Analysis of energy development sustainability: The example of the lithuanian district heating sector

Energy Policy 100 (2017) 227–236

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Analysis of energy development sustainability: The example of the lithuanian district heating sector

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Vaclovas Kveselis , Eugenija Farida Dzenajavičienė, Sigitas Masaitis Lithuanian Energy Institute, Breslaujos str. 3, LT-44403 Kaunas, Lithuania

A R T I C L E I N F O

A BS T RAC T

Keywords: District heating and cooling Sustainability Resource efficiency Carbon emissions Renewables Labelling

Today, sustainable energy development is one of key issues on European development agenda. The article describes one of sustainable energy development promoting tool - the eco-labelling scheme for district heating and cooling systems elaborated within the framework of Intelligent Energy for Europe program project “Ecoheat4cities” and partially funded by European Agency for Competitiveness and Innovation. The scheme is based on measured energy and environmental performance data of the district heating and cooling system and considers primary non-renewable energy usage together with the share of renewable energy and carbon dioxide emissions calculated using life-cycle analysis methodology. The “power bonus” approach is used for performance indicators of the heat generated in cogeneration installations. An analysis of a number of Lithuanian district heating companies using elaborated labelling criteria shows positive trends towards fulfilling Lithuania's energy policy goals. The labelling scheme gives opportunity for policy makers and urban planners to compare different heat supply options and decide upon exploiting district heating advantages and benefits for reaching EU energy and environment policy goals.

1. Introduction Common understanding of sustainable energy is provision of energy that meets the needs of the present without compromising the ability of future generations to meet their needs (Renewable, 2004). Two main trends in development of sustainable energy technologies are wider use of renewable energy sources and increasing energy efficiency. The first trend means replacement of fossil fuels with renewable energy sources such as wind, solar, hydro, and geothermal energies as well as biomass, which is the main renewable source in Nordic countries. The second trend, which is considered to be even more important, is raising energy efficiency in whole energy supply chain leading to reduced extraction, transporting and conversion as well as supply losses coupled with higher efficiency in consumers’ installations. The shortcomings of the use of fossil fuel becomes more evident due to declining global resources, political dictatorship of exporters, as well as the impact of increased greenhouse gases emissions on climate change. Biomass is the main renewable energy source, widely used in Lithuania, where besides above mentioned reasons, biofuel production also contributes to the development of regional economics, creates new jobs and reduces energy generation costs. The use of RES is constantly growing, so the demand for biomass also increases. This demand

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fosters the need for new policies, legislation, rising of awareness and creating new opportunities for forestry and agriculture sectors. Thus, one can clearly see that security of energy supply and climate change prevention are the main driving forces for bioenergy market development. Methodological background for sustainable technological development includes environmental, economic and social aspects of energy sector in various governing levels. Energy criteria for sustainable development were formulated by several global and European energy agencies (IAEAI, 2005), which involved development guidelines and methodology for impact assessment in social, economic and environmental dimensions. For the purpose of this work several criteria were analysed, which are most closely related to the use of biofuel and energy efficiency measures in autonomous and district heating (DH) technologies. Primary nonrenewable energy factor, carbon dioxide emission factor and renewable and recycled energy factor were selected as best describing purposes of this investigation i.e. data availability, transparency, explicitly and public acceptance. The paper deals with sustainability criteria, which is used for labelling purposes of DHC systems with the aim to promote sustainable development and enlarge public acceptance of DH, which is considered as the most efficient and environment friendly type of heat supply within towns and other densely populated areas. Scores used for

Corresponding author. E-mail addresses: [email protected] (V. Kveselis), [email protected] (E.F. Dzenajavičienė), [email protected] (S. Masaitis).

http://dx.doi.org/10.1016/j.enpol.2016.10.019 Received 8 June 2015; Received in revised form 4 October 2016; Accepted 16 October 2016 0301-4215/ © 2016 Elsevier Ltd. All rights reserved.

