The <str<strong>on</strong>g>12th</str<strong>on</strong>g> <str<strong>on</strong>g>Internati<strong>on</strong>al</str<strong>on</strong>g> <str<strong>on</strong>g>Symposium</str<strong>on</strong>g> <strong>on</strong> <strong>District</strong> <strong>Heating</strong> <strong>and</strong> <strong>Cooling</strong>,September 5 th to September 7 th , 2010, Tallinn, Est<strong>on</strong>iaproducti<strong>on</strong> is quite seas<strong>on</strong>al following the water flows.The amount of power produced by the Daugava riverHPP cascade is average 2.6–2.8 TWh [1] annually,reaching in the years, rich by spring floods <strong>and</strong> raineven 4.5 TWh [ [5].equipment with this capacity heat producti<strong>on</strong> bycogenerati<strong>on</strong> would be a maximum.More in detail the three HPPs, located <strong>on</strong> the river ofDaugava, form a sort of cascade with the relativecapacity of: Plavinas 870 MW, Kegums 263 MW <strong>and</strong>Riga 402 MW.Almost two thirds of hydro electricity is produced in thespring m<strong>on</strong>th of March, April <strong>and</strong> May. In this period thesupplies are from the hydro plants. In the high dem<strong>and</strong>winter seas<strong>on</strong> amount of electricity generated by hydroplants is relatively low.Looking the electricity supply statistics [1] the nati<strong>on</strong>alproducti<strong>on</strong> of electricity is around 10.0 PJ where the9.8 are produced using hydro energy <strong>and</strong> 0.2 PJproduced by wind energy. The net electricity import(including the amount of energy exported) is around10.8 PJ approximately the 50% of the nati<strong>on</strong>al supply.These figures shows the lacks of energy sources in thenati<strong>on</strong>al system <strong>and</strong> seems reas<strong>on</strong>able to foreseen amore large fracti<strong>on</strong> of other energy sources for theproducti<strong>on</strong> of electricity, the main questi<strong>on</strong> is <strong>on</strong> whichmethodology base this strategy .2.2 Well organized <strong>and</strong> developed DH systemLatvian heating primarily is performed <strong>on</strong> a centralizedbasis c<strong>on</strong>sequently c<strong>on</strong>sumers are grouped <strong>and</strong> theheat is supply from heat source which is established fora certain c<strong>on</strong>sumer group. The heat source power,depending <strong>on</strong> type of c<strong>on</strong>sumer group, varies from therange of kW to several hundred of MW. In generallower power can corresp<strong>on</strong>d to building groups,individual houses or even apartments heating.Residential <strong>and</strong> separate heating of individual housesbel<strong>on</strong>gs mainly from the decentralized heating. One ofthe benefits of district heating is centralizati<strong>on</strong> of heatload, which gives a possibility to increase the heatsource power <strong>and</strong> to form basis for the development ofcogenerati<strong>on</strong> power. For large heat c<strong>on</strong>sumers inLatvia (mainly heating systems in large cities like Riga)large cogenerati<strong>on</strong> plants are installed. The customerswho are not c<strong>on</strong>nected to a district heating cannot beprovided from this system. In the other regi<strong>on</strong>s far fromthe big cities the heat supply system is mainly based<strong>on</strong> district heating, c<strong>on</strong>sequently it means that thatthere possibility for a CHP development.CHP plants cover <strong>on</strong>ly a part of the total heat load. Therest of the load is covered by the peak load boilers.This means that following the total heat capacity of thesource, the potential heat capacity of cogenerati<strong>on</strong>should be assessed quantitatively. Heat capacity ofcogenerati<strong>on</strong> plant has to be selected so that operating179Fig. 3. <strong>Heating</strong> energy distributi<strong>on</strong> by cities in LatviaIf we are looking at the district heating divisi<strong>on</strong> of Latviaa huge difference can be seen in quantity of heatsupply in