production, such as solar and wind power, electricity is to a larger extent produced and connected on the consumer side of the grid [23].

The stem in the Swedish transmission network is the national grid that consists of AC power lines at 400 kV and 220 kV and stretches from north to south to connect the large producers with the consumer

16 areas [19]. HVDC cables link Sweden to neighboring countries Finland, Lithuania, Poland, Germany and Denmark [19]. The national grid connects to the local distribution network via regional grids with voltages of 20−130 kV [19]. The regional networks are mainly owned by Vattenfall, E.ON and Ellevio [24].

Locally, power is distributed to consumers through either medium-voltage networks (10-20 kV) or low-voltage networks (400/230 V) [23]. When faults occur in the power system it is most often in the local grids [19]. Networks can have either radial or looped structure, as illustrated in ﬁgure 3. A radial grid is the least costly network structure and the easiest to protect but in the event of failure in a line, all nodes connected behind the fault will be aﬀected [25]. This structure is mostly used on the countryside. Loop and multi-loop structures are used in urban areas [25]. They are more expensive to construct but have higher resilience since each point can be fed in several ways. During normal feeding, these networks are operated as radials but have the possibility to open or close loops so that the power can be alternatively fed in case of faults or maintenance on a line.

Figure 3: Network structures can be either radial, looped or multi-looped. The dots represents substations or consumers. Dotted lines mark where the loop can be closed with switches to enable an alternative operation [25]. (a) Radial network with single-point feeding. (b) Loop network with single-point feeding. (c) Multi-loop network with single-point feeding. (d) Multi-loop network with multiple-point feeding.

Distribution network planning involves planning long-term and short-term investments to meet demand changes or maintain quality as well as construction design of network structure, cables, power lines, transformers and other components. The main goal is to achieve safe and reliable power transfer to the lowest possible lifetime cost [26]. When major installations are made in a node, both the capacity of the normal feeding mode as well as the back-up feeding should be analyzed so that it is not exceeded.

The load patterns of various electricity customers can be described by a type curve that graphs the consumed power during a day as mean and standard deviation. Type curves are an important resource that aid in grid planning activities such as grid dimensioning, load forecasting, investments, reinforcement planning etc. A load forecasting model was developed by Svenska Elverksföreningen in the 90’s and although updated, it is still used today. The model is based on substantial measurements and covers many load types. Several type curves can be superimposed to create load behaviors closely linked to reality. Inputs to the model are degree-day, month, weekday/weekend, mean temperature (24h), yearly energy consumption and likelihood that the load does not overstep the forecast. For a more detailed description of the model, the reader is referred to [27].

2.1.3 Substations A substation is a node in the grid network where power lines can be divided and current or voltage levels changed. It is also where the system protection is located and where the current can be stopped. Substations

17 can be equipped with transformers, protective relays, breakers and disconnectors as well as meters and devises for reactive compensation [25]. Relays measure currents and voltages, detect abnormalities and control the breakers. A breaker stops the current, most commonly with the insu- lating SF6 − gas, while the disconnector physically sepa- rates two conductors as a visual conﬁrmation of the bro- ken current. Fuses and other surge protection devises protects the components from over-voltages [28]. Substations can be located in open air, when space is enough, or inside a metal enclosed construction isolated with SF6 − gas, when space is restricted [25]. Inside the substation incom- ing and outgoing feeders are connected to one or several Figure 4: Layout of a typical 10/0.4 kV common bus bars. Figure 4 depicts a typical substation lay- distribution substation in the Västerås grid. out.

2.1.4 Power lines and cables Over-head transmission lines and under-ground cables transport electricity from producers to consumers. Burying cables under ground increases the system reliability due to avoided exposure to weather, lightning, falling trees etc., but the investment is more expensive than equally rated over-head lines [25]. Power can be transferred either through direct current (DC) or alternating current (AC). A DC current uses the whole cross-section area of a conductor while an AC current, due to the skin effect, flows only on the conductor surface. This makes DC transfer more efficient [25]. Despite this, AC is dominating the distribution system.

Over-head lines generally uses light aluminum conductors combined with a steel core to improve the strength [25]. The transmission lines are hung on towers separated from each other and can be either uninsulated or insulated [29]. Since it is the cheapest method, it is the most common choice for long-distance power transfer [25]. However, over 97 % of the existing kilometers of low-voltage power conductors in Sweden are under-ground cables [23]. A cable and its components are illustrated in ﬁgure 5.

Figure 5: A cable consists of several layers, each with its special function. Conductors are made out of copper or aluminum. Copper has a lower resistivity than aluminum, but it is heavier and more expensive [25]. Copper is used for cross section areas of 0.5 - 2500 mm2 while aluminum only is preferred for areas of 50 mm2 and above [29]. To isolate the conductor either plastic or rubber is used. For high voltage cables, PEX-isolation is dominating. This is a cross linked polyethylene with thermal and mechanical characteristics very suitable for electric isolation applications [29]. Separated from the conductor with insulation is the concentric neutral conductor, made out of copper or aluminum wire or tape. To give the cable a circular cross section, a ﬁlling material is often used. As protection, several layers of plastic, sometimes with metal reinforcement, are added on the surface [29].

18 2.1.4.1 Cable selection The cable load capacity speciﬁes the maximum current or power a certain cable can transport and is limited by the temperature level the cable materials can withstand. When a current runs in a cable, the temperature rises due to heat power losses in the conductor. These losses are determined by the current and the resistance according to [28]: 2 Ploss = R · I (1) where Ploss is the resistive losses in the wire. The current depends on the transferred power and nominal voltage. To minimize the losses during high power transfer (large I) and long distances (large R) the voltage is increased.

The percentage voltage drop in a cable is described by equation 2. It is seen that it depends on the transmitted power (P), the resistance (R), the reactance (X) and phase shift (φ). The reactance can be neglected and the resistance described by the cable resistivity (ρ), length (L) and cross-section area (A). In a customer facility, the voltage drop should not exceed 4 % according to the Swedish electricity standardization Svensk elstandard SS 436 40 00 [30]. This requirement aﬀects the feasible cable geometry. √ √ ∆U 3 · I(Rcosφ + X sinφ) 3 · I · ρ · L · cosφ = ≈ (2) Unom Unom A · Unom

In addition to these two requirements, the cable must be short enough for the service fuse to release if there is an overcurrent. In case of a fault that creates a current higher than the fuse’s breaking current, the fuse releases and protects the circuit from thermal and mechanical stress. The short circuit current should be completely isolated within a speciﬁed time (often 5s). The let-through energy can be expressed as I2t, where I is the RMS short circuit current and t the breaking time [30]. This is however not a measure of the energy, but of a quantity that is proportional to the energy transmission. Each cable can withstand a certain level of high fault currents, expressed in k A2s, and the fuse must be chosen so that its speciﬁc let-through energy does not exceed the cable limits.

The high current regulations (Starkströmsföreskrifterna) states that a faulted facility must be discon- nected rapidly from the grid [30]. To meet these requirements both the fuses and the cables must be correctly dimensioned with respect to the highest as well as the lowest possible fault-current. It is the lowest fault current that limits cable length. The lowest fault current in directly earthed systems occurs when there is a 1-phase ground fault at the furthest distance from the fuse [30]. To ensure that the fuse breaks within its given time the short circuit current Is must be at least the size of the fuse’s breaking current Ib [30]:

Is ≥ k · Ib (3) k is a tolerance factor. This is called the trigger condition. The short circuit current is described by U I = (4) s z · L where, in the case of a 1-phase earth fault, U is the phase-to-neutral voltage and z equals the combined impedance of one phase and the cable neutral expressed in W/m. L is the distance from the fault to the fuse. To assure that the fuse releases as it should, the following must hold [30]: U U Ln = ≤ (5) Is · z k · Ib · z The above equation is obtained by combining equation 3 and 4 and assumes that the short circuit power at the start of the cable is inﬁnite. Usually it is important to take into account also the impedance at the

19 start, that consist of the impedances of the feeding grid (ZQ), the transformer (ZT ) and, if applicable, the feeder before the fuse (ZF). The maximum allowed cable length is thus described as

ZQ + ZT + ZF Lmax = Ln(1 − ) (6) Zmax

where Zmax equals the total cable impedance in W at length Ln [30].

2.2 Electric buses 2.2.1 Energy supply and demand Electric vehicles are driven by various types of traction motors, such as the brush-less DC motor, the switched reluctance motor and the induction motor [32]. The engine efficiency is around 25 % for regular combustion engines while electric engines can operate at efficiencies of 80-90 % [6]. The energy demand of an electric bus depends on many factors, such as speed, route distance, number of passengers (weight), temper- Figure 6: The energy demand of electric buses de- ature, topography, road quality and driver be- pend on factors such as climate, speed and topog- havior [31]. As shown in figure 6, the raphy. The graphics illustrates a consumption esti- consumption varies between 0.8 kWh/km in mation made by Volvo, where the electric energy use the best case to 2.82 kWh/km in the worst in best case is 0.8 kWh/km and in worst case 2.82 case. kWh/km [31].

The diﬀerence between the various types of electric buses (grid bounded, hybrid, fuel cell and battery electric buses) is the electricity sources they use to power their motors [33]. Battery Electric Buses (BEB) can be equipped with smaller batteries that are fully charged in 5-10 minutes or larger batteries that charges over-night and lasts throughout the day [33]. Range is a limiting factor for electric vehicles since storing energy in large long-lasting batteries increases the weight of the vehicle substantially [6]. Battery types used in EV:s today are Lead-acid, Ni-Fe, Ni-Cd, NiMH (Nickel-Metal hydride), Sodium-metal chloride, Na-S and various Lithium based [32].

A hybrid bus commonly combines an electric motor with a conventional internal combustion engine (ICE). If the engines are connected in parallel the traction power can be delivered from both engines simultaneously, or either of them separately. When series connection is used, the ICE functions as a generator that provides electricity to the EM, sometimes via a battery [32]. Plug-in hybrid vehicles have series connected motors, but also the ability to charge the battery through an external source, thus enabling fully electric operation [33].

2.2.2 Charging of electric buses Charging can take place either while the vehicle is moving or when it is at rest. Furthermore, energy can be supplied to electric vehicles by means of conduction or by wireless coupling (Wireless power transfer, WPT). Four main charging technologies can thus be identiﬁed; static conductive, dynamic conductive, static wireless and dynamic wireless.

20 International standards for electric bus charging are in the making and expected to be ﬁnalized by ISO/IEC in 2020 but presently a broad variety of solutions can be seen throughout the world [34]. Because of this uncertainty, bus manufacturers commonly produce buses that allows for the customer to specify either conductive or wireless charging systems rather than focusing on one speciﬁc technology [35]. Sev- eral European electric bus manufacturers (Irizar, Solaris, VDL and Volvo) are cooperating with charging system developers (ABB, Siemens and Heliox) around a common charging interface [34].

Electric Road Systems (ERS) are roads that dynamically provides vehicles with power [36]. This dynamic charging is a strategy that secures the range of an EV without relying on large energy storage systems [36]. However, this type of charging requires a lot of infrastructure. Static and dynamic charging can be combined by letting the vehicle drive outside the ERS on a combustion engine (hybrid vehicles) or on electricity stored in batteries (fully electric vehicles) [36].

In cases where the bus is to be exclusively charged statically, there are several options on when to charge. For city buses, opportunity charging has been identiﬁed as a suitable operational strategy [13, 37, 18]. It entails charging the bus during its scheduled idle time at a few stations along the route (usually end stations). Frequent charging allows for a smaller battery to be used but it also requires high power, which increases the price of the charger [38, 6, 39]. The alternative to opportunity charging would be slow charging overnight of a large, long-lasting battery, fast charging at every bus stop along the route of a small battery or battery swapping one or a few times a day [39]. A comparison made by Grauers et. al. [18] shows that opportunity charging at end stations have a lower total cost than night charging and bus stop charging (cost of battery, charger and electricity included).

