XIV Conference Environmental 940 • Province (voivodeship) 2. CharacteristicsofnatureandclimateintheOpole for solution optimized the transportation tasks. for searching power in for consists biomass of generation utilization and acquisition of process the of databases where statistical informationandtheGISsystemareinvolvedaswell. with analysis optimization multi-criteria and of biomass is available should be only one component of a multistage and amount potential opportunities for its utilization. The process of the estimation how much with associated indirectly only are that stemmed be out from investigation of numerous conditions and economic factors must decision a Such utilization. its about decision a the potential size for speciic types of biomass is not suficient to take about knowledge the accuracy its regardless and applied is method estimation whichever Nevertheless, level. evaluation the on depending 1. Introduction oss ih h hget fcec o arclua pouto within production agricultural of eficiency highest the with boasts region The conditions. natural beneicial by stimulated is agriculture where region, industrial and agriculture a as classiied is Province the economy, to regard With Province. the of 92% about occupy areas Rural urbanization. of degree high demonstrate and units populated sizeable represent that villages large are Province the within regions rated among the provinces with the lowest population. Typical inhabited The Opole region is the province with the smallest area in Poland and is mountains. in are parts remaining the Lowland, Silesian the within its with theCzechRepublic. of Łódź and Silesia. In south the Opole region has the common border borders on the province of Lower Silesia, Great Poland (Wielkopolska), about 60% falls to arable lands and 27% to forests. The Opole Province the basin of the Odra river. It occupies the area of 9,412 km 9,412 of area the occupies river.It Odra the of basin the estimation ofthebiomassenergeticpotential[4,5]. energy amount that can be generated from biomass theis referred of to Determination an production. biomass for opportunities local of investigation accurate on depends orsubstantially level municipal commune the at i.e. scale, local the at utilization biomass the of local degree The safety. are energy of level sources the improve energy may and ones Renewable [7]. biomass with fuelled facilities generating power of erection for precondition key localthe is that one and economic the global is both factor important of most The factors magnitude. many on depends biomass by offered potential of energetic comprises of production use as The energy fuel. well environment-friendly as renewable heat and of power electric share of generation The 15%. by sources renewablefrom energy of growth as goals such achieve to obliged According to the climatic and energy package [1] Poland by 2020 is to increase share of renewable energy in the overall energy balance. n o sgicn cmoet f h otmzto ts for task optimization the of component signiicant of One In terms of geographic location about 75% of the Province area Province the of 75% about location geographic of terms In The province of Opole is situated in south-west part of Polandin of part south-west in situated is Opole of province The ma estimation potential energetic the of Usefulness states member obliges Union European of policy energy The Please citeas:CHEMIK2013, and Logistics, OpoleUniversityofTechnologyPoland inOpole, Anna DUCZKOWSKA-KĄDZIEL, Jerzy DUDA, Marek WASILEWSKI – Faculty of Production Engineering of biomass storage approach tosearchingforanoptimumlocation Application oftheminimumspinningtree(MST) 67 , 10,935–944 2 , y vary vary y of that of tion andexpansion prospectsassociatedwiththebiomassenergy 3. Renewable sourceofenergyintheNysaCounty, theirutiliza area [2](Tab. 1) Province the of 28.38% up make regions such law, by protected with theaverageareofapeasantfarmamountingto10.1ha). country the within ones size medium the among rated are Opole of potential for further growth. With regard to size, farms in the Province high with farms modern of share high ind can one region, entire the for the south, western and north parts of the Province where, likewise 200 to 225 days). The agricultural production is substantially important from lasts plants of period vegetation (the conditions soil and climatic Poland, which results from advanced culture of farming and favourable many investmentprojects. of implementation disable practically that regulations legal speciic by areas in the Nysa county. Each form of nature conservation is governed lands of conserved nature and landscape. Figure 1 presents depicts such