Riga <strong>and</strong> the rest of Latvia (see fig. 3)Two large CHP plants, Riga TPP-1 with an installedelectric capacity of 144 MW <strong>and</strong> Riga TPP-2 (390 MW),are located in Riga [5]. CHP plants are the main heatgeneratingsources of heating networks of Latviancapital. Power is produced mainly in cogenerati<strong>on</strong>mode, according to the heat–load curve.During the heating seas<strong>on</strong>, when there is a substantialdem<strong>and</strong> for heating <strong>and</strong> hot water, Riga CHP plantsproduce approximately 80% of the total annualproducti<strong>on</strong> volume, while during summer the volume ofproducti<strong>on</strong> reduces [5].Nowadays Riga CHP plants cover about 20% of thetotal annual power dem<strong>and</strong> of Latvia [5] .The main fuel used in Latvia biggest cities is naturalgas <strong>and</strong> the rates of thermal energy are 75% - 85% [3].In Riga <strong>and</strong> other cities where most part of the heat isproduced in cogenerati<strong>on</strong> cycle, the increase of rateswas not so high <strong>and</strong> currently (in the autumn of 2009)heat rates are lower that in the cities where wood chipsare used.From the thermal energy point of view seventy percentof the heat in Latvia is supplied from district-heatingsystems either from boiler houses or co-generati<strong>on</strong>:37% of the district heating in Latvia was produced bymeans of co-generati<strong>on</strong> plants [6]. This means that63% of the district heating is produced in boiler houses[6]. This means that there is potential to replace someof the heat plants with co-generati<strong>on</strong> units (Eightypercent of the district heating in Denmark is suppliedfrom CHP [6]).As for heat supply outside of Riga, the dominantthermal energy is produced in boiler houses with
The <str<strong>on</strong>g>12th</str<strong>on</strong>g> <str<strong>on</strong>g>Internati<strong>on</strong>al</str<strong>on</strong>g> <str<strong>on</strong>g>Symposium</str<strong>on</strong>g> <strong>on</strong> <strong>District</strong> <strong>Heating</strong> <strong>and</strong> <strong>Cooling</strong>,September 5 th to September 7 th , 2010, Tallinn, Est<strong>on</strong>iarelatively high proporti<strong>on</strong> of local fuel usage. Outside ofRiga CHP heat producti<strong>on</strong> rate does not exceed 5% [3](combined heat <strong>and</strong> power plant up to 4 MW of poweroperating in Bauska, Valmiera, Ogre, Vangazi,Daugavpils, Jelgava, Dobele, Grobiņa, Saldus,Ventspils, Ozolnieki, Ādaži, Lielvārde <strong>and</strong> Cesis).3. METHOD FOR EVALUATIONIn c<strong>on</strong>necti<strong>on</strong> to achieving sustainable development <strong>on</strong>global scale the correct <strong>and</strong> judicious use of resources,technology, appropriate ec<strong>on</strong>omic incentives <strong>and</strong>strategic planning at the local <strong>and</strong> nati<strong>on</strong>al levels isrequired. Therefore, choosing energy fuels <strong>and</strong>associated technologies for the producti<strong>on</strong>, delivery<strong>and</strong> use of energy services, it is essential to take intoaccount ec<strong>on</strong>omic, social <strong>and</strong> envir<strong>on</strong>mentalc<strong>on</strong>sequences. The research <strong>on</strong> criteria <strong>and</strong>/orindicators in order to underst<strong>and</strong> the best energeticchoice for Latvia is the first step for a correct energyplanning.gas), c<strong>on</strong>structive parameters of cogenerati<strong>on</strong> plant,parameters of heat energy c<strong>on</strong>sumers, heat loaddurati<strong>on</strong> curve, durati<strong>on</strong> of heat energy c<strong>on</strong>sumpti<strong>on</strong>levels, behaviour of energy end users, installedcapacity, energy efficiency of technologies,development of dem<strong>and</strong> side management factor, <strong>and</strong>other factors.3.2. Methodologies: EISD method <strong>and</strong> MOO methodIn the following paragraph the algorithm of ISED coreset tool, included in the