A few other charging strategies has been proposed, for example charging fast and very frequent though built-in structures on the road while storing the energy in super capacitors [40]. Musavi et. al. [38] recommends a solution for public transport that consists of a few fast DC charging stations combined with wireless chargers at bus stops or traﬃc lights. The choice of charging strategy depends on the route distance as well as on project economy and available charing station area. For a more detailed analysis of diﬀerent charging methods the reader is referred to [39] and [18].

2.2.2.1 Conductive charging During conductive charging energy is transferred to the vehicle from a voltage source through an electric conductor. Dynamic conductive charging through overhead lines is a well-established technology used for trains, trams and trolley buses. Electric trolley buses draw a current from overhead wires through trolley poles as seen in Figure 7a [7]. The poles are dragged behind the vehicle and allow for lateral and vertical movement, although disconnection sometimes occurs in sharp turns [41]. In their project eHighway, Siemens together with Scania has developed an ERS concept for trucks connected to over-head catenary wires that allows for higher speed than regular trolley buses [42]. Advantages of trolley buses include low noise, no emissions, easy maintenance, similarity to diesel buses as well as the possibility to operate on existing infrastructure [7].

In order to avoid the visual impact from overhead wires, solutions for ground-based charging systems has been developed. Alstom is the largest supplier of catenary-free charging systems for trams. Their Aesthetic Power Supply (APS) technology includes a third middle rail that provides electricity through several current collector shoes mounted at the bottom of the tram [43]. Alstom and Volvo are both participating in a project to implement the APS technology in an ERS that can power all sorts of vehicles [36], see Figure 7b. Ground-based charging systems have the advantages of easy extension of the lines and no overhead-wires but electric rails on the road might aﬀect the safety of humans and animals due to changed driver behavior, road friction and magnetic ﬁelds [43, 36].

21 (a) (b)

Figure 7: (a) Electric buses connected through trolley poles are seen all over the world. This particular one is operated in Vancouver, Canada. The overhead wire has two lines; one with a voltage of around 600-700 VDC and one at ground potential [41]. This is required since the vehicle is rubber tired and thus not grounded. The control system of the trolley poles enables automatic connection to the catenary [7]. The connecting material in the trolley shoe is usually carbon-based, such as graphite [44]. Photograph by Steve Morgan [45]. (b) Pilot ERS that uses APS technology developed by Alstom and trucks with conductive pick-ups constructed by Volvo GTT. The truck is provided 750 VDC from ground-based rails through the collector shoe at the rear of the vehicle [36]. Image from Volvo [46].

A pantograph is a current collect- ing devise traditionally used to power trains and trams. Today, the pantograph has been reused in static conductive fast charging stations for electrical buses, as shown in ﬁgure 8a. Com- panies that develop this technology are ABB, Hybricon, Siemens and Proterra, amongst others. The power provided by these stations is in the range of 150- (a) (b) 1000 kW [49, 50, 51]. Both ABB and Figure 8: (a) Station for high power opportunity-charging, Siemens provide charging stations of 150 constructed by ABB. The system consists of a current col- kW, 300 kW and 450kW DC, which en- lector, a pantograph, that automatically connects to con- ables a charging time of 4-6 minutes tacts at the bus roof to provide the battery with 150 kw, for a regular city bus [47, 50]. The 300 kW or 450 kW DC [47]. The utility AC power must pantograph can be placed either on the be rectiﬁed at the charging station. Image from ABB [47]. roof of the bus or at the station (re- (b) Illustration of the SRS technology, a conductive ground- versed pantograph). A pantograph at based fast charging station developed by Alstom. The bus each vehicle increases the system resilience is supposed to charge in a few minutes while idling at a bus but it adds weight and cost to the bus stop. Image from Alstom [48]. [47].

In addition to the APS system, Alstom has also developed a static conductive ground-based fast charging system for electric vehicles called SRS. The technology is very similar to APS but the idea is for trams and buses to charge while idling at bus stops [48]. The charging concept is viewed in Figure 8b.

2.2.2.2 Wireless charging Wireless power transfer can be divided into two categories; Inductive power transfer (IPT) and Resonant power transfer (RPT) [52]. The two technologies are similar since they are both based on electromagnetic coupling. Coupling can also be achieved using capacitors (Capacitive power transfer, CPT) but this solution is only suitable at short distances [38]. For a more thorough review of diﬀerent wireless charging

22 technologies the reader is referred to [38].

In a wireless charging station, like the one outlined in figure 9, energy is transfered in the electromagnetic field between a coil buried under ground, the track, and another coil in the vehicle, the pickup-coil [53]. In order to achieve efficient energy transfer an AC current of high frequency is required (80-500 kHz) [35]. This is obtained by the use of high frequency inverters at the charging station. Power electronic devises in the vehicle converts the AC current to DC before charging the battery, as seen in figure 9.

Figure 9: In a wireless charging station AC power from the distribution grid is converted to a higher frequency before being transmitted from the connector under ground to the pick-up coil inside the vehicle. In the vehicle the high frequency AC power is rectiﬁed and the battery charged. Controls in the charging station as well as in the vehicle ensures the battery is fully charged.

Wireless charging poses many advantages over conventional conductive charging; it is convenient for the user, there are no issues with charging in wet weather and the size and weight of the charger can be reduced [38]. Other advantages of inductive charging are the low visual impact as well as the possibility to use the same standard for all types of vehicles [35]. The grid interaction is a major drawback as well as the cost and safety issues concerning human exposure to high frequency radiation [35]. In addition, the power transfer eﬃciency is sensitive to misalignment [53]

Several pilot projects with static inductive charging of buses is or has been conducted; Scania (Sweden, 2016), Flaunder DRIVE (Belgium, 2011), City of Den Bosch (Netherlands, 2012), Bombardier (Germany, 2013), Dong Won Olev (South Korea, 2013) and Wrightbus (UK, 2014) to mention a few [9, 35]. As of 2014 there were seven companies providing inductive charging systems worldwide, Bombardier and Conductix-Wampﬂer being the only two with solutions for buses. Examples of companies producing buses with inductive charging systems are VCL (Netherlands), BYD (China), VanHool (Belgium) and Solaris (Poland) [35].

2.2.3 Grid connection The grid connection is an important diﬀerence between conductive and inductive charging stations. While regular conductive charging points are located at the grid connection point, inductive charging points are separated from the grid connecting point since the coils are placed under ground [35]. Underground grid connection is being investigated to avoid separate installation [35].

Loads that use power electronics, such as chargers for electric buses, have a dynamic behavior. The internal control systems in the power electronic devises will make sure a constant power is supplied to the charger, which leads to increased current if the voltage drops. Locations in the grid with a lot of power electronics therefore have a higher risk of developing resonance issues. [54]. Lindberg [15] concludes that the fast charging stations for electric buses in Umeå emits harmonics that might aﬀect the voltage quality for nearby customers.

A simplified image of the grid connection of a reversed pantograph fast charging station is shown in figure 10. The system consists of the primary substation, the 10/0.4 kV substation, service cables, the charging station with its rectifier and pantograph and the bus containing a battery. In addition, there are

23 systems for safety, control and communication between bus and charger. The input to the fast charger should be 3-phase 400 VAC and the output a DC voltage of 400-850 V.

The charging station owner can be either a high-voltage or a low voltage-customer, depending on if the connection point is 10 kV or 400 V, respectively. At the connection point, the ownership of the grid shifts from being the network operator’s to being the connecting customer’s. In a low voltage connection, the customer is responsible for the facility itself and the 400 V service. In a high voltage connection, on the other hand, the customer is also the owner of a 10/0.4 kV substation and a connecting 10 kV-cable in addition to a 400 V service. The connection fees to the network operator are diﬀerent, depending on the connection voltage. They include the cost price of the necessary cables, a starting fee that depends on the subscribed current or power as well as monthly and yearly power and energy transfer fees.

Figure 10: The system, that consists of a primary and a secondary substation, the service cables, the fast charger and the bus as well as control system, safety system and wireless communication. Input to the charger is 400 VAC and output is 400-850 VDC.

An energy storage system can be connected to the charging station as shown in ﬁgure 11. The idea of using an energy storage is to decrease the power demand from the buses. This is done by charging the storage when no bus is at the station, and later, when a bus arrives, help provide charge power. This way, the energy outtake from the grid is spread out over a longer time, which decreases the required power. The storage can be sized to provide the full power demand or only a portion. It can be designed to recharge fully in between each bus or make it so large that it does not have to recharge fully during the busiest hours.

Figure 11: The system layout with an energy storage system connected to the fast charging station.

24 2.2.4 Swedish examples In Sweden, there are at present four diﬀerent bus lines that are operated with opportunity charging. Fast charging stations are not owned or managed by the bus companies. Instead the charging service is procured by the municipality or local public transport authority and the stations owned and operated by a charging station operator. Table 1 below summarizes the opportunity charged Swedish bus lines.

Table 1: A summary of Swedish bus lines operated electrically with fast chargers at end stops. Most of the information was gathered through interviews with grid companies, charging suppliers and charging station operators.

Location Operator: Supplier: Charging Voltage: Power Comment network/ charger/ technology input/output (kW) charging bus (V) station Gothenburg Göteborg Siemens/ Static conduc- 400/ 600 2x120 All fed from previously existing distribu- Energi/? Volvo tive, reversed and tion substations. One station shares service pantograph 2x300 with other consumers, the others have their own. [55] Umeå Umeå Hybricon/ Static conduc- 400 / 700 300 The 300 kW station has its own transformer Energi/ Hybricon tive, reversed and in a shared substation and is combined with Hybricon pantograph 650 a BESS of 120 kWh to decrease the load on the weak grid. The 650 kW station is fed by its own substation. [15, 56] Södertälje Vattenfall/ Bombardier/ Static induc- ?/? 200 The bus line is a research project in coop- Vattenfall Scania tive, ground eration with KTH and was implemented in based december 2016 [10]. Stockholm, Vattenfall/ Siemens/ Static conduc- 400/ 600 150 The bus line is evaluated between 2015 and Ropsten Vattenfall Volvo tive, reversed 2017 [57]. pantograph

2.3 Energy storage 2.3.1 Applications and technologies The following grid beneﬁts from energy storage has been identiﬁed:

• Balance the capacity Energy storage can be used to cover the few short periods when line capacity is exceeded, as an alternative to reinforcement of the grid [58].

• Level out load To even out the load and relieve the grid, energy storage can be charged from the grid when the load is low and help meet the demand when it is high [54].

• Improve voltage quality Energy storage can help mitigate harmonics, ﬂicker, voltage oscillations, voltage drops and other voltage quality issues [54].

• Balance production from intermittent sources. [54]

• Increase hosting capacity The hosting capacity is a measurement of the amount of power from renewable resources that can be inputed to the grid. It is determined by evaluating various limiting factors such as grid thermal capacity and voltage drop. Energy storage can help increasing the level of renewables in the grid by improving its characteristics [54].

25 • Participate in frequency regulation The purpose of frequency regulation is to make sure the system frequency is kept at 50 Hz by instantaneously matching production and consumption. Since energy storage systems can be both producers and consumers they can assist in regulating the frequency [54].

• Back-up power Back-up energy storage increases the resilience in the grid [54].

• Minimize losses In each energy storage system there are internal losses, but energy storage can partially compensate these losses by reducing the grid losses that are due to variations in the transmitted power [54].

• Decrease grid fees A network operator can decrease its fees to superjacent grid owners by reducing grid losses and evening out the power outtake. Consumers can reduce their fees by decreasing their power consumption. This can be achieved by applying energy storage in the grid [59].

Various applications for energy storage are presented in figure 12 according to their respective time scale. The application determines the required time frame, power and energy rating, life-time etc. and thus the energy storage technology. According to a study conducted by Ei, the profitability of energy storage for network operators strongly depends on the amount of system benefits the storage system has as well as the alternative investments that are avoided [60].