selection of the area for investigations must be started from exclusion of the most area assigned for agricultural purposes. Considerations about Nysa. The county is located in the south-west part of the province with Fig. 1.Areasofconserved natureandlandscapein the Nysacounty[2] oa rao xrm aua au 2,671 189,207 Total 11,668 areaofextremenaturalvalue Natural andlandscapeunits Lands ofecologicaluse 941,167 Areas ofprotectedlandscape Landcape parks Reserves ofnature 260,623 Lands undersurfacewaterreservoirs Built-up andurbanizedareas Forest areasalongwithcoveredbytreesandshrubs Total areaoftheOpoleProvince The Province area also comprises sections of nature conservation h ivsiain cvrd l cmue wti te ony of county the within communes all covered investigations The Regions ofnatureconservationwithintheProvince ofOpole Speciication nr 10/2013 • tom67

Area inha 73, 998 54,759 2, 583 471 802 Table 1 - – themethodicalapproach 4. Estimationofenergeticpotential offeredbybiomass of renewableenergy intheOpoleprovince. from renewable sources. Nowadays, biomass is also the major source to solid biomass with the contribution of 85.5% in total total energy acquired in falls energy renewable of balance the in energy item important most The [7]. primary of 9.0% up makes that sources renewable generation intheNysacounty. heat for used is biomass how depicts 3 Figure t/month. 660 about is output total their and briquettes and pellets produce to biomass use that plants technological ive are there county Nysa the in Nowadays is also sawdust used of production of and fuel – pellets Straw or briquettes of wooden cereals. chips. drying for and greenhouse of heating for power thermal generated of utilization further with combusted is Opole consists in combustion. It the Nysa county predominantly straw makes upca.25%ofallirewoodfarmingintheprovinceOpole. as Włostowa and Nysa and occupy 29 ha of arable land altogether that woods of trees with short lifetime – willow) are located in such places (i.e. farms such county Nysa the In land. arable of 3% about occupy region investigated the for in plants plants such of Farms irewood engineering. power of farms from products and straw irewood, generation of10.1GWh/year. with MW 8.3 to amount plants power industrial and professional of power installed county.overall Nysa the the total, in In supply sources heat of individual of locations depicts 2 the Figure of [2]. communes province for Opole developed reports of basis the on evaluated was heat of production The communes. individual in clients for heat provide coal-ired, mostly houses, boiler some addition, In systems. for demands of town inhabitants is chiely supplied by municipal heating places where basic sources of heat supply are located. Thermal energy Fig. 3.UseofbiomassforheatgenerationinthecountyNysa Fig. 2.Locationsofbasicsourcessupplywiththermalpower In 2009 exactly 253153 TJ of energy was generated in Poland from The primitive manner for utilization of biomass in the province of province the in biomass of utilization for manner primitive The on based is biomass from production county Nysa the In of survey comprise shall analyses undertaken of phase next The nr 10/2013 • tom67

• potential ofbiomasscanbeclassiiedinthefollowingway[4]: of energypotentialforselectedtypebiomass[5]. makes comparisons and balances quantitative solution out carry to easier more much a such since year) (per GWh as energy thermal electric both and for unit power the offered of potential uniication assumes energy biomass by of Calculation power. of forms usable to energy chemical of conversion for used be to equipment of eficiency as well as types biomass available of properties chemical and physical about information as well as types biomass speciic of availability and crops the of yield on information in breeding), animal of amount lands commune, other and crops of (acreage data statistical available all foremost, and irst include, information necessary The assumptions. the and data input of series a calculations themselves always know need many to simpliications and has additional one potential of types power.and heat for commune speciic a of demand To satisfy these calculate to how way, quick and simple a in learn, to possible it makes due totechnicalandeconomicrestriction(Fig.4). such an algorithm should take account for gradual drop biomass, of the by potential offered potential energy the of estimation for algorithm applied to potential estimation it is irst necessary to develop a suitable on the type of speciic potential. To improve usefulness of the in many ways, procedure where selection of an adequate method chiely depends • • • • • • from derived green