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ref s σ η

Nomenclature CHP DH DHC DHS EU GHG IEE LNG RES RES-E RES-H

Combined heat and power District heating District heating and cooling District heating system European Union Greenhouse gases Intelligent Energy for Europe Liquefied natural gas Renewable energy sources Renewable energy sources for heat generation Renewable energy sources for heat generation

Indexes aux hn cond hp chp Hi del ng dh nren el P ext R F ref i

Symbols E Q K R β EP ES f

reference power loss index power-to-heat ratio efficiency

energy heat emission coefficient renewable and surplus heat fraction ratio of any specified energy to total heat energy performance indicator energy source indicator factor

auxiliary heating network in condensation mode heat producer combined heat and power heating value delivered natural gas district heating non-renewable electricity primary energy external renewable and surplus heat fuel reference index for energy carrier

economic challenges faced during the past decades. It includes social, economic and environmental issues as well as development of techniques for decision-making process because traditional approach involving just economic or just environmental factors appeared to be noneffective for sustainability assessment of energy systems. Such situation led to the need of applying multi-criteria approach for analysis of complex systems, using a number of indicators for assessment of various aspects which are important for the future decision-making (Tsoutsos et al., 2009; Bazmi and Zahedi, 2011). These energy policy solutions, that meet sustainability requirements would help in selection of desirable sustainable and feasible technological solution (Häyhä et al., 2011). Among the most informational criteria for selecting the most advanced energy generators, using renewable and hybrid energy sources, energy generation costs and CO2 emissions are considered as the most important criteria (Goodbody et al., 2013). Implementation of such energy systems requires also technological assessment to define specific mix of resources, technologies and capacities for specific solution. Well-designed energy generating system using efficient technologies, should be the lowest costs solution, as well as reliable and sufficient to maintain appropriate living standards of consumers (Yılmaz and Selim, 2013). Various forms of broadening scope, primarily by focusing on electricity production by building combined heat and power plants, or using the alternative value of the technical system for new applications were investigated for DH systems in Sweden (Magnusson, 2012). Particular focus was made on strategic planning in district heating sector due to the fact that increased recovery of excess heat from CHP generation and industrial processes has the potential to reduce primary energy demand (Persson and Werner, 2012). Danish investigation shows that increased share of renewable energy sources reduces CO2 emissions in the Danish building stock, while at the same time increasing flexibility of the energy system. Their economic model calculates the potentials and costs of connection to expanded district heating networks depending on supply technology. At the same time CO2 emissions, fuel consumption and socio-economic costs can be reduced by expanding district heating (Möller and Lund, 2010). Energy efficiency improvement defined via demand-side energy savings is not less important, as social aspect such as reduction of

labelling are related to reference system, where above indicators meet minimal efficiency and environmental requirements which mean that such system meets the goals of EU 2020 energy policy. An analysis covers a number of Lithuanian DH companies. There are no district cooling networks in the country at present. Geographic location and climate conditions make Lithuania highly dependent on DH generation and supply effectiveness as widely developed DH sector covers heating needs of about half of population and up to 90% of heat demand in public and residential houses of largest cities. The main goals of Lithuania's heat sector are to ensure reliable, secure and qualitative heat supply to all consumers with the least costs; to promote competition between various types of fuel and heat generation technologies; to improve the efficiency of heat generation, transmission and consumption; to promote wider use of indigenous fuel, biomass and other renewables; and to reduce negative impact to the environment (Ministry of Energy, 2016). Recently not secure natural gas supply from single Russian supplier has fostered DH conversion to biomass fuel as the most urgent priority, thus adding to implementation of nearly all above defined goals. At the same time, the new liquefied natural gas (LNG) terminal started operating in 2014 in the Baltic Sea port Klaipeda thus increasing supply security and bargaining power of Lithuanian natural gas importers. Lithuania's Government supports these actions via use of EU Structural Funds for modernization of existing and construction of new biomass boilerhouses and CHP plants, also via establishment of biomass fuel trading system as well as via establishing of new extended environmental requirements in national legislation. 2. Background Energy consumption is increasing fast due to growing energy demand in all countries and especially in those that are developing, which also leads to growing energy costs and growing GHG emissions. Another factor is diminishing fossil fuel resources. Those two factors have raised global interest in the use of renewable energy sources and in the design of sustainable energy systems, which use renewable sources (Baños et al., 2011). The new concept of sustainable development came into practice in planning and reforming of energy sector as a response to political and 228