Figure 12: The image collected from Elforsk [54] points out various grid issues and energy storage applications. The logarithmic time scale indicates within what time frame each grid phenomenon or application take place.

Energy can be stored using a large variety of methods, classiﬁed according to the following [61, 62]:

• Electrochemical: Batteries

• Mechanical: Pumped Hydroelectric Storage, Compressed Air Energy Storage, Flywheels

• Electric: Superconducting Magnetic Energy Storage, Capacitors and Supercapacitors

• Chemical: Hydrogen and other fuels

• Thermal: Low temperature thermal storage, High temperature thermal storage Chemical and thermal storage will not be further considered in this work. Thermal storage has few power system applications and chemical storage is primarily suitable for long term storage [61]. Batteries will be described detail since they are the most common energy storage devices [62] and already are combined with EV charging stations. Characteristics of the remaining energy storage technologies are found in Appendix A5.

26 2.3.2 Battery Energy Storage (BES) A battery has the ability to perform conversion between electrical energy and chemical energy through redox reactions at the electrode/ electrolyte interface [63]. The battery cell consists of two electrodes, the anode and the cathode, separated by an ionic solution, the electrolyte. When the battery is discharged, electrons flow from the anode to the cathode via a load while positively charged ions flow from the anode to the cathode through the electrolyte [62]. The voltage between the two terminals of a battery, when no current flows, is denoted open-circuit voltage (OCV) and it is the chemical potential difference between the two electrodes. When a current is drawn from the battery the voltage between the terminals is called closed-circuit voltage or terminal voltage, and it varies during the discharging process. Every battery has an internal resistance to current flow [63].

2.3.2.1 Battery charging characteristics A primary battery is discharged once and then disposed of whereas a secondary battery can be charged again by applying a current in the oppo- site direction [63]. The charing characteristics of a lithium-ion battery is shown in ﬁgure 13. The process of ﬁrst charging and then discharging an energy storage is called cycling. The state-of-charge (SOC) is a measure of how many percent of the total capacity a battery contains at the moment. Figure 13: The image shows the charging process 2.3.2.2 Battery capacity of a lithium-ion battery [64]. The current stays con- The battery capacity is measured in Ampere-hours stant until the nominal voltage is reached, and then (Ah) and indicates the amount of charge that is decreases exponentially. stored. It can be described by Peukerts law [61]

k Capacity = I · td (7) where the discharge current I is assumed to be constant throughout the whole course, and the discharge time td is expressed in hours. k is the Peukert constant, that is 1 for an ideal battery. The rate, at which the battery is discharged (and charged), may vary. It can be related to the maximum battery capacity by the C-rate. At 1C, the current required to discharge the full capacity in an hour is used. At 2C the current is doubled and at 0.5C the current is halved. In an ideal battery, the discharge time Figure 14: Depending on the C-rate during dis- would according to equation 7 be 1/C −rate hours. charge, the battery delivers diﬀerent capacities. The However, that is not the case. The bigger the C- larger the C-rate (and thus the discharge current), rate, the smaller the available battery capacity, as the smaller the available capacity. The image shows illustrated in ﬁgure 14. the discharge characteristics of a Kokam 17-Ah/3.7-V lithium-ion battery [61]. 2.3.2.3 Battery chemistries Characteristics for several common batteries are presented in table 2. Lead-acid is the most used battery chemistry and also the cheapest available [61]. Batteries in the lithium-ion family (for example lithium

27 iron phosphate, LFP, and lithium titanate, LTO) all have high energy as well as power densities and are thus favored in portable and vehicle applications. The NaS battery has the highest rated capacity out of all batteries. The materials are common and non-toxic, but require a high temperature (575-624 K) and is therefore expensive to operate [62]. Although NiCd batteries are robust and cheap to operate and maintain, the compounds are toxic. Also, the capacity of the NiCd battery is reduced substantially if repeatedly recharged without being fully discharged (so called memory eﬀect) [62]. Less common battery chemistries used in vehicle applications are Nickel-metalhydride (NiMH) and sodium-nickel chloride (ZEBRA) [61].

Flow batteries differ from regular batteries in the sense that the energy is stored in the electrolytes instead of the electrodes. The electrolyte solutions are pumped to and from flow compartments and are oxidized and reduced at the electrodes [62]. Common flow batteries include vanadium-redox flow batteries (VRB), zinc-bromine (ZnBr) and polysulfide-bromine (PSB). Also flow battery characteristics are found in table 2.

Table 2: Characteristics for common batteries. The best performing battery for each category is marked in bold. The cycle life implies 100 % DoD. When nothing else is noted, the numbers are collected from a review by Lou et.al. [62] and the conversion 1 SEK = 8.5 USD is used.

Chem. Density Power Energy Eﬃciency Life-time Self- Discharge Cost (Wh/L; rating rating (cycle; charge; (cycle; years) discharge time @ (Invest W/L) (MW) (MWh) discharge) (%/day) rated SEK/kWh; Oper. power SEK/kW/y) Lead- 50-90; 0.05-40 0.0005- 63-90; 85; 85 500-1800; 5-15 0.1-0.3 seconds - 425-3,400;425 acid 10-400 40 hours Li-ion 150-500; 0.1-100 0.004- 75-90;85; 85 1000-20,000;5- 0.1-5 minutes - 5,100-32,300 1,500- 10 15 hours (3,485 [65]); - 10,000 NaS 150-300; <34 0.4- 75-90;85;85 2500-4500; 10- 0 seconds - 2,550-4,250;680 140-180 244.8 20 hours NiCd 60-150; <40 6.75 60-85;85;85 2000-3500;3-20 0.03-0.6 seconds - 3,400-20,400; 20 80-600 hours VRB 16-35; 0.03-3 <60 65-85; - ;75-82 12,000+; 5-20 small seconds - 1,275-8,500; 595 <2 24+ h ZnBr 30-65; 0.05-10 0.05-4 65-80; - ;60-70 1500-2000+;5- small seconds - 1,275-8,500; - <25 10 10+ h PSB 20-30; 0.004- <0.06 60-75; - ; - - ;10-15 0 seconds - 1,275-8,500; - <2 15 10+ h

Battery storage systems have a broad variety of applications, such as power quality improvement, peak shaving, energy management, back-up power and transportation [62]. Applications most suited for batteries have discharge times from minutes to hours [54]. Flow batteries typically operate as daily storage, with longer discharge times than regular batteries [61]. It is important to notice that each battery chemistry has its own characteristics and therefore are suited for its speciﬁc applications.

2.3.2.4 Lithium-ion battery cost A review by Nykvist and Nilsson [65] shows li-ion battery cost has decreased by 14 % each year between 2007-2014. According to the market study, the price was around 410 USD/kWh in 2014. Figure 15 shows past as well as estimated future cost of li-ion batteries (all diﬀerent types).

28 Figure 15: The graph illustrates the cost development of li-ion batteries for BEV applications, based on a review of publications, journals, reports, the market trends, expert statements and manufacturer’s estimates [65]. 150 USD/kWh is considered the point of commercialization of BEV.

2.3.2.5 Battery aging A battery’s aging is determined by operating and storing temperature, depth-of- discharge (DoD), number of cycles and the charge/discharge current. High temperature, deep discharge, a large number of cycles and a high discharge current all contribute to capacity fading and decrease of battery life [67]. The DoD is defined as the amount (in percent) of the total battery capacity that has been discharged by the time charging starts again. At 100 % DoD, the battery is completely emptied at every discharge. Figure 16 illustrates the relationship between the DoD and the number of cycles a lithium- Figure 16: The figure illustrates the relationship between cycle- ion battery can perform before 20 % of life and depth-of-discharge for a typical lithium-ion battery [66]. its capacity is lost. It is in accordance The number of cycles indicates how many cycles the battery can with similar graphs presented in [18] and perform before the capacity is decreased to 80 % of the original. [68]. Shallow charge cycles significantly increases the battery life. .

29 3 Method and data

When performing a distribution system design assessment, Lakervi and Holmes [26] suggests the following three main tasks, that are the basis for the execution of this study:

• Determination of a technically feasible solution.

• Estimation of cost per unit for all components.

• Conversion of costs to make them comparable.

3.1 Technical feasibility 3.1.1 Electric bus system The public transportation company VL has provided information on the following design parameters: maximum bus energy consumption, bus frequencies, time at the end stations, total drive time on the routes and route distances (table 3). The power and energy requirement at each end station is based on the route distance and the scheduled stops as well as the energy consumption for the buses. Each time the bus arrives to the charging station it is assumed to require the amount of energy it consumes during the route (one way). This is calculated through equation 8 where k is the energy demand in kWh/km and l the route distance in kilometers.

E = k · l (8) VL estimates the dimensioning energy demand to be 1.6 kWh/km and 2.3 kWh/km for a 12 m and a 18 m bus, respectively. In this study, the ﬁgure that refers to the largest bus type is used. It is assumed that the charging eﬃciency of the bus battery is 85 %. Table 3 lists the demanded charging power that is based on the charge energy and scheduled time at the end station.

Table 3: The table shows the power demand during one charge for each bus (18 m) as well as route characteristics.

Bus End station Distance Total route Bus frequency Time at end Required power (m) time (min) (buses/hour) station (min) (kW) 1 Bjurhovda 12765 44 8 6 345 Skälby 12727 2 1032 2 Björnön 14108 44 5 4 573 NorraGryta 14019 6 379 3 Erikslund 13930 45 6 10 226 Airport 14293 8 291 4 Brottberga 12161 39 3.5 4 494 Finnslätten 12264 7 285 5 Tunbytorp 12815 40 4 6 347 Hälla 12848 3 695 6 Rönnby 11920 36 3 7 276 Finnslätten 11876 10 285 7 Centralen 6006 14 2 1 975 Hacksta 6018 1 976

30 Line 1 and 7 (Skälby and Hacksta) require very high power to charge in 2 and 1 minute, respectively. Ultrafast charging of up to 1000 kW is being developed, by for example Hybricon, but another option to decrease the needed power is however to also charge these buses at the central station and thus decrease the distance and the energy requirement at each charge. This option has not been further studied.

3.1.2 Evaluation of grid capacity Based on type curves (see section 2.1.2), data is collected on the highest transformer load factor that occurs throughout a whole year in each substation in Mälarenergi’s grid. Knowledge of the transformer ratings gives the maximum power consumption in each substation. As explained in ﬁgure 17, the available capacity in each cable during normal feeding is calculated using the maximum power outtake from every substation as well as the cable loadability given in Appendix A2.

3.1.3 Cable sizing Figure 17: The image shows a section of the Västerås city grid. The orange circles mark substations close As described in section 2.1.4.1, the ca- to the Bjurhovda end-stop for bus line 1. They are bles must be sized with respect to ther- both fed by primary substation ÖM. During normal mal capacity, voltage drop and trigger con- feeding, seven other substations also get their power dition. The optimal choice is the cheap- from the same exiting feeder which implies it must be est cable that fulfills all the criteria. Eight able to carry the power demanded by all nine stations. cable choices are considered; 1, 2, 3 or 4 Figures in red denotes the maximum power demand Al 240 mm2 and 1, 2, 3 or 4 Al 150 from each substation. Cable capacities used can be mm2. For each cable distance between the found in Appendix A2. The figures in blue represents charging stations and the substations and for the available capacity which is the difference between each of the eight cable choices, the maxi- the cable capacity and the total power demand from mum power that can be transported is de- all substations further along the line. termined based on thermal capacity, voltage drop requirements and the trigger condition.