biomass)thefollowinginput informationmustbeavailable: is of type them other any to (similarly of straw cereal of case part In data. statistical a where assumptions, of adoption comprises computations of phase irst The commune. single a of area Calculations are always carried out for a conined territory, e.g. for the straw.cereal – type biomass selected arbitrary the of example the on • • Fig. 4.Diminishingofenergypotentialofferedbybiomassinpacewith Calculation of the potential on the theoretical and technical levels technical and theoretical the on potential the of Calculation Evaluation of potential offered by energy sources can be carried out (usually lessthantheeconomicpotential). from biomass and inally used for the purpose of power generation available (usable) potential – an amount of energy to be generated and tools(detailedanalysesofproitability) under cost-effective terms with consideration to economic criteria utilized reasonable be can that potential technical of part the is It rates of taxes, economic indices and amounts of inancial supports. process, fuel on depends – potential business) (market, economic generation process) power the of needs auxiliary market, the in available equipment of eficiency (limited restrictions technical to due reduced and tial technical potential – represents the part of the theoretical poten theoretical the of part the represents – potential technical tial isexclusivelyusedforpowergeneration cess) and also under the assumption that the total available poten pro generation the of imperfectness for account no (with 100% is plant generation the of eficiency that provided biomass from generated be can that energy of amount – potential theoretical yield ofdrops(orannualgrowth) availability In terms of practical utilization of the estimation results, the energetic acreage orcerealplanting The way how to determine theoretical energy potential is explained caloriic valueof biomass annual acquisition D , % P the levelofitsestimation , % W A , ha d , GJt I -1 , t/ha . • 941 - - - XIV Conference Environmental XIV Conference Environmental 942 • simpliication, as a set of nodes of set a as simpliication, least ofallpossibletrees. the is tree the in edges the all of weight total the that tree a such called so inding in consists way shortest the for Searching nodes. for the express, between distances and instance, numbers integer or real be may edges graph of w(e) to assign weight coeficients to each edge of the possibility the graph is graphs of feature by characteristic The [3]. nodes the means of the with edges the shortestroute 5. Applicationofthetheorygraphstoseekingfor Floyda-Murchland’s algorithm. tools, of or algorithm A number algorithm, Prim’s algorithm, Kruskal’s the a including of use with resolved be can task The edges. (graph points of graph to pre-assigned factors weight set to consideration with nodes) a between way shortest the inding It allows science. of branches many in application broad found has that as thetoolsuitabletoseekforshortesttransportationroute. serves and graphs of theory the on based is that algorithm optimizing on transportationofbiomass. of such an analysis consists in optimization of costs, including expenses associated with detailed economic analyses, where the key component and possible incomes achievable during the plant operation. Thus, it is of expenses necessary provision as well as for investment the for conditions resources inancial actual to consideration needs balance cost-effectiveness a Such terms. economic the under determination county aredepictedinFigure6. potential expressed in GWh/year for individual communes of the Nysa technical of Amounts investigations. detailed and analysis further for point starting a merely be the may estimation an to such of due results that fact as well as computations for adopted are data input and assumptions preliminary when phase initial the during approximations and simpliications substantial on rely to need the to due low rather is biomass combustionandgenerationofheat. for boiler a of eficiency e.g. conversion, energy of eficiency consider calculation of the technical potential is a point, the computations must When parameters. foregoing all of product a as calculated is potential Fig. 6.Technical potentialofstrawintheNysacounty, GWh/year [2] The theory of graphs is an independent mathematic discipline mathematic independent an is graphs of theory The h graf The an of application to devoted is study this of part further The in consist should procedure estimation the of step next The Anyway, as it was mentioned before, usefulness of such a procedure technical of value the straw) cereal (e.g. type biomass each For function that determines these weights. The weight coeficient e i in such a way that each edge begins and ends in any of G = (V , E , w(e)) a b cniee, ih certain a with considered, be can Minimum Spanning Tree(MSP) Spanning Minimum v i that can be mutually connected mutually be can that