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largest global CO2 reduction potential, about 300 kg tonne/year of CO2 for Sweden, and the CO2 reduction potential is highly dependent on the marginal electricity production (Difs, 2010). Minimum cost per unit of greenhouse gas reduced is required to economically sustain a renewable energy plant, and is the most appropriate social criterion for choosing among multiple options (Searcy anf Flynn, 2010). The potential for applying various promotion measures for RES usage in heat sector was discussed in (Connor et al., 2013) evaluating all pros and cons. Good practice examples can be discovered in Germany – these are Renewable Energies Heat Act (EEWärmeG) and government grants. The two measures not only ensured short-term success in heat market, but also turned to long term mitigation of climate change and saving of energy resources (Nast, 2010). German scientists are also among the most active in the investigations related to detailed energy system analysis of the complete national energy system, which enables predicting fuel demand, CO2 emissions and generation costs for various heating options, including district heating as well as individual heat pumps and micro combined heat and power (Lund et al., 2010). We can state that increasing the share of indigenous and renewable energy sources in heat and power generation leads to improvement of energy security, diversification of fuels and mitigation of climate change (Raslavičius, 2012). Financial issues are not less important while addressing private investments, as it shows that investors still find renewable energy systems not so attractive and we do not fully understand yet what mechanisms should foster more investment into this type of energy (Masini and Menichetti, 2013). One of the possible incentives might be better understanding that renewable energy resources appear to be the one of the most efficient and effective solution for sustainable energy development (Ahiduzzaman and Sadrul, 2011). Country's energy policy should be focused on substantial modernization of existing energy systems, their reorganisation and creation of appropriate institutional structure together with setting up necessary legal basis. The most important factors stimulating development of distributed generation in Lithuania are the international obligations to increase contribution of power plants using RES into electricity's production balance; the development of small (with capacity less than 50 MW) cogeneration power plants, and implementation of energy policy which promote renewable energy in DH systems (Miskinis et al., 2011) as heat market infrastructure will play a key role in successful implementation of above strategy by switching from recently dominating fossil fuels to biomass fuel and other renewable sources (waste, solar heating). The above analysis indicates increased interest in RES usage and highlights various aspects of sustainability such as:

energy bill is encountered here. A possibility to increase the share of renewable energy appears at the same time without specific investment into new generating capacities. Thus, improvement of energy efficiency reduces greenhouse gases emissions and mitigates climate change (Harmsen et al., 2011). On the other hand, end-use energy savings and DH expansion combined under the existing energy system improves the overall fuel efficiency of the system (Sperling et al., 2012). Heating sector and especially district heating is still highly dependent on fossil fuel. On the other hand DH and/or DHC are energy sectors where implementation of renewable energy sources could be the most effective. Estimated heating and cooling processes account for 40–50% of global energy consumption in domestic, commercial and industrial sectors (IEA, 2012). European Union have provided financial support for implementation and maturation of RES technologies for electricity generation (RES-E), however, we can notify that considerably less funding was assigned for development of heat generation (RES-H) technologies. Some EU Member States, especially those with rather severe climate conditions, historically produce large amounts of heat using renewable sources, which is almost entirely biomass. Eastern European countries also have widely developed district heating sectors, which partially use biomass for energy generation (Connor, 2013). Benefits from the use of RES in heating sector can be clearly expressed in economic, environmental and social terms due to the possibility of combined heat and power generation and ability to accept excess heat from industries. Heating sector can reduce consumption of biomass, thus leaving biomass for other sectors and still enabling a 100% renewable energy system. The analysis of heating technologies shows that DH systems are important in limiting the dependence on biomass and creating cost effective solutions (Mathiesen et al., 2012). Some sophisticated technologies can be interesting for DH suppliers in the future, such as biomass gasification, which could be a vital measure to reach the 2020 targets for greenhouse gases and renewable energy, given continued technology development and long-term policy instruments (Difs et al., 2010). Among others one of the most promising commercially available technologies is cogeneration. Cogeneration systems produce both electrical energy and thermal energy from the same primary energy source (Thilak Raj et al., 2011). The optimal coefficient of the share of cogeneration depends mainly on the ratio of heat required to get hot tap water in relation to heat needed for space heating and ventilation (Ziębik and Gładysz, 2012). If we are discussing the use of renewables in heat and power generation, we should notify that the main source here is biomass derived energy. Biomass energy contributes to energy consumption and reduced dependence on imported fossil fuels, it also develops sustainable energy systems, based on RES and thus contributes to reduction of greenhouse gases emissions (Srebotnjak and Hardi, 2011). The evaluation criteria in this case include GHG emissions, particulates emissions, maturity of technology, traffic load, and locally available sources (Ghafghazi et al., 2010). Besides technological aspects, environmental issue related to GHG emissions is an extremely important assessment criterion for sustainable development of district heating sector. The sources of CO2 emission has been of great interest to researchers and/or policy makers within on-going efforts to reduce the emissions due to serious CO2's environmental impact (Bilgili, 2012). Bioenergy is regarded as costeffective option to reduce CO2 emissions from fossil fuel combustion. However, it is still not quite clear which wood biomass conversion technology reduces fossil CO2 emissions at the lowest costs (Schmidt et al., 2010). Some renewable energy technologies can simultaneously achieve efficiency in the energy conversion and in the conversion of carbon. These renewable energy technologies can generate useful energy and remove CO2 from the atmosphere, either by direct capture and recycling of atmospheric CO2 or indirectly, by involving biofuels (Budzianowski, 2012). The DH system with natural gas-fuelled CHP plant has 30% lower system cost than the CHP system using biofuel. Nevertheless, natural gas combine cycle CHP based system has the