The thermal capacity limit is determined based on the data in Appendix A2. The maximum power that can be transported in order for the voltage drop to be less than 4 % is calculated from equation 2. The maximum power with regards to the trigger condition is evaluated using the program Elvis, that uses the theory presented in section 2.1.4.1 as well as tabulated values from the Swedish Electricity Standard [30]. For each cable choice, the program calculates the maximum cable length that can be used in order for a certain set of fuses to break within 5 seconds. Fuses come in the sizes 80, 125, 160, 200, 250, 315, 400, 500, 630 and 800 A, the figures indicating the highest current that can possibly run in the cable without triggering the fuse. As seen in figure 18a, there is a fuse on each cable. Close to the facility are the fuses with the lower breaking current (service fuse), and close to the substation, the fuses with the higher rating. In order to determine the maximum allowed power in a cable of a certain length, tables like in figure 18b is created using Elvis. It lists the longest cable distances for each fuse pair and each cable choice. To evaluate a cable choice of a certain distance, the distance in the table that is closest above the one in question determines the largest fuse that can be used and thus, the largest current and power.

31 (a)

(b)

Figure 18: (a) The image is an excerpt from the program Elvis and shows the service with smaller fuses close to the facility and larger fuses close to the substation transformer. The program allows the user to specify the transformer characteristics, the type of cables and the types of fuses and then calculates the maximum allowed cable distance in order for the fuse to release within given time (here 5s). (b) The table is used to evaluate the maximum power that can be transported in the various cables, for a given transformer (in this case one 800 kVA) and length. For example, for two 240 mm2 cables of 300 m, the largest fuse pair that can be used is 160/200 A which enables a total of 320 A to be transported (222 kW). It is created using Elvis. The x note that the values does not exist in the tables in the Swedish Electricity Standard (SEK), that the program is based on.

3.1.4 Energy storage system Several factors determine the suitable energy storage technologies. Since the application is stationary and all end-stations are considered spacious, the energy and power density is not considered important but only the energy and power rating. The power demand from the buses is in the span 226-1032 kW. If the storage is dimensioned to provide 30-100 % of the power demand it must be in the approximate range 70-1000 kW. The needed capacity is likely to be within the range 10 kWh - 1 MWh. The area of interest is marked in the graph of figure 19 and shows that the energy storage technologies with suitable characteristics are batteries (lithium-ion, lead-acid and potentially NaS), flow batteries (VRB, ZnBr) and flywheels.

However, another requirement is the cycle life. It is assumed that the number of energy storage charge cycles equals the number of bus charges, which is approximately in the range 30-120 in a weekday (route 7 and 1 respectively). In order for the storage system to last 8 years (life time of the bus and the charging system), it must be able to withstand 87,600-350,400 cycles. Out of the technologies of interest, this requirement can only be met by lithium-ion batteries (at approx. 3-20 % DoD) and ﬂywheels, according to the review in section 2.3.2. This study will focus on lithium-ion batteries, because it is a mature technology with a rapidly decreasing cost. Two diﬀerent types of lithium-ion batteries are investigated; lithium-iron-phosphate battery (LFP) and lithium-titanate battery (LTO). These types are common in vehicle applications. Table 4 lists their respective characteristics.

32 Figure 19: The image shows power rating and energy capacity of a large variety of energy storage technologies. The red square marks the area of interest for electric bus fast charging applications. The image is collected from the review by Luo etl. al. [62].

Table 4: Battery model parameters used in simulations for a lithium-iron-phosphate battery (LFP) and a lithium-titanate battery (LTO). The LTO- battery enables a slightly deeper discharge and higher C-rate than other lithium-ion batteries but it is about 3 times more expensive [62]. LTO is often the chemistry of choice for fast charging [18] and is used for example in the Umeå electric buses as well as the fast charging station [56]. The life time is set to 8 years (same as bus and charging station) and, depending on the number of charges a day (=cycles) for a speciﬁc bus route, the DoD is collected from ﬁgure 16 as well as the the graph in Appendix A4.

Battery Life Cycle-life DoD Max C-rate Eﬃciency time (cycles) (%) for 20 charge level charge/ ηc/ηd (years) % Ah loss in 8 yr (%) discharge (%) LiFePO4 8 no.o f charges/week· ﬁgure 16 93 2C/2C [62] 85/85 (LFP) 52 · 8 [62] Li4Ti5O12 8 no.o f charges/day· Appendix A4 91 [56] 6C/6C [69] 85/85 (LTO) 365 · 8 [62]

3.2 Cost estimates Standard values of grid component costs are determined by Ei and collected in a list called Normvärdeslis- tan [70], see Appendix A1. All costs are based on industry averages. The purpose of these costs is to determine how much a grid owner can reasonably charge their customers for a grid connection. These costs have been used for all cables, substations and transformers in the study. The cable price includes the installation. A rule of thumb is that the price of a cable installation increases with times 0.3 for each added cable. This is because the excavation is the most expensive part, not the cable itself. The grid connection fees at Mälarenergi Elnät are presented in Appendix A3.

33 The price of the LFP battery is set to 3500 SEK (410 $/kWh) (from the general market evaluation of lithium-ion batteries as a whole [65]) and the price on LTO batteries to 8500 SEK [13]. It is assumed that the converter and control system of the charging station is used also for the energy storage and thus, this is not included in the cost.

3.3 Comparison of costs The costs associated with an investment are evaluated using the Equivalent Annual Cost (EAC) method, that calculates the cost per year during the investment life time. This allows for comparison of investments with different life time. The EAC is calculated according to the following [71]: (N PV − S) · r E AC = (9) (1 + r)−n − 1 N PV is the Net Present Value, or the initial investment cost. r is the rate of interest which according to Ei should be 4.55 % for grid investments [72]. Since investments in energy storage can be considered notably more risky, the interest rate used in this case is 8 %. n is the investment life time in years. The assumed life time of grid components (such as cables and transformers) is generally 40 years, while the life time for energy storage is much shorter and depends on many factors. It is treated in section 2.3 and specifically for batteries in section 2.3.2.5. S is called the salvage value and is the remaining value of the investment after its life time is over. Batteries are the only components considered in this study to have a salvage value. This is because it is very common to define the battery life time as the time it takes for the capacity to decrease by 20 %. That implies that 80 % of the charge capacity still is intact after the life time is over and that the battery can be repurposed and sold. The future repurposed battery price is assumed to be 40 USD/kWh (=340 SEK/kWh if 1USD=8.5 SEK is used) according to an estimate by Gallagher et. al. [73].

3.4 Optimization of annual grid connection cost The connection cost of three stations, with diﬀerent characteristics, is optimized; Bjurhovda (both substations), Hälla and Björnön. To minimize the cost of the connection as well as meet the capacity, trigger condition and voltage drop requirements the solutions below are possible.

• Use one or several 400 V service cables to connect. The required area is met by the cheapest combination of cable thickness and number of cables. The owner of the charging station will be a low-voltage customer and pay the associated fees.

• Transport the power at higher voltage (10 kV) and build a new substation and step-down transformer at the location of the charging station. (Also needed: a short 400 V service). The owner of the charging station will be a high-voltage customer and pay the associated fees.

• Decrease the power demand by the use of an ESS and connect to the 400 V grid with one or several 400 V services.The owner of the charging station will be a low-voltage customer and pay the associated fees.

• Decrease the power demand by use of an ESS and connect to the 10 kV grid. (Also needed: 10 kV cable, substation, transformer and short 400 V cable). The owner of the charging station will be a high-voltage customer and pay the associated fees.

34 3.4.1 Linear programming problem The target for optimization is the annual cost for the grid connected customer. This includes the equivalent annual cost of the initial investment as well as yearly charges based on power and energy outtake. To minimize this cost, the optimal size of the energy storage in relation to the grid components are identiﬁed using Mixed Integer Linear Programming (MILP) in MATLAB. A MILP problem is speciﬁed by a set of constraints according to [74]:

x(intcon)(are integers) A · x ≤ b (inequality constraint) min f (x) subject to  (10) Aeq · x = beq (equality constraint)  lb ≥ x ≤ ub (bounded constraint)  where x is a vector of variables that is to be optimized. The objective function, f (x) is the expression that is to be minimized (or maximized). The algorithm used by the program is called Dual simplex, which is the most common linear programming algorithm [74].

The system is investigated during one day (24 h) with a resolution of 1 minute. The constraints must be fulfilled at each time step, meaning there has to be one set of constraints for each minute of the day (1440 minutes). The model that is used to evaluate the system and minimize the annual cost is inspired by a paper by Ding et. al [13], that suggests a method to cost optimize an electric bus system combined with energy storage. It is modified to suit this evaluation. In order to perform the optimization a series of constraints are specified and the optimization performed on the objective function for each time step t. The input to the model is the site specific load curve from the potential fast charging station.

3.4.1.1 Load proﬁles

The power required by the bus, Pbus, is determined by the bus energy demand, the bus schedule and the idle time at the station, tbus. In the normal case, the bus is assumed to arrive at the end station according to schedule. Pbus is inputed to the model as a 24 hour load curve with 1 minute resolution. The operation of the charging station is assumed to follow the below mentioned principles:

• The bus is always charged with the designed power, that is based on the scheduled time at the end station.

• If a bus arrives early, it will not charge until its expected arrival time.

3.4.2 Parameters In order to design the optimal system, 14 or 17 parameters are optimized in the low-voltage and high-voltage case, respectively. The following parameters are used in both cases:

• CL: the maximum power drawn from the grid

• EB: the size of the energy storage

• Pc (t): the charging power of the storage

• Pd (t): the discharge power of the storage

• Pg (t): the power drawn from the grid

• E(t): the energy level of the storage

35 In addition, g = [gA, gB, gC, gD, gE, gF, gG, gH] is used to determine the appropriate choice of 400 V cables, where each element in the vector represents one option. The options considered are 1-4 150 mm2 cables and 1-4 240 mm2 cables. If one element is 1, it means the corresponding choice is made. The rest of the elements should then be zero. In the high-voltage investigation, the best transformer and substation size must be calculated as well. To do this, ts = [tsA, tsB, tsC] is used in the same way. The transformer and substation options that are evaluated are 315 kVA, 500 kVA and 800 kVA. Figure 20 shows a simpliﬁed model of the grid and the charging station with an energy storage unit.

Figure 20: Model of the system that is to be optimized.

The system is though to operate according to the following:

• The ESS is charged with power Pc, when there is no bus at the station. This power is limited either by the grid capacity, CL, or by the ESS charging capacity.

• The bus is charged with power Pbus, from both the grid and the ESS. It is limited by the bus battery charge capacity or the charger capacity (assumed to be the same).

• The ESS is discharged with power Pd, limited by the discharge capacity of the ESS.

• The grid provides the power Pg, limited by the grid capacity, CL.

3.4.2.1 Integer constraints The elements in g and ts are speciﬁed as integers.

3.4.2.2 Bounded constraints Most parameters have zero as lower bound and Inﬁnity as upper bound, with the exception of all the integers, that have 1 as upper bound. This ensures that they will only be 0 or 1. It is possible to constrain any variable, for example the grid capacity or the size of the energy storage. In certain investigations this can be necessary.

3.4.2.3 Inequality constraints

Firstly, the power drawn from the grid, Pg can never exceed the grid capacity Cgrid. This is ensured by equation 11.

Pg < CL (11) Secondly, the choice of cable, transformer and substation (when applicable) is determined based on CL according to equation 12 and 13 where Pmax is the maximum capacity of either component choice.

36 CL ≤ Pmax,gA · gA + Pmax,gB · gB + Pmax,gC · gC + ... + Pmax,gH · gH (12)

CL ≤ Pmax,tsA · tsA + Pmax,tsB · tsB + Pmax,tsC · tsC (13) The magnitudes of the charging and discharging power are constrained according to equation 14 and 15. Etot is the total battery capacity in kWh and tmin is a constant that describes the minimal time during which the storage unit can be charged or discharged. 1 0 ≤ Pc (t) ≤ · EB (14) tmin 1 0 ≤ Pd (t) ≤ · EB (15) tmin The battery is assumed ideal, and thus the minimal charge/discharge time is approximated as 1 t ≈ hours (16) min C − rate although the relationship is more complex, as described in section 2.3.2.2.