, i.e. , (1) to the set of external be must edge the i.e. node, new a and tree the into included weight is sought, where the edge must connect a certain node already iiu Sann te bgn fo abtaiy hsn oe f the graph, for instance of node chosen arbitrarily from begins tree Spanning Minimum up the MST according to a predeined procedure. Construction of the road network (graph edges). The algorithm makes it possible to drawn interconnecting the and nodes) (graph generation energy for used is where and planted is biomass where locations relect that graphs for the presentedexampleprocedurestartsformedge Figure 7. The initial step consists in arbitrary selection of a node, for be chosen from all graph edges that are incident to incident are that edges graph all from chosen be { L L (for theexampleinplaceitis node that edge connected the spanning tree with the last node of the graph selected. The procedure is repeated until the last edge is selected and edge thatconnects( 2 +3=10 )(Fig.8). calculated minimum distance for the presented example is 2 + 1 + minimum the of form the spanning tree with the minimum possible in total weight of edges (the graph the into analysis optimizing list – for this graph it is the ( [ steps. The edge picked in that step is added to the set of set the to added is step that in picked edge The steps. (Fig. 7). The notation [ set ofgraphnodes. the to equal is that nodes of set the with obtained is tree the i.e. tree, process is looped until every edge in the set connects two nodes of the A,B,6 = {[ = v is supplemented with additional edges and the set adopts the content i , Fig. 7.SearchingfortheMinimumSpinningTree (MSP)withuse v For this study the Prim’s algorithm was applied to ind out the MST e u asm a once wihe udrce gah s in as graph undirected weighted connected a assume us Let The algorithm converts the initial graph that is subjected to the hn h sre ls i cetd sc that such created, is list sorted the Then The Prim’s algorithm operation is explained on a simple example simple a on explained is operation algorithm Prim’s The j } edge. In each step of the algorithm the edge with the minimum ]}. Next, the edge with the minimum weight is chosen from that A,F,2 ], [ L E,B,2 edges already incorporated into the tree during previous ], [ v i v . Then the edge with the minimum weight should E,D,3 i , v v i of thePrim’s algorithm. , v , j ) nodesanditsweightis j , w , ], [ A,E ] was adopted, which stands for the graph A,B,6 ) edge. In the subsequent step the set of ], [ nr 10/2013 • tom67 E,F,7 D ). ]}. This time the ( L w {[ = . v i . Let it be the be it Let . A,E,1 A,F L , [ ], and the and ) edge is A A,F,2 .

],

of strawdelivery 6. Procedure andresultsofsearchingfortheshortestroute s h iiil ae Te aus f acltd nry oeta are potential energy summarized inTable 2. calculated served of values analysis The the base. initial by the covered as communes the of areas the on located farms from sourced straw of potential energy theoretical determinedalready the and county Nysa of communes elected for performed were Computations section. previous the in described the optimizing analysis carried out by means of the Prim’s algorithm communes andsites ofstrawharvestingaredepicted inFigure9. annual demand for municipal heat required by these communes. Selected the exceeds potential energy determined the where +KF) +ŁM, +SK, Theoretical andtechnicalpotentialforenergygenerationfromstraw No. 1 tuhw+T6.630–34 65.56 4 +OT 3 Otmuchów 2 5 aołwc P 68 19–23 36.81 +PK Pakosławice 6 7 9 8 Fig. 8.TheresultsachievedbyapplicationofthePrim’s algorithm Nysa countywithspeciicationof communesandsitescovered This section of the study outlines the course and results from results and course the outlines study the of section This Further studies were limited to six communes (+OT,communes +PK, six +KM, to limited were studies Further azó PZ3.419–23 35.14 +PCZ Paczków ya+S8.030–34 23–26 81.60 52.16 +NS +GŁ Nysa Głuchołazy Kamiennik krsye+SK Skoroszyce ofnó K 16 23–26 11–15 71.62 36.70 +KF +ŁM Korfantów Łambinowice Fig. 9.Boundariesandadministrativebreakdownofthe Commune name harvested incommunesofNysacounty[2,4] marking code nr 10/2013 • tom67 Adopted by theoptimizationanalysis +KM Theoretical potential of straw, GWh 38.81 48.44 / year Technical potentialof straw, GWh 19–23 23–26 Table 2 / year