• • • • • • • •

Criteria for choosing of most advanced heat generators, Importance of end use energy efficiency, Advantages of DHC technology for RES expansion, Advantages of biomass based CHP, Environmental issues related to DHC development, Benefits from RES promoting policies, Financial issues, and Lithuania's RES policy

Demonstration of DHC system benefits against individual heating solutions is important for policy makers, city infrastructure planners and publicity for maintaining existing and attracting new customers. Various aspects of sustainable energy development discussed above led to idea of DHC system labelling which should disclose main technical and environmental characteristics in clear and transparent way, thus allowing comparison with other heating and cooling alternatives. Nevertheless, important socio-economic aspects and end use energy efficiency were left outside the labelling scheme, as they depend on fluctuating fuel prices, support policies and other factors which are not DHC system-specific values or are outside the DHC system boundaries. 229

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technologies makes serious challenge for DH in terms of competition, especially in small towns due to low heat demand density, resulting in higher heat generation and distribution costs. Possibilities for new micro CHP solutions appear in residential, administrative and other buildings. Initially approximately 30 various criteria were considered for the use in the labelling scheme. The main requirements for criteria selection were that indicators used must be clear and measurable. Another requirement was that criteria are to be comparable with those used in other energy efficiency labelling schemes thus enabling comparison with alternative technological solutions. On the other hand only the limited number and easily understandable criteria can be accepted by stakeholders. And last but not the least – the criteria should be sound with and reflect the main energy and environment policy targets of EU member states. The criteria selection was performed, first, rejecting interdependent criteria and then choosing the most appropriate ones. Three selected labelling criteria – environmental (CO2 emission factor), efficiency of resources consumption (primary energy factor), renewability (renewable and recycled energy factor) – reflect the goals of the new political strategy EU2020 and thus allows interested countries all over Europe to prove that district heating and cooling may add to reaching EU energy aims and present DHC systems to be competitive and viable option in European heating and cooling market. The created labelling system provides method for measuring sustainability and efficiency of DHC systems by using available and verified knowledge and resources. For assessment of modernization options for heating installations one should assess local environmental and socio-economic issues. This requires information not only on heat costs at current DHS but also at future modern ones. On the other hand, renovation strategies for DHC systems of small towns should be based on economic costs analysis. For this purpose “green field” heat supply costs from DHC systems and autonomous heating/cooling sources should be compared. As heat supply is closely related to electricity and fuel sub-sectors, power, natural gas and other fuel costs, it has inevitable impact on analysis

3. Methodology and modelling Multiple criteria analysis of energy system usually contains both measurable data and expert evaluations, which are subjective and depend on the knowledge of invited experts. Even for measurable values (energy consumption, economic indicators, impact on environment by harmful emissions) there is no single methodology for importance estimation of each value because of different units used. Therefore it is hardly possible to find single criteria for energy system sustainability, properly reflecting manifold aspects of sustainability. Besides, there are big differences between heating and cooling systems installed in buildings and DHC systems where network losses occur. On the other hand, DHC enables using co-generation and/or alternative fuel such as solid biomass (chips) instead of oil fuel or natural gas, which is technically and economically less feasible in autonomous building heating systems. Furthermore, new technologies appear on the market which can be used in buildings for autonomous heat/cold and power generation. The new technological solutions penetrating current heat market are: gas turbines, reciprocating engines, biofuel gasification, etc., for heat and power generation. The project Ecoheat4cities, partly funded under Intelligent Energy for Europe (IEE) program, was dedicated to promote consciousness and science based public acceptability of DHC systems by establishing voluntary eco-labelling scheme. Such labelling provides information on main energy and environmental parameters of particular DHC system. For this purpose labelling criteria must be transparent, easy understandable for public and policy makers therefore should be based on real (documented) figures characterizing DHC system performance. This is applicable also for newly developing systems; in this case design data are used for labelling. Such ex ante label is temporary and validation is required when real technical performance data becomes available. The model was developed within this investigation for comparison DHC and autonomous heating and cooling, considering usual and innovative technologies in typical buildings, as well as technologies used in DHC systems. Fast development of new heat generation