There is a limit to the highest or lowest amount of energy the storage can contain, ensured by

Emin ≤ E(t) ≤ Emax (17) In order to maintain battery life-time (see section 2.3.2.5) it is important not to fully charge or discharge the battery. The limits in equation 17 is therefore expressed as (100 − DoD) Emin = · EB (18) 100 max Emax = · EB (19) 100 where DoD is the maximum allowed depth-of-discharge and max indicates the maximum charge level (in %).

3.4.2.4 Equality constraints According to the model by Ding et. al. [13], the energy level E in the storage unit at time t + 1 can be described by

E(t + 1) = E(t) + Pc (t) · dt · ηc − Pd (t) · dt/ηd (20)

where Pc is the charging power, Pd the discharging power and dt the time step of the discrete simulation. ηc and ηd are the respective charging and discharging eﬃciencies. Since the energy level at the end of the day must be the same as the level at the start of the next day, the following condition must be met:

E(1) = E(T) (21) The power taken from the grid equals

Pg = Pc + Pbus − Pd (22)

37 Ding et. al. [13] shows that when performing linear optimization Pc and Pd never are nonzero simultaneously, because it is never optimal to charge both the energy storage and the bus at the same time.

To ensure that only one cable, transformer and substation option is chosen equations 23 and 24 must hold. Remember that the elements in g and ts are either 0 or 1.

gA + gB + gC + gD + gE + gF + gG + gH = 1 (23)

tsA + tsB + tsC = 1 (24)

3.4.2.5 Objective function The objective function is the expression that is to be minimized, in this case the annual cost. For the low-voltage case it can be written as equation 25 where the ? denotes element-wise multiplication.

f (CL, EB, g) = a · CL + b · EB + c ? g + r (25) a is the monthly power fee, and r the additional fees that is required by the grid owner for a low-voltage customer. They are found in Appendix A3. b is the annuity of the battery price wB (SEK/kWh) minus the salvage value S (SEK/kWh) according to k ESS · − · b = −YESS (wB 0.8 S) (26) −1 + (1 + kESS)

where YESS is the energy storage lifetime and kESS its rate of interest. The battery speciﬁc parameters used in the simulation are presented in table 4. c is the annuity of the cost associated with each of the eight cable choices (SEK/km), inputed as a vector (see Appendix A1): k g · c = −Yg [wgA, wgB, wgC, wgD, wgE, wgF, wgG, wgH ] (27) −1 + (1 + kg)

These costs are found in Appendix A3. The lifetime Yg and rate of interest Kg are found in 3.3.

The objective function for the high-voltage case is expressed as equation 28.

f (CL, EB, g, ts) = a · CL + b · EB + c ? g + d ? ts + r (28) As in the low-voltage case, a and r constitute the fees, that are speciﬁc for the high voltage case and found in Appendix A3. b is also in this case the annuity of the battery cost minus the salvage value and c the associated cost of the low-voltage cable. d is the respective costs of the transformer and substation choices (Appendix A1): k g · d = −Yg [wtsA, wtsB, wtsC] (29) −1 + (1 + kg)

38 4 Results

4.1 Annual grid connection cost 4.1.1 Hällagatan, Hälla From the station (ﬁgure 21), the distance to the nearest substation Hällagatan is medium long (319 m), the power demand is high (695 kW) and the bus frequency low (4 buses/hour). Connection to the low voltage grid is not possible without energy storage, since the trigger condition can not be guaranteed given the power demand and the distance. Connection with four 240 mm2 cables of 319 m is estimated in Elvis to have capacity for about 550 Figure 21: The Hälla bus station (yellow circle) rela- kW, which is not enough. It is possible to connect tive to the closest 10/0.4 kV substations (red squares) to the high-voltage side of the substation without are shown. Yellow lines illustrate the linear distances decreasing the power outtake. and blue the cable distances.

A summary of the results obtained from the optimization of the high- and low-voltage case at station Hälla is presented in table 5.

Table 5: Optimization of the connection cost at the Hälla station.

Low-voltage connection LTO LFP Optimized total annual cost 537,360 934,820 (SEK/year) Fees (%) 38.5 47 Investment (%) 61.5 53 Optimal battery size (kWh) 215 830 Optimal grid capacity (kW) 219 554 Battery power to bus (%) 68 20 Grid power to bus (%) 32 80 High-voltage connection LTO LFP Optimized total annual cost 399,000 399,000 (SEK/year) Fees (%) 93 93 Investment (%) 7 7 Optimal battery size (kWh) 0 0 Optimal grid capacity (kW) 695 695 Battery power to bus (%) 0 0 Grid power to bus (%) 100 100

In both cases, the LTO battery manages best to decrease the annual cost, even though this is the most expensive of the studied batteries. This is explained by the fact that the LTO battery can be discharged to a deeper level than the LFP battery and thus use more of its capacity. That way it does not have to be

39 over-dimensioned to the same extent as the other battery option (compare 215 kWh to 830 kWh). Another diﬀerence between the batteries is their charge- and discharge capacity. For the same battery size, LTO batteries charges and discharges faster than the LFP does. However, this is not limiting in this case because of the high cycle life requirements.

In the low-voltage case, the grid can not meet the capacity demand on its own but if LFP batteries are to be used, a large investment is required. A 215 kWh LTO battery combined with a 219 kW grid achieves the optimized annual cost of 363,400 SEK/year but the LFP option would mean a cost of 934,820 SEK/year. In the LTO case, 60 % of the cost consist of the investment but in the LFP case it is rather evenly distributed between fees and the investment. It should be noted that, even though the LFP battery is very large, it only manages to provide 20 % of the required bus power while the LTO battery provides almost 70 %. In the high-voltage case, the grid can meet the demand on its own, and the optimal solution is to not invest in a battery at all (giving a cost of 399,000 SEK/year). 93 % of that cost comes from fees.

Figure 22 shows the relation between grid capacity, energy storage investment and annual cost of a low-voltage and a high-voltage connection at Hälla. The numbers are based on the annuity of the investment costs as well as the annual fees, that differ between a high voltage and a low voltage connection. It is assumed that the cheapest cable, transformer and substations that meets the requirements are used. From studying the figure, it is evident that the annual cost depends linearly on both the energy storage investment cost as well as the grid capacity. Steps are distinguishable where it is necessary to step up one size in cable/transformer/substation. It is noted that a high-voltage connection have lower annual cost than a low-voltage connection, for the same grid capacity and energy storage investment. Increasing the grid capacity in the high-voltage case has less effect on the total annual cost than in the low-voltage case, explained by the lower fees related to power outtake.

Figure 22: The image shows the total annual cost (SEK) for a low-voltage and high-voltage connection at Hälla, depending on the grid capacity as well as the investment in energy storage. It is important to realize that the energy storage capacity obtained by an investment depends on the type of store and its cost per kWh. The optimized annual cost achieved for Hälla by three different types of Lithium-ion batteries is marked in the graphs. It can be noted that a high-voltage connection is the cheapest option for a given grid capacity and energy storage investment, that the optimized annual costs at Hälla are lower in the high-voltage case and that the LTO battery achieves the lowest cost of the low-voltage case. The slope, achieved by a constant cost, is steeper in the low-voltage case which indicates that the grid capacity has a larger effect on the final cost. This is explained by the higher power based fees in the low-voltage case

Figure 23a shows the load curve from the charging station at Hälla and how it is met by a combination of the grid and the LTO battery (high- and low-voltage case). The storage is charged with as high power as possible (the grid capacity 219 kW) in between each bus charge. This enables the power from the grid to

40 be almost constant throughout the whole day. When the gap between the buses is smallest, the grid power never goes down to zero but is kept constant the whole time (around 20h in ﬁgure 23b). That means 219 kW is the lowest possible grid capacity that can be used without sizing the battery to provide several buses with power. It can be seen in ﬁgure 23c, which shows the battery energy level, that this is true.

(a) Power demand at Hälla.

(b) Grid power at Hälla.

Figure 23: (a) The expected power consumption from the potential charging station at Hälla is plotted in blue and reaches 695 kW each time a bus charges. This power demand is, in the cost optimized case, met by the grid (green) and the LTO battery storage (pink) according to the ratio 32/68 %. (b) In the normal case, the power from the grid can be substantially decreased with the use of an energy storage as viewed in the ﬁgure. The red area is the power outtake necessary if no storage was present. The blue area is the power outtake from the grid when the optimally sized LTO battery is used. (c) The graph of the battery energy level shows that the battery is fully charged between each bus charge.

4.1.1.1 Model sensitivity To evaluate the sensitivity of the model, various parameters are changed with ±10% and the resulting change of the annual cost, battery size and grid capacity is noted in table 6 below. The parameters of the model that have the largest impact on the outcome of the optimization are the bus energy consumption and the battery depth-of-discharge (DoD). The DoD greatly aﬀects the optimal size of the battery. A 10 % variation of the battery lifetime and the battery cost changes the result but with less than 10 %. The salvage value as well as the rates of interest has minimal impact.

41 Table 6: Results of the sensitivity analysis for optimization of the LTO cases at Hälla. The model parameters on the left hand side has been varied with ±10% and the change of CL, EB and the annual cost is noted in the table.

To investigate the degree to witch the results depend on the load profile that has been used to optimize the system, the load profiles for Hälla is varied. This is done by letting the arrival time of the buses be generated from a normal distribution with an expected value that equals the scheduled time and a standard deviation that equals 10 % of the total run time (4 minutes for Hälla). The optimization of a low-voltage connection is done for 5000 randomized load profiles and the result is shown in figure 24. It is evident that the result vary significantly. The annual cost achieved by optimizing the normal case is 537,360 SEK/year which is just within the 5th percentile. In the majority of the cases, the grid is required to have significantly higher capacity than 219 kW and the storage to be smaller than 215 kWh. This is because the time between the buses is sometimes shortened when the arrival times are varied.

Figure 24: To investigate the low-voltage result’s dependency on the load profile, the optimization was performed on 5000 different load profiles that was created using random bus arrival times. The resulting annual cost, battery size and grid capacity is shown in the box plots. When the normal case is optimized, the resulting cost is 537,360 SEK/year which is below the 5th percentile.

4.1.1.2 Suggested design approach The design method depends on what is demanded from the system. In this approach, the idea is to demand that X % of all load profiles, where the arrival times are varied with Y min, should be handled by the system. Hälla is used to illustrate this suggested design approach for electric bus charger systems. In figure 25a the annual cost at Hälla is plotted for various LTO battery sizes and grid capacities. The symbol marks all the design points that was generated when optimizing the 5000 randomized load profiles. Nine different options are visible. The design point for the normal case is marked with an arrow, and is the cheapest of all designs. The bar plot in figure 25b shows the accumulated fractions of the 5000 cases that is optimized to a certain cost, and from left to right they correspond to the costs marked as in the graph of annual cost.

42 (a)

(b)

Figure 25: (a) The annual costs achieved by certain grid capacities and storage sizes. The marks the design points obtained for the 5000 load proﬁles (9 diﬀerent). (b) The accumulated fractions of the 5000 cases optimized to a certain cost, matched by the marked points in the graph in (a).

637,280 SEK/year fulfills all 5000 cases but it is seen that 565,030 SEK/year manages to optimize 93 % of the cases. This is chosen as the X value, and thus the second point from the right is chosen as the design point. It has a grid capacity of 554 kW and a battery size of 77.2 kWh. In order to confirm that this design point really is the optimal way to handle 93 % of the load cases, it is tested on 5000 new randomized load profiles with arrival time deviations of ±10% of the total run time (the Y value). The grid capacity is fixed at 554 kW and only the battery size is optimized. The result is shown in figure 26.

Figure 26: Battery sizes obtained when optimizing 5000 randomized load proﬁles with a ﬁxed grid capacity of 554 kW. The two lower lines together constitutes 93 % of the cases.

The two lower battery sizes (77.2 and 63.9) constitutes 93 % of the 5000 cases and it is thus conﬁrmed that the design point 554 kW and 77.2 kWh is the optimal way to realize 93 % of the load proﬁles. The technical feasibility is assured by all the constraints of the model.