c<strong>on</strong>ceptual framework used byUnited Nati<strong>on</strong>s Commissi<strong>on</strong> <strong>on</strong> sustainabledevelopment (CED), is shown. After is also shortlyreported the MOO methodologyThe EISD is an analytical tool developed which canhelp energy decisi<strong>on</strong> <strong>and</strong> policymakers at all levels toincorporate the c<strong>on</strong>cept of sustainable developmentinto energy policy. EISD core set is organized followingthe c<strong>on</strong>ceptual framework used by United Nati<strong>on</strong>sCommissi<strong>on</strong> <strong>on</strong> sustainable development (CSD).There are several methodologies that can be chosen toidentify the most suitable indicators, <strong>and</strong> in the sametime the choice is related <strong>and</strong> strictly c<strong>on</strong>nected <strong>on</strong>what the planning <strong>and</strong> c<strong>on</strong>sequently analysis is based<strong>on</strong>.3.1 Criteria <strong>and</strong> indicatorsThe methodologies can be chosen using severalmethodological tools <strong>and</strong> approach such us: multicriteriaor multi-objective optimizati<strong>on</strong> (MOO) [7],energy indicators for sustainable development (EISD)[8], Life Cycle assessment (LCA) [9, 10]. Each of thesemethodology start from different point of views <strong>and</strong>bases: MOO methodology is c<strong>on</strong>nected to bestoptimizati<strong>on</strong> choice of a certain number of variablesthat optimize certain objectives, EISD methodologyaims to evaluate (<strong>and</strong> c<strong>on</strong>sequently increase) thec<strong>on</strong>cept of sustainability based <strong>on</strong> social, ec<strong>on</strong>omical<strong>and</strong> envir<strong>on</strong>mental indicators, LCA aims to figure outthe global envir<strong>on</strong>mental load of a process <strong>and</strong>/orproduct taking into account the entire outflows <strong>and</strong>inflows c<strong>on</strong>nected (in terms of energy, substances <strong>and</strong>emissi<strong>on</strong>s), in this last case the indicators changedepending <strong>on</strong> type of Life cycle assessment methodschoosen.A summary of the factors that can influence CHPdevelopment in Latvia has been proposed in previouspapers. A. Volkova et al. [2] identify four main factors:political, geographical-climatological, legislative <strong>and</strong>technological.In general the total amount of electricity produced in acogenerati<strong>on</strong> regime <strong>and</strong> c<strong>on</strong>densing mode depends<strong>on</strong> c<strong>on</strong>structive soluti<strong>on</strong>s (e.g. technical soluti<strong>on</strong> for thebiogas‘ collectors), availability of source used (mainlyFig. 4. set of core EISD [8]There are 30 indicators, classified into threedimensi<strong>on</strong>s (social, ec<strong>on</strong>omic <strong>and</strong> envir<strong>on</strong>mental) <strong>and</strong>grouped in 7 big themes. There are four socialdimensi<strong>on</strong> indicators: three of them represent equity(accessibility, affordability, disparities) <strong>and</strong> <strong>on</strong>e healththeme (safety). The set of energy indicators ofec<strong>on</strong>omic dimensi<strong>on</strong> c<strong>on</strong>sists of 16 indicators. Thereare nine envir<strong>on</strong>mental dimensi<strong>on</strong> indicators in theEISD core list. The scheme of core EISD indicators ispresented in Fig. 4. The priority areas for energy sectoranalysis in Latvia can be were selected based <strong>on</strong> themain EU energy policy directi<strong>on</strong>s. These priority areasare as follows:Energy use.Energy intensities.End-use intensities of ec<strong>on</strong>omic branches.Energy security.Envir<strong>on</strong>mental energy impacts.The next Fig. 5 shows the linkages am<strong>on</strong>g theindicators selected for energy policy analysis in BalticStates. Relevant policy acti<strong>on</strong>s based <strong>on</strong> analysis180
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