Fig. 1. System boundaries for energy efficiency rating of DH system.

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sions factor KP, dh, nren; and, in case technological solution uses combined fuel (renewable and fossil), renewable energy fraction R. For assessment of DHC system efficiency 3 levels of indicators can be used: mean default EU values, national, and case specific for energy system (boiler-house or CHP plant). The model here uses default fuel values, which were adopted on EU level under standard EN 15603:2007. There are two descriptions of primary energy factor: general primary energy factor and non-renewable primary energy factor (EN 15603:2008, 2008). The first one accounts all energy resources supplied to the system and is used for technical energy efficiency estimations. The second, non-renewable energy factor shows energy input from non-renewable sources (uranium or fossil fuel). Nonrenewable primary energy factor is used for labelling purposes. This factor is estimated using standard EN 15316-4-5 (EN 15316-4-5, 2007) in case national estimation rules are not provided. Primary non-renewable energy factor fP, dh, nren (primary energy factor for supplied heat/cold) defines input of all non-renewable energy resources for heat delivered to customer sub-station MWh/ MWhdh:

Table 1 Data for reference district heating system. Obligatory σ ηchp

0.53 0.87

ηhp,ng

0.9

ηhp,biogas ηhp,wood

0.9 0.85

ηhn ηel,cond,coal

0.9 0.442

βaux βchp

0.04 0.75*(1β R) 1-βchp-βR

βhp,ng

Power-to-heat ratio overall efficiency of the CHP-unit (0,3 electric + 0,57 thermal) overall efficiency of the heat produced from natural gas overall efficiency of the heat producer using biogas overall efficiency of the heat producer using wood chips efficiency of the heating network electric efficiency of a coal power plant in condensing mode from 2011/877/EU ratio of auxiliary electricity to produced heat ratio of cogenerated heat to total heat ratio of heat from natural gas to total heat

Adaptable in a national annex βR 23% national target for market-share of renewables (Lithuania) βR/2 ratio of heat from biogas to total heat βhp,biogas βhp,wood βR/2 ratio of heat from wood chips to total heat fP,coal 1.1 primary energy factor for coal fP,ng 1.1 primary energy factor for natural gas fP,biogas 0.2 primary energy factor for biogas (refined secondary biofuel) fP,wood 0.1 primary energy factor for wood chips (primary biofuel) fP,el 2.6 primary energy factor for electricity KP,coal 370 primary emission coefficient for coal KP,ng 230 primary emission coefficient for natural gas KP,biogas 40 primary emission coefficient for biogas (refined secondary biofuel) KP,wood 20 primary emission coefficient for wood (primary biofuel) Kel 420 primary emission coefficient for electricity

fP, dh, nren =

∑i Ei⋅fP, nren, i + Qext ⋅fP, nren, ext + (Eel, aux − Eel, chp )⋅fP, el ∑j Qdel, j

here Ei – energy content of input to the system of energy carrier i in MWhHi; fP, nren, i – non-renewable primary energy factor of energy carrier i; fP, nren, ext – non-renewable primary energy factor of the external heat supply; fP, el – primary energy factor of electricity. Fuel consumption assigned to heat generated in CHP installations are estimated using (CWA 45547:2004, 2004), in which is considered that primary energy volume consumed for heat generation and emissions correspond the difference between fuel used in CHP installations and mean statistic volume of fuel consumed for generation of electricity only. Carbon dioxide emission factor KP,dh,nren defines the fuel supply chain CO2 emissions, when one energy unit (lower heating value) of a fuel is extracted, refined, stored, transported, converted and finally delivered as useful heat to consumer, kg CO2/MWh. Non-renewable primary energy CO2 emissions factor shows emissions level of district heating system occurring due to use of nonrenewable energy resources:

results of heat supply systems. The “power bonus” method was chosen for primary energy and CO2 emissions calculation in CHP installations within DHC system bearing in mind that major share of electricity in EU countries is produced by condensing power plants using fossil fuel. This method provides a carbon credit for electricity generated by the CHP plant. The carbon credit is equal to the amount of carbon that would be emitted from a condensing power plant using the same fuel as the CHP plant in generating a unit of electricity. For DHC system labelling purposes first one should define boundaries of the heat supply system. This includes area with heat sources and heat consumers to which heat is supplied from single heat supply network, and which is restricted by building heat sub-stations. All fuel and energy consumption as well as heating and cooling generation volumes in the area are evaluated. Energy as system input is estimated using specific conversion factor, showing the amount of energy in specific fuel converted into useful energy (heat, electricity, coolness). Here we also regard heat losses in supply network and other types of energy used for heat generation including energy used in fuel extraction, preparing, processing and transportation as well as electricity consumed in boiler-house and for circulation of heat carrier in the network (Fig. 1). In case it is not possible or not expedient to estimate connected installations together with networks, these can be divided into subsystems. Thus several subsystems appear; some of them consume heat, other supply it. Heat from suppliers’ subsystem should be assessed using its own energy indicators. However for subsystem of consumers this is external heat supply, which is regarded as energy input Qext with specific energy efficiency indicators. While assessing competitiveness of technologies using renewables with those using fossil fuel one should evaluate important sustainable energy indicators, such as: primary energy factor fP, dh, nren , CO2 emis-

KP, dh, nren

⎛ ∑i Ei⋅KP, nren, i + Qext ⋅Kext + Eel, aux⋅Kel − ⎜∑i ⎝ = ∑j Qdel, j

Eel, chp, i ⋅ KP, nren, chp, i ⎞ ηel, i

⎟ ⎠

here: KP,dh,nren – non-renewable primary CO2-emission coefficient of district heating in kg/MWh; Ei – energy content of energy carrier i input to heat production and cogeneration unit in MWh; KP,nren,i – non-renewable primary CO2-emission coefficient of energy carrier i in kg/MWh; Qext – energy content of heat from external source in MWh; Kext – non-renewable CO2-emission coefficient of external heat in kg/MWh; Kel – non-renewable CO2-emission coefficient of electricity in kg/ MWh; Eel,chp,i – cogenerated electricity produced with fuel i in MWh; KP,nren,chp,i – non-renewable primary CO2-emission coefficient of energy carrier i that was used in CHP-unit in kg/MWh; ηel,i – electric efficiency of fuel i from 2011/877/EU. 231

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Qdel,j – delivered heat to customer j in MWh.

using the above rules in this investigation. Companies seeking certification of their DH systems must apply to national labelling bodies and follow certain procedures. In this investigation analysed DH companies in some cases operate more than one DH network. Therefore the investigation results can’t be treated as real labelling procedure which is applicable for isolated DH network. Since the fast development of bioenergy use the three years development period in district heating sector was selected: the years of 2010, 2012 and 2013. Fast development of bioenergy projects started during this period. 28 Lithuanian DH companies were analysed, where required data about their performance indicators was available through data basis of Lithuanian District Heating Association. Analysed companies supply more than 90% of total heat delivered by DH sector in Lithuania; therefore the results reflect well the DH sector of the country. Figs. 2–4 present the calculated values of 3 sustainability factors listed above and demonstrate correspondence to labelling classes of 28 analysed Lithuanian DH companies. Fig. 2 presents that 19 of 28 companies meet the requirements of I and II energy efficiency classes in terms of primary non-renewable energy factor, where fp < =0.78 in the year 2013. Besides, some improvement could be observed during the past four years as the number of companies meeting energy efficiency target was 17 out of 28 at the beginning of the year 2010. In this figure even 15 companies meet the primary energy requirements of labelling class I, where fp < 0.39 (where in the year 2010 there were only 8 such companies). We can also see companies with minor or no improvement of this factor (companies numbered 18, 19, 21 and 23 on the chart below). Improvement of primary non-renewable energy factor by majority of companies is explained not only because of the switching to biomass fuel which have lower primary energy factor, but also by implementing advanced technological solutions improving efficiency of heat generators, such as installation of condensing economizers in gas and biomass fired boiler-houses. On the contrary, companies not investing in biomass fuel installations have worse figures of primary energy consumption. The use of cogeneration even using fossil fuel also enhances primary energy factor. This is due to fuel savings for power generation comparing with the average figure of whole electricity production. However, increasing electricity generation volumes today is problematic due to low electricity market price and limited financial possibilities to provide adequate support for electricity production in already existing CHP plants by applying preferential feed-in-tariff. Therefore CHP plants in big cities are under loaded. Fig. 3 clearly shows that situation is a bit worse with respect to carbon dioxide emissions factor, as there were only 11 efficient companies, with Kdh < =215 kg/MWh in year 2010 and 15 companies in year 2013 meeting the national target. Besides, improvement of this factor can be seen and the number of companies fitting to class I grew from 1 in 2010 to 3 in 2013, where Kdh < 107.5 kg/MWh. One can see that companies having high primary non-renewable energy factor also have high CO2 emission values (companies marked with number 6, 19 and 21 on the charts). The third factor, renewable energy fraction, shows renewability of the DH system resources used, and efficient system in Lithuania's case is a system where renewable and recovered resources share exceeds at