43 4.1.2 Flisavägen, Bjurhovda The distance to the substation Flisavägen (ﬁgure 27) is very long (654 m) and the power demand medium-high (345 kW). The buses arrive with high frequency (8 buses/hour). Connection to the low voltage grid can not be performed without the use of an energy storage. The limiting factor is the trigger condition that can not be guaranteed given the power demand and the distance. Connection with four 240 mm2 cables of 654 m have a capacity less than 280 kW, which is less than required by the charging station. Connec- tion to the high-voltage grid can be done Figure 27: The Bjurhovda bus station (yellow circle) rel- without any additional storage. The results ative to the closest 10/0.4 kV substations (red squares) are of the optimization can be viewed in table shown. Yellow lines illustrate the linear distances and blue 7. the cable distances.

Table 7: Optimization of the connection cost at the Flisavägen, Bjurhovda station.

Low-voltage connection LTO LFP Optimized total annual cost 1,518,420 6,422,500 (SEK/year) Fees (%) 18 4 Investment (%) 82 96 Optimal battery size (kWh) 811 7,498 Optimal grid capacity (kW) 277 277 Battery power to bus (%) 20 20 Grid power to bus (%) 80 80 High-voltage connection LTO LFP Optimized total annual cost 254,810 254,810 (SEK/year) Fees (%) 97 97 Investment (%) 3 3 Optimal battery size (kWh) 0 0 Optimal grid capacity (kW) 345 345

The results suggest that a high-voltage connection is signiﬁcantly cheaper than a low-voltage connection and in no need of energy storage. In order to perform a low-voltage grid connection, energy storage is required, which increases the investment cost. Independent of the battery type, it is ideal to draw 80 % of the power from the grid and 20 % of the power from the storage unit. This equates to a grid capacity of 277 kW, which is the maximum capacity possible (achieved by four 240 mm2 cables). An LFP battery must evidently be very large in order to meet the power demand.

44 The expected load curve for Bjurhovda is plotted in ﬁgure 28a alongside the power provided by the grid and as well as a battery. In ﬁgure 28b, the LTO battery energy level throughout the day is shown. The battery must be over-sized to provide several buses with power without fully charging in between. This is because the bus frequency is high at Flisavägen.

(a)

(b)

Figure 28: (a) The expected power consumption from the potential charging station at Bjurhovda is plotted in blue and reaches at most 345 kW. Note that this power curve was created assuming varying time spent at the end station, as evaluated based on the time table. Power is in the cost optimized low-voltage case provided from the grid (green) and the LTO battery storage (pink) according to the ratio 80/20 % (at maximum power demand). (b) The graph of the battery energy level shows that the battery is not discharged to its DoD other than in the beginning and end of the day. In the middle of the day, it uses only a small fraction of its capacity but is sized to charge several buses in a row without getting charged to the same level again in between.

4.1.2.1 Model sensitivity According to the sensitivity analysis of the low-voltage case (see Appendix C), the battery size and thus the cost is signiﬁcantly changed by a change of bus energy demand per kilometer. Also the depth-of-discharge has eﬀect on the battery size but not very much on the cost. In the high-voltage case, the cost is not noticeably changed by anything but the bus energy consumption and the battery size continues being zero.

When 5000 randomized load proﬁles are optimized, the high-voltage case does not change. The result for the low-voltage case is presented below in ﬁgure 29. It shows that in at least 95 % of the cases, the grid capacity is optimally 277 kW but that the storage size is often required to be larger and the cost is thus generally higher.

45 Figure 29: To investigate the low-voltage result’s dependency on the load profile, the optimization was performed on 5000 different load profiles that was created using random bus arrival times. The resulting annual cost, battery size and grid capacity is shown in the box plots as well as the bar graph.

4.1.3 Forntidsgatan, Bjurhovda This station is characterized by a large distance to the substation Forntidsgatan (515 m), medium power demand (345 kW) and high bus frequency (8 buses/hour).

Table 8: Optimization of the connection cost at the Forntidsgatan, Bjurhovda station.

Low-voltage connection LTO LFP Optimized total annual cost 258,800 258,800 (SEK/year) Fees (%) 89 89 Investment (%) 11 11 Optimal battery size (kWh) 0 0 Optimal grid capacity (kW) 345 345 High-voltage connection LTO LFP Optimized total annual cost 248,320 248,320 (SEK/year) Fees (%) 86 86 Investment (%) 14 14 Optimal battery size (kWh) 0 0 Optimal grid capacity (kW) 345 345

Simulations for the normal case (see ﬁgure 8) indicates that no battery storage is an optimal option but that it is cheapest to size the grid for the whole power demand. For the low-voltage case, this means

46 connection with four 240 mm2 cables that, at this length, have capacity for about 346 kW. Additional graphs of the results are presented in Appendix C.

4.1.3.1 Model sensitivity The sensitivity analysis shows that only the bus energy consumption has any eﬀect on the result. Increasing the energy consumption per kilometer enforces the use of an energy storage in the low-voltage case and thus increases the cost. Decreasing it instead lowers the total cost. When 5000 randomized load proﬁles were optimized, no deviation from the normal case was seen. The complete results of the sensitivity analysis is found in Appendix C.

4.1.4 Björnögården The station at Björnögården (ﬁgure 30) is located close to a substation (121 m), the buses require a medium high power (573 kW) and they arrive with medium high frequency (5 buses/hour). Due to the short distance it is possible to connect both to the low- voltage and the high-voltage side of the substation.

Table 9 compiles the results of the optimization. Neither in the low-voltage case nor the high-voltage Figure 30: The Björnö bus station (yellow circle) rel- case, the annual cost is minimized by the use of a ative to the closest 10/0.4 kV substation (red square) battery storage system. Most of the cost consist of are shown. Yellow line illustrates the linear distance the fees. It is cheaper to be a high voltage customer. and blue the cable distance.

Table 9: Optimization of the connection cost at the Björnögården station.

Low-voltage connection LTO LFP Optimized total annual cost 474,610 474,610 (SEK/year) Fees (%) 99 99 Investment (%) 1 1 Optimal battery size (kWh) 0 0 Optimal grid capacity (kW) 573 573 Battery power to bus (%) 0 0 Grid power to bus (%) 100 100 High-voltage connection LTO LFP Optimized total annual cost 342,270 342,270 (SEK/year) Fees (%) 93 93 Investment (%) 7 7 Optimal battery size (kWh) 0 0 Optimal grid capacity (kW) 573 573

47 4.1.4.1 Model sensitivity Only the bus energy consumption have a significant effect on the outcome of the optimization, when parameters are changed with ±10%. At Björnögården however, a bigger change in the battery price can cause a battery storage to optimally be included in the system. This is illustrated in figure 31, where the annual cost has been optimized using different values of the LTO and LFP cost per kWh. Already at a cost of 6500 SEK/kWh for the LTO battery, the system optimally uses the battery to decrease the grid power outtake. It is never optimal to use an LFP battery or to use a battery that is larger than 180 kWh.

Figure 31: The plot shows how the optimal battery size varies with the cost of the battery, for an LTO battery as well as for a LFP battery.

The reason 180 kWh is the largest useful battery size is viewed in ﬁgure 32 that shows plots of the estimated power demand, the resulting grid power as well as the energy level of a 180 kWh LTO battery. The power is provided evenly by the grid and the storage. In ﬁgure 32b the total power drawn from the grid is plotted, and it can be seen that it is constant throughout the largest part of the day. That means it is providing the same amount of power to the bus as it is to the battery storage. The LTO battery is discharged to its allowed depth each cycle and charged fully again during the time in between buses. If the grid capacity was to be decreased, the battery would have to be sized in such a way that it was not necessary to fully charge it again between each bus. In other words, it would have to be very large. This is not optimal, even with a cheaper battery price.

48 (a)

(b)

(c)

Figure 32: (a) The expected power consumption from the potential charging station at Björnögården is plotted in blue and is 573 kW. In the cost optimized low-voltage case power is drawn from both the grid (green) and the LTO battery storage (pink). (b) The plot shows the total power drawn from the grid during a day. It shows that the bus and the storage is charged with the same power, and that the power outtake is kept constant. (c) The graph of the battery energy level shows that the battery is discharged to its DoD every time a bus charges.

When the load proﬁle is varied and the optimization performed on 5000 times, both the high- and the low-voltage case is optimized without energy storage for all cases. The complete analysis is compiled in Appendix C.

4.2 Grid owner investments The power to the charging stations are ﬁrst fed through the primary substations. Table 10 lists the loading, the transformer rating as well as the available capacity in the primary substations that feed the fast charging stations. Note that a primary substation feeds several charging stations located at diﬀerent nodes in the distribution grid.

49 Table 10: All charging stations would be fed by primary substations (130/10 kV). The primary substations aﬀected by the fast chargers are presented in the table along with their transformers as well as available transformer capacity. The primary substation must be dimensioned to feed all connected chargers simultaneously, hence the total power required by the buses during normal feeding mode is presented. Fed by the primary substation CM there is only one charger at the central station, marked 900 kW. It is possible that there will be several fast chargers at the central station.

Primary substation Transformers Power fed by super- Total power re- Available capacity (MVA) jacent grid (MW) quired by electric in transformer buses fed by sta- (MW) tion (MW) ÖM 2 x 25 17.5 1.35 7.5 NM 2 x 40 33.4 1.3 6.6 LM 2 x 40 32.1 1.8 7.9 SM 2 x 40 20.5 0.95 19.5 CM 1x 40, 1x 63 39 At least 0.9 1

Secondary substations suitable for connection are identiﬁed based on their proximity to each charging station. Customer owned substations were neglected in most cases. No end-station is considered unsuitable for a fast charging station due to lack of space. All relevant substations are presented in table 11.

No lack of capacity is identiﬁed in the primary substations. As shown in table 11, the available capacity in the cables during normal feeding is in the size of MVA for every charging station. Lack of capacity is therefore presently not an issue in cables, when normal feeding mode is used. Overcapacity might occur during certain back-up feeding. but it is diﬃcult to analyze in a strategic way since there are so many options for back-up feeding and it stretches outside the scope of this work. It is concluded that no cable reinforcements will be needed in the Västerås grid due to the fast charging stations only.

The identiﬁed distribution substations are equipped with one or two step-down transformers of 315 - 1250 kVA. At Skälby, Bjurhovda, Björnögården, Hälla and Hacksta the charging station power demand exceeds the available transformer capacity (see table 11). Bjurhovda, Björnögården and Hälla will be evaluated. It is assumed that the substation capacity equals the present transformer capacity, since this information is not available in the grid model for most substations. Three possible grid-owner investments are assessed from a cost eﬃciency perspective.

• A new transformer, the same size as the already existing one.

• A new substation and a transformer that is sized to feed only the charging station. (Also needed: a 10 kV cable.)

• An ESS that decreases the charging station power demand to a level that can be met by the existing transformer.

50 Table 11: The end-stations are listed together with their closest substations. The available cable capacity is based on estimated worst case power demand as well as maximum allowed line load, as explained in section 3.1.2. Available transformer capacity is calculated from the transformer load factor. If the capacity is exceeded, the transformer in question is marked in bold.