coeficients andwill beeliminatedanywaybythe Prim’s algorithms. direct connections, if any, would require assignment of very high weight connections would bypass other sites incorporated into the graph. Such the where edges edges such of ends the at located sites between path no road direct has no is there that sections fact the from results road It nodes. some with between sites individual connecting by where itisconvertedintoenergy. site locations the and commune each in the stored and gathered is biomass between where routes shortest the searching for algorithm f h otmzn aayi crid u fr niiul omns are communes individual summarized inTable 4. for out carried analysis optimizing the of osdrto t wih ceiins dsacs bten individual inhabited places. between (distances) with coeficients (+OT) weight Otmuchów to of consideration commune the in sites between route should beconvertedintousableformofenergy. is where site the to communes individual from biomass of delivery for routes (shortest) best the out ind to order in way foregoing the in up drawn graph the for repeated was analysis optimization The storage. biomass of sites to network road the through connected and chosen Then delivered. was biomass gathered the from energy be of generation for location the should (straw) biomass where destination the as appointed and analysis the by covered places the selected all was among commune from each of area the on site one phase second the For sites). selected edge the connect that of routes shortest (the sums weights associated the with along 9) (Fig. from communes in sites selected the for Treeout Spanning found Minimum was the one locations ofasystemforenergygeneration. possible the and communes individual in stored is straw where sites between route shortest the for seek to has one then and communes individual in harvested is straw where locations connects that route anwc 10.6 S Wójcice Sarnowice aijwc M Maciejowice Goświnowice Kałków omn O K P S Ł +KF +ŁM +SK +PK +KM +OT Commune Fig. 10.SearchingfortheminimumroutewithuseofPrim’s S algorithm ontheexample ofsitesappointedinthecommune s n cn e (i. 1 Tb 5 te rp ta i created is that graph the 5) Tab. 11, (Fig. see can one As the work does how explanation graphical the depicts 11 Figure The minimum sums of weight coeficients calculated as the results Figure 10 explains course of the algorithm that inds the minimum irst the During phases. two comprises analysis completed The shortest the of determination to aimed in analysis completed The ienm Symbol Site name w min Minimum sumsofweightcoeficients Weight coeficients 31.4 11.4 W G - - - - K 15.7 (road distancesinkm) communes, km of Otmuchów 14.1 42866.9 8.6 14.2 M W S K w i forspeciicroutesections 14.9 6.9 . 8.6 5.9 - - - 0320.9 20.3 S w min - - forindividual 7.7 -

• 943 Table 4 Table 3 S 39.0 31.4 w min

XIV Conference Environmental XIV Conference Environmental 944 • by theanalysis). 7. Finalconclusions rcdr t dtrie h ptnil f nry rdcin t the at production economic (business)level. energy of potential the determine to procedure associated withconversionofbiomassintousableformsenergy. cost-effective, for developed tools technical of and business use analysis with of possible units power engineering territorial enterprises by conducted be can that studies research further for points kickoff the as serve may level theoretical and technical the at potential biomass S weight minimum the of value total the as well as graph optimized a singlecriterion. than more of terms in route optimum the out ind to applied be can coeficients weight single than more however investigation, route between the selected points (e.g. sites) within the area under (usable) potential. available and economic respective and potential between theoretical gap the substantial a since low quite is level technical and ałwc aeKM Karłowice Małe Grądy produkcji energii) Złotogłowice (miejsce aołwc P Pakosławice aoieM MW Korfantów Malerzowie Wielkie Makowice Weight coeficients Fig. 11.ApplicationofthePrim’s algorithmtosearchingforthemini w min The Prim’s algorithms makes it possible to ind out the shortest the out ind to possible it makes algorithms Prim’s The The theory of graphs can be applied to the algorithm of optimization of estimation from result the as achieved been have that Results theoretical the at estimation from potential of usefulness The Table 5 summarizes weight coeficient for individual edges of the mum transportationroutesfordeliveryofbiomasstothesite (the shortest possible route that connects the sites covered sites the connects that route possible shortest (the ienm yblKM Symbol Site name w i

for individualroadsections(routedistancesinkm) G Z x x K of energyproduction 18.4 70-31-- - 3.1 - 17.0 6.2 - - - x - x x x ------15.5 G - - - - - 07xx14.4 x x 10.7 20.3 9.2 MW M P . - - 9.0 x 16.7 S K - Table 5 58.9 w