Criterion of renewable and recycled energy fraction R is introduced in order to specifically support the use of renewable and recycled energy in district heating systems. The criterion visualise the use of non-fossil fuels and heat sources from industry which otherwise would be wasted (released to environment). The criterion is calculated as the percentage of renewable and recycled energy content of the total energy input (fuels) delivered to the site where they are finally converted. Indicator R is the percentage share of renewable sources and (or) recycled heat sources in all heat volume delivered to consumers. In case electricity is used as energy input (e.g., heat pumps and electric boilers) 20% of this electricity is considered as renewable/surplus energy corresponding to the share of RES in total power production across the EU (hydro, wind, solar, biomass, etc). Renewable and recycled energy fraction R is calculated according to the following formulae: n

Rdh = 100 ×

∑i =1 EK (i )⋅RK (i ) EK

here: R – share of renewable and recycled energy of the district heating system, %; RK(i) – renewable and recycled energy factor for fuel i, between 0 and 1; EK(i) – energy content of fuel i allocated to DH (lower heating value); and EK – energy content of all fuels allocated to DH (lower heating value). Scale used for labelling purposes is linked to reference system, where indicators meet minimal efficiency and environmental requirements and those, where the system meets the goal of EU 2020 energy policy (Table 1), as well as with regard to recommendations in 2011/ 877/EU and 2008/952/EC. Primary energy factor is estimated using the formulae:

fP, dh, ref =

(1+σ )∙βchp ∙fP, coal ηchp ∙ηhn −

+

βhp, wood ∙fP, wood ηhp, wood ∙ηhn

+

βhp, biogas ∙fP, biogas ηhp, biogas ∙ηhn

+

βhp, ng ∙fP, ng ηhp, ng ∙ηhn

(σ ∙βchp − βaux )∙fP, el ηhn

Primary energy carbon dioxide emission factor is calculated using the formulae:

KP, dh, ref =

(1+σ )∙βchp ∙KP, coal ηchp ∙ηhn βhp, ng ∙KP, ng ηhp, ng ∙ηhn

+

+

βhp, wood ∙KP, wood ηhp, wood ∙ηhn

+

βhp, biogas ∙KP, biogas ηhp, biogas ∙ηhn

+

βaux ∙Kel (σ ∙βchp − βaux )∙fP, el − ηhn ηhn ∙ηel, cond , coal

Depending on national target for market-share of renewables in final energy consumption by the year 2020, different reference indicators are used for different EU countries (this target indicator is 0.23 for Lithuania according to the Annex I of Directive 2009/28/EC). Labelling scale is divided into seven classes. Indicators for reference system reflect the limit between classes two and three. The primary energy and carbon dioxide emission factors use linear scale, and renewable energy fraction use non-linear scale (Table 2). The ranges of energy and environmental indicators for Lithuanian DH systems, defined using above rules, are presented in Table 3.

Table 2 Rules for determination of energy classes.

4. Results Informal labelling of Lithuania's DH companies was performed 232

Class

fP,dh and Kdh

Rdh

1 2 3 4 5 6 7

EP < 0,5 ref 0,5 ref ≤ EP < ref ref ≤ EP < 1,5 ref 1,5 ref ≤ EP < 2 ref 2 ref ≤ EP < 2,5 ref 2,5 ref ≤ EP < 3 ref 3 ref ≤ EP