End-station Substations Transformer Type of Distance: Available ca- rating load fed by linear/- pacity during (kVA) distribution cable normal feeding, substation (m) grid/transformer (MVA) Skälby V. Skälby (ET 65) 800 Residential 135 / 153 4.76 / 0.15 Bjurhovda Flisavägen (ET 198) 2x800 Residential 408 / 654 4.29 / 1 Forntidsgatan ö. (ET 128) 315 Residential 421 / 515 2.59 / 0.25 Norra gryta Hyacintv (ET 298) 800 Residential, 194 / 271 3.26 / 0.53 school Tulpang (ET 300) 800 Residential, 222 / 288 3.26 / 0.59 school Björnön Björnögården (ET 2001) 500 Restaurant, 95 / 121 2.08 / 0.41 Conference center Erikslund Järnbruksgatan (ET455) 800 Mall 128 / 138 2.25 / 0.79 Flygplatsen Hässlö ﬂygst (ET349) 500 Airport 91 / 112 ? / 0.35 Brottberga Lavegatan (ET 392) 800 Residential 37 / 40 4.42 / 0.63 Finnslätten Bränslegatan (ET 262) 500 Industrial 544 / 730 6.25 / 0.46 Stolpgatan (ET 461) 800 Industrial 462 / 747 5.79 / 0.62 Tunbytorp Batterigatan (ET 467) 800 Oﬃce 224 / 283 4.61 / 0.57 Hälla Hällag. N (ET 342) 2x1250 Mall 218 / 319 5.36 /1.55 Stockh.-v.142 (ET 7) 800 Mall 269 / 384 4.56 / 0.44 Rönnby Diskusgatan (ET498) 800 Residential 236 / 442 4.9 / 0.39 Löpargatan (ET 221) 2x800 Residential 200 / 253 ? /0.94 Hacksta Saltängsv. 38 (ET 241) 800 Industrial 39 / 39 6.24 / 0.78 Central station Own substation fed by CM - - - -

4.2.1 Hälla The power demand from the charging station without energy storage is 695 kW at Hälla. In the substation, the 800 kVA transformer has 440 kVA available capacity. To solve this, a few options are explored and presented in table 12. Note that the battery that previously was optimized to decrease the customers annual cost only decreases the power demand to 577 kW. It will therefore not help to solve the transformer issue. Looking at the results, it is evident that the least costly option, both as an investment and as annuity, is to just invest in a new 800 kVA transformer and substation.

51 Table 12: Results for the Hälla station. It is assumed that nothing larger than one 800 kVA transformer ﬁts into the existing substation and that the grid owner invests in the energy storage.

Option 1 Description Investment cost Annuity Decrease in cus- (SEK) (SEK/year) tomer fees Investing in a new substation and trans- 528,433 28,963 0 former rated 800 kVA, close to the bus station and a connecting 10 kV cable. Option 2 Description Investment cost Annuity Decrease in customer fees Decrease the power demand to 500 kW 1,034,049 143,317 116,000 with an 85.5 kWh LTO and invest in substation and transformer rated 500 kVA instead, plus connecting 10 kV cable. Option 3 Description Investment cost Annuity Decrease in customer fees Decrease the power demand to 440 kW 952,000 165,662 165,240 with a 112 kWh LTO and avoid other investments

4.2.2 Forntidsgatan, Bjurhovda The substation Forntidsgatan have one 315 kVA transformer with only 240 kVA available. The power demand from the charging station is 345 kW. Possible solutions are presented and compared in table 13. The results show that also at Bjurhovda, it is cheaper to just invest in a new station and transformer.

Table 13: Results for the Forntidsgatan, Bjurhovda station. It is assumed that nothing larger than one 315 kVA transformer ﬁts into the existing substation. To decrease the power demand to 240 and avoid other investments was not feasible without a very over-dimensioned battery.

Option 1 Description Investment cost Annuity Decrease in cus- (SEK) (SEK/year) tomer fees Investing in a new substation and trans- 702,470 38,447 0 former rated 500 kVA, close to the bus station and a connecting 10 kV cable. Option 2 Description Investment cost Annuity Decrease in customer fees Decrease the power demand to 315 kW 912,695 130,973 19,661 with an 80 kWh LTO and invest in substation and transformer rated 315 KVA instead, plus connecting 10 kV cable.

52 4.2.3 Björnögården At Björnögården, there is one 500 kVA transformer with an available capacity of 410 kVA. The power demand from the bus charger would be 573 kW. Some options are presented in table 14.

Table 14: Results for the Björnögården station. It is assumed that nothing larger than one 800 kVA transformer ﬁts into the existing substation and that the grid owner invests in the energy storage.

Option 1 Description Investment cost Annuity Decrease in cus- (SEK) (SEK/year) tomer fees Investing in a new substation and trans- 735,656 40,263 0 former rated 800 KVA, close to the bus station, as well as a connecting 10 kV cable. Option 2 Description Investment cost Annuity Decrease in customer fees Decrease the power demand to 500 kW 721,293 90,296 19,661 with an 50 kWh LTO and invest in substation and transformer rated 500 KVA instead, plus connecting 10 kV cable. Option 3 Description Investment cost Annuity Decrease in customer fees Decrease the power demand to 410 kW 954,030 166,015 105,851 with an 112 kWh LTO and avoid other investments

The result is similar to the previous stations, the cheapest option by far is to invest in a new station and transformer to meet the demand from the new charging station. However, at this station the optimal battery (180 kWh LTO) from the previous investigation manages to decrease the power demand to 275 kW. If this investment was realized by the charging station owner, the grid owner would only have to invest in a 315 kVA transformer and substation instead of those rated 800 kVA.

53 5 Discussion

5.1 Annual grid connection cost The model presented in this study describes the expected power load from the different bus lines, the charging station, the energy storage and the connection to the local grid. It optimizes the size of the energy storage as well as the maximum power outtake from the grid in order to minimize the total annual cost of the connection. To evaluate the cost, both the connection fees as well as the annuities of the investments in grid components and energy storage are considered. The more components and parameters that are optimized instead of manually specified, the better the optimized system. The model allows for the battery to be operated in the most suitable way, limited only by its depth-of-discharge as well as power capacity. The operation is not controlled. This means that if optimal, it can do one cycle per bus charge or one cycle per day or anything in between. The model itself also choses the optimal size and number of cables, the appropriate service fuse (LV), the transformer (HV) and the substation (HV). The two parameters that most affect the result are the battery depth-of-discharge and the bus energy consumption. Therefore weaknesses to the model are the rough estimations of these parameters. An improvement that can be made is to include the battery lifetime and depth-of-discharge in the optimization.

The bus energy consumption per kilometer was in this study approximated to 2.3 kWh/km although it is known to depend on weather, season, time of day, day of the week, driver behavior, speed, topography and road quality. It is seen in the sensitivity analysis that changing the energy consumption can drastically change the result. Because of this, the results should be seen as indications rather than actual suggestions on how to construct the charging system at the stations. It is recommended to do a more thorough analysis on the bus energy consumption on each route when designing the system because of the evidently large impact on the ﬁnal results.

The LTO battery is characterized by the largest depth-of-discharge and the fastest charging and discharging. It is also the most expensive of the studied batteries. In all studied cases, the LTO battery is the most cost eﬀective battery option. At the stations that require an energy storage system to connect to the low-voltage grid (Hälla and Flisavägen) the LTO battery is by far the better option. At Björnögården and Forntidsgatan, grid connection to the low-voltage grid can be performed without decreasing the power demand. However, at Björögården the LTO battery price only has to decrease to 6500 SEK/kWh in order for it to enable a lower annual grid connection cost. Also the similar study by Ding et al. [13] concludes that LTO batteries can be used to cost optimize connection and operation of fast charging stations. However, this study also concludes that LFP batteries can be used for this purpose.

What limits the LFP battery is the depth-of-discharge. This is concluded since the maximum possible charge and discharge power, determined by the size of the battery, in all cases is higher than the battery power required by the system. In this study, LTO batteries uses 13-15 % of its total size and LFP batteries only 1-3 % in order to last 8 years. The depth-of-discharge has a great effect on the sizing of the battery, which is visible in the sensitivity analysis as well as when comparing the results for LFP and LTO. The cost of the used battery capacity can be calculated by dividing the battery cost (SEK/kWh) by the used capacity (in % of total capacity.) For the batteries in this study it is 65,450 SEK/used kWh for LTO (22 % DoD) and 116,550 SEK/used kWh for LFP (3 % DoD). The LFP is, as was seen in during the optimization process, more expensive. It is important to notice that the depth-of-discharge and its relation to cycle life vary between battery manufacturers. Therefore, the analysis should be performed with a specific battery in mind and with the knowledge of all its characteristics. In this study, the battery parameters are collected from a few different sources and might not reflect the characteristics of an existing battery. Also, there has been significant improvement in the recent years and the numbers used in this study might not be the most

54 recent ﬁgures.

A high-voltage connection is cheaper than a low-voltage connection in all four cases. The contour plots conﬁrm this, since the cost increases faster with increased grid power in the low-voltage case. This is mainly due to the lower fees of the high-voltage connection. A high power customer therefore beneﬁts from connecting to high-voltage, even though it means investing in a substation and transformer. A high- voltage connection might however not be the best solution since owning and operating a substation with a transformer means a need for maintenance and possible expenses that would otherwise be avoided.

It is seen that the biggest portion of the annual cost consist of the fees, in the cases where the investment is limited to grid components. The fees of a high-voltage connection constitutes 86-97 % of the total annual costs of connection. For a low-voltage connection it is 89-99 % without an energy storage and 18-38.5 % with an LTO battery. This shows how expensive investing in energy storage is compared to investing in cables, transformers and substations.

The low-voltage connection can be optimized by a 8500 SEK/kWh LTO battery at Hälla and FLisavägen and by a 6500 SEK/kWh LTO battery at Björnön. It is most cost eﬃcient where the bus frequency is low enough for the buses to do one cycle for each bus charge. At Flisavägen, the buses arrive with so high frequency that the battery must be large enough to provide several buses in a row with power without fully charging in between. As a rule of thumb, energy storage solutions should be investigated at stations where the power demand is high but the bus frequency low.

When the load curves are varied and optimized, the cost is always larger than what was achieved for the normal case (no deviations from the schedule). This is because the variation in arrival time decreases the time in between the buses and forces the battery to be bigger. It is unlikely that the buses will always arrive on time and if the system is sized according to the normal case it will be expected to see buses having to charge slower than scheduled because the battery did not have time to charge fully after the previous bus. There is a risk that this will cause line-ups at the charging station.

One could argue that a better solution to the problem of this study would be to just redraw the bus routes so that the bus stops right in front of a substation. The bus schedule could be made so that the bus stays long enough at the station to charge with whatever power is available. This way, the connection cost would drastically decrease. However, the flexibility of the bus system would also decrease which makes it difficult for electric buses to compete with other types of bus systems based on renewable fuels (bio-gas for example). Installing an energy storage in connection to the charging station could, in addition to decreasing the connection costs, contribute to increased flexibility. While energy storage can increase the flexibility it also increases the system complexity. The electric bus system will become similar to the train system, where each vehicle and its operation is dependent on the other vehicles in the system. There can be lineups at the stations, electrical issues that causes delays etc.

An interesting application for the energy storage can be discussed for the Björnö station, that is fed by a radial with no backup feeding. This is something that makes the system vulnerable, as the traﬃc of bus line 4 would be completely stopped by a fault somewhere on that cable. At the stations, the 6000 SEK/kWh LTO battery was optimized to 180 kWh. Since it is only discharged to 21 % during normal operation, it means at least 142 kWh are available at any time. This could be used to power the buses in case of a power outage. One bus is estimated to consume 32.45 kWh/charge and during the busiest time there are 5 buses/hour. The energy from the battery can thus be used to power at least 4 buses and keep the normal bus operation for almost an hour. During this time, a backup generator could be put in place. This is a good example on how an energy storage system could increase the system redundancy.

55 5.2 Suggested design approach Before designing the system it is important to gain accurate knowledge of the expected worst-case bus energy consumption, the bus schedule, statistical deviations from the bus schedule, speciﬁc energy storage parameters (DoD, C-rate etc) as well as connection costs and fees at the location. The dimensions of the system is then determined based on what to demand from it. In this study, the anticipated load is achieved when the buses run according to the time table. It is called the normal case. However, as was seen when varying the load proﬁle, using the normal case as the design point will cause trouble if the buses deviate from the schedule. If an energy storage is used in the design, bus delays will lead to a decrease in the time where the storage can charge (when there is no bus at the station). This in its turn will decrease the power that can be provided by the system, which transfers the delay to buses that were initially on time.