min - 7. 6. 5. 3. 4. References to seek for optimized sites (e.g. the site for conversion of acquired biomass intousableformsofenergy). of conversion for site the (e.g. sites optimized for seek to 2. 1. conferences.. energy the author or renewable co-author of 5 papers and posters at as well national as and of journals international technical and scientiic in papers 12 books, monograph application in chapters three processes, of author the is She processes. technological to sources engineering power optimization engineering, of power in strategies investment innovative for searching engineering, power thermal include interests scientiic of scope Production Engineering and Logistics, Opole University of Technology. Her TechnologicalInnovative of Chair of the Faculty at , Processesadjunct Mechanical a as the at thesis Technology.employed of PhD is University she Opole Currently the at her Faculty presented She Opole. of University the at Science Computer and Physics Mathematics, of as Faculty Wrocławthe as of well University the at Science Computer and Mathematics of author of 5 chapters in monograph books and two papers and posters at posters and papers national andinternational conferences two and books monograph in chapters 5 of author to manufacturing of cement. He is a scientiic editor of one monograph book, engineering, optimization of manufacturing processes with environmental particular engineering, process attention include Technology.interests research of of scope His University Opole Logistics, and Engineering Production of Faculty , TechnologicalProcesses Innovative of Chair the in assistant an as Engineering at the Opole University of Technology. Currently he is employed of renewableenergytotechnologicalprocesses. application processes, generation power of optimization engineering, power and generation heat include interests research his of scope The industries. result that have been implemented in great deal in the cement and limestone splendid with programs research 100 than more counts output scientiic His patterns. utility 2 registered and certiicates patent 11 received papers, and manuscripts 110 that more Technology.published of He University Opole Logistics, and Engineering Production of Faculty Innovative , of Technological Processes Chair the heads Technology. Currently of University Opole the at professor titular as employed been Technology.has of he 2007 Since WroclawUniversity the at Faculty PowerEngineering and Mechanical the at nominates for the professor position after Technology.presentation was of of He Sc.D. University thesis Wroclawin 2006 the at Fluids of Mechanics and TechnologyThermal of Institute the at 1985 in thesis PhD his presented He Mechanical and Power Engineering at the Wroclaw University of Technology. Opolska, Wydział Mechaniczny, 2005. biomasy z elektrycznej energii i ciepła dukcji TrinczekK.: 2005. ISBN83–204–3103–4. Skorek J., Kalina J.: Kalina J., Skorek edings ofECOpole.Vol. 3,No,1,2009.23-26 acu M, lrc R. Ulbrich M., Tańczuk Rolnicza, 6(104),2008,167–174. getycznego biomasy na przykładzie wybranej gminy woj. opolskiego e-mail: [email protected],phone:+48774498849 Faculty the from graduated Ph.D., – DUCZKOWSKA-KĄDZIEL Anna M.: Skrzyszewski A., Duczkowska-Kądziel R., Bartnik suitable tools with provided and expanded be can algorithm The e-mail: [email protected], phone:+4877449 8849 Mechanical of Faculty the from graduated M.Sc., – WASILEWSKI Marek e-mail: [email protected], of Faculty the from graduated Professor Eng.), (Sc.D., – DUDA Jerzy Ross K.A., Wright C.R.B.: Wright K.A., Ross skim Siejka K., Tańczuk M., TrinczekTańczukM., K., K.: Siejka 2005, ISBN83–0114–380–0. W.Guzicka, P.Guzicki, Warszawa,Wydaw.PWN, Zakrzewski. Naukowe Głodek E., Kalinowski W.:Kalinowski E., Głodek 2011, ISSN0013–7294. gazowo-parowe układy dwupaliwowe a energetyczny . Wyd. InstytutŚląski,Opole,2011,ISBN978–83–62105–80–9. Dobór parametrów pracy urządzenia do zdecentralizowanej pro zdecentralizowanej do urządzenia pracy parametrów Dobór Gazowe układy kogeneracyjne układy Gazowe seset f nrei ptnil f biomass. of potential energetic of Assessment Matematyka dyskretna Matematyka Odnawialne źródła energii w województwie opol województwie w energii źródła Odnawialne phone: +48 77 449 88 47 88 449 77 +48 Koncepcja szacowania potencjału ener potencjału szacowania Koncepcja nr 10/2013 • tom67 . Praca doktorska. Politechnika doktorska. Praca . . Wyd. WNT,Wyd. Warszawa,. . Z ang. przeł. E. Sepko- E. przeł. ang. Z . Eegtk, styczeń Energetyka, . Pakiet klimatyczno- Pakiet . Inżynieria Proce - - - -