In order to design the system to tolerate some delays, two parameters can be changed from the normal case:

• Increase the design bus charging power.

• Decrease the design time between buses.

The scheduled time at the end station is likely required in order for the driver to take a break. Even if the bus is delayed, some idle time at the end station might still be necessary. Because of this, it is considered better to account for shorter time in between the buses instead. This way, the delay of one bus does not necessarily mean the delay of the following bus.

It is likely that there will be delays on some buses during the day. However, it is not likely that the time between the buses will be shortened many times in a row or during the whole day. A reasonable requirement was stated as "X % of all load proﬁles, where the arrival times are varied with Y min, should be handled by the system ". The percentage X should be determined based on what costs are considered reasonable. In the example of Hälla, X was set to 93 % because the annual cost had to increase very much in order to cover 100 % of the cases. Had the extra investment instead been small, it would have been worth considering. The parameter Y require some knowledge about the bus system and its statistic delays. In this study, the standard deviation from the arrival time is assumed to be 10 % of the total run time. The arrival times are assumed to be normally distributed and thus not depend on the previous arrival time. Correlation factors such as traﬃc and weather is ignored.

5.3 Grid owner investments The main reason it is more cost eﬀective to invest in a new transformer and substation is the fact that these components are expected to last for 40 years, while the battery lifetime only is 8 years. Something worth considering however, is the fact that the bus system might not stay the same for 40 years. If the routes are redrawn or other types of buses are implemented, the power outtake at the substation will drastically decrease and the investment become unnecessary. This is a good example of how an energy storage increases the ﬂexibility, since it is easier to relocate a battery bank than a transformer substation and cables.

5.4 Criticism of the sources Energy storage cost figures vary substantially between different reviews and it is particularly difficult to differentiate the costs of various lithium-ion batteries. 410 $/kWh (3500 SEK/kWh) is a well established figure that was estimated by Nykvist et. al. [65] based on 85 references (peer reviewed articles, experts, industry estimates etc). The lithium-ion battery type is however not specified, but there exist a significant price difference between the various chemistries and LTO batteries are more expensive than any other

56 lithium-ion batteries. The cost ﬁgure for the LTO battery that is used here is not conﬁrmed by other sources.

It makes a lot of sense to use the standard values from Ei as indication on grid connection costs, since this constitutes the framework for network operator charges. It means that even if the connection in reality costs more to construct, the customer will not be charged more than the standard costs of the components. In this study, the grid capacity evaluation is not performed on real consumption data but on estimated ﬁgures from type curves. However, the numbers are based on worst case scenarios and it is very likely that the available capacity in reality is larger.

5.5 Criticism of the methods The dual simplex algorithm is a well established method to optimize a problem that is subject to a set of constraints. The problem is well formulated and the solver has no issue converging towards a solution. However, since the constraints must hold each minute of the day, the set of constraints must be repeated 1440 times and the problem quickly becomes very big. The available computer capacity might constrain a further expansion of the model.

Since the investigation is based on concrete examples from Västerås, it might not be possible to transfer the results to other locations. Instead, they can be used as guidelines on how to analyze an electric bus system and determine whether an energy storage is suitable. In addition, the results give an indication on the kind of system characteristics that make energy storage suitable.

5.6 Suggested further studies In this study, the life time of the batteries was set to 8 years to match the guaranteed life time of the buses and charging stations. The life time is then used to determine the battery depth-of-discharge. It is assumed that the battery will do one cycle each time the bus charges, but that is not always the case. An important improvement of the model would be to optimize the cycling of the batteries so that the resulting depth-of-discharge, lifetime and size is the most cost eﬀective.

Only batteries were studied in this investigation but other energy storage technologies could be of interest. In particular, flywheels show potential due to their ability to charge and discharge fully without decreasing its lifetime significantly. At present, flywheels are more costly than lithium-ion batteries but could be a better option because of the much longer life-time and its independence of cycle depth.

57 6 Conclusions

The evaluation of the distribution system indicates that implementing an electric bus system based on opportunity charging in Västerås does not cause the available capacity in the 10 kV grid to be exceeded during normal feeding mode. However, grid reinforcement might become necessary to ensure that potential backup feeding modes are available. To minimize the grid owner investments in new transformers, batteries are not a cost eﬀective option. Nevertheless, grid owners might beneﬁt from customer’s investment in batteries to decrease their power demand since this have the potential to decrease the need for new transformers.

Battery energy storage have the possibility to decrease the annual cost of connecting a fast charging station to the low-voltage grid. The main benefit of the storage is to decrease the fees to the grid owner. Out of the studied batteries, the LTO is the most cost effective solution due to its larger possible depth-of- discharge. The primary factor to determine whether a battery storage will decrease the annual costs of a charging station is the bus frequency. The longer the time in between buses and the higher the power, the more beneficial is the energy storage.

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62 Appendix A. Data

A1. Cost of components

Table 15: Normal values of cables, substations and other grid components as estimated by Ei in 2014 [A1]. These costs are what Ei considers reasonable, and when a grid company connects a customer to their grid and potentially performs reinforcements the list determines what the customer can be charged. This list is valid during 2016-2019. This table shows the items used in this study.

Type Code Technical Voltage Normal Unit speciﬁcation (kV) value 2014 (SEK) Earth cable, urban NG14536 PEX 3x240 mm2 0.4 726,738 km Earth cable, urban NG14535 PEX 3x150 mm2 0.4 683,690 km Earth cable, urban NG14521 PEX 3x50 mm2 12 590,373 km Transformer NG15923 315 kVA 12/0.4 70,501 - Transformer NG15922 500 kVA 12/0.4 101,565 - Transformer NG15921 800 kVA 12/0.4 134,751 - Substation NG15224 315 kVA 12/0.4 162,973 - Substation NG15223 800 kVA 12/0.4 205,354 -

A2. Cable loadability

Table 16: Maximum cable loading for 3 phase underground cables with PEX isolation according to Vattenfall Eldistribution guidelines [A2].

Al Cu Conductor area Current (A) at Power (kVA) at Current (A) at Power (kVA) at (mm2) 65 °C 10.8 kV 65 °C 10.8 kV 10 75 1 403 16 78 1 459 101 1 889 25 100 1 871 126 2 357 35 121 2 263 152 2 843 50 142 6 656 184 3 442 70 173 3 236 221 4 134 95 205 3 835 263 4 920 120 231 4 321 299 5 593 150 257 4 807 331 6 192 185 294 5 500 373 6 977 240 336 6 285 431 8 062 300 383 7 164 483 9 035

63 A3. Grid connection cost Low-voltage Customers with a service fuse over 80 A pay the cost price of the service cables according to the normal value prices established by Ei. In addition, the following fees are payed. Table 17: Prices for low-voltage connection at Mälarenergi Elnät in 2016 [A3]. The monthly power fee refers to the highest power outtake during the month. The initial fee refers to the service fuse and is payed by customers having a service fuse larger than 80 A.

Monthly fee (SEK/- Monthly power fee Electricity transfer fee Initial fee (SEK/A) month) (SEK/kW) (SEK/kWh) 453 54 0.053 500

High-voltage High-voltage customers pay the cost price of the 10 kV cables according to the normal value prices established by Ei. In addition, the following fees are payed. Table 18: Prices for high-voltage connection at Mälarenergi Elnät in 2016 [A3]. The yearly power fee refers to the mean of the two highest hourly power outtakes during the year. The initial fee refers to the subscribed power and is payed by customers having a subscription up to 2 MVA.

Monthly fee (SEK/- Yearly power fee Electricity transfer fee Initial fee (SEK/kVA) month) (SEK/kW month) (SEK/kWh) 1150 38 0.023 500

A4. Battery depth-of-discharge

Figure 33: Relationship between battery cycle-life and depth-of-discharge for LTO battery from Altairnano [A4]. The number of cycles indicates how many cycles the battery can perform before the capacity is decreased to 80 %. .

64 A5. Energy storage technologies Flywheel Energy Storage (FES)

Table 19: Characteristics of a flywheel energy storage system. Flywheels possess high cycle efficiency as well as high power density. The cycle life is also notably high and it is not affected by the depth of discharge [A5]. A drawback is the high hourly self-discharge. The numbers are collected from a review by Lou et.al. [A6] when nothing else is noted and the conversion 1 SEK = 8.5 USD is used.

Density Power Energy Eﬃciency Life-time Self- Discharge Cost (Wh/L; rating rating (cycle; charge; (cycle; discharge time @ (Invest SEK/kWh; W/L) (MW) (MWh) discharge) years) (%/hour) rated power Oper. SEK/kW/y) 20-80; 0.1-20 0.005-5 90-95; 90-93 ; >21,000 >20 seconds - 8,500-119,000; 1000- 90-93 (>1,000,000 (5 -15 [A5]) minutes 20 5000 [A7]); 15-20

Superconducting Magnetic Energy Storage (SMES)

Table 20: Characteristics of a SMES system. The technology shows a high cycle life as well as high power capability, although it is complicated and expensive to construct and maintain [A5]. The numbers are collected from a review by Lou et.al. [A6] and the conversion 1 SEK = 8.5 USD is used.

Density Power Energy Eﬃciency Life-time Self- Discharge Cost (Wh/L; rating rating (cycle; charge; (cycle; discharge time @ (Invest.SEK/kWh; W/L) (MW) (MWh) discharge) years) (%/hour) rated power Oper.SEK/kW/y) 0.2-6; 0.1-10 0.0008- 95-98; - ; 95 >100,000; 10-15 milliseconds 4,250-612,000; 1000-4000 0.015 20-30 - minutes 18.5

Capacitors and supercapacitors

Table 21: Characteristics of capacitors and supercapacitors. Both capacitors and supercapacitors exhibit very long cycle-life but the self discharge is up to 40 % in a day which means they are only suitable for very short-term storage. Supercapacitors have higher eﬃciencies as well as power and energy ratings than capacitors. When nothing else is noted, the numbers are collected from a review by Lou et.al. [A6] and the conversion 1 SEK = 8.5 USD is used.

Technology Density Power Energy Eﬃciency Life-time Self- Discharge Cost (Wh/L; rating rating (cycle; charge; (cycle; discharge time @ (Invest.SEK/kWh; W/L) (MW) (MWh) discharge) years) (%/day) rated power Oper.SEK/kW/y) Capacitor 0.05-10; <0.05 - 60-70; - ; 75-90 5000- 40 milliseconds 4,250-8500; 13 >100,000 50,000; (10- - hours 1-10 15[A5]) Super- 10-30; <0.3 0.0005 84-97; -;95-98 50,000- 5-40 milliseconds 2,550-17,000; 6 capacitor >100,000 100,000; - hours 10-30

65 B. Substations

(a) Erikslund (b) Hacksta

(d) Norra Gryta

66 (e) Rönnby (f) Skälby

(g) Flygplatsen (Airport) (h) Brottberga

67 C. Results

Björnögården LTO

Figure 34: Sensitivity analysis.

Low-voltage case

Figure 35: Optimization of 5000 randomized load proﬁles.

High-voltage case

Figure 36: Optimization of 5000 randomized load proﬁles.

68 LFP

Figure 37: Sensitivity analysis.

Hälla LTO High-voltage case

Figure 38: Optimization of 5000 randomized load proﬁles.

LFP

Figure 39: Sensitivity analysis.

69 Flisavägen LTO

Figure 40: Sensitivity analysis.

High-voltage case

Figure 41: Optimization of 5000 randomized load proﬁles.

LFP

Figure 42: Sensitivity analysis.

70 Forntidsgatan LTO

Figure 43: Sensitivity analysis.

Low-voltage case

Figure 44: Optimization of 5000 randomized load proﬁles.

High-voltage case

Figure 45: Optimization of 5000 randomized load proﬁles.

71 LFP

Figure 46: Sensitivity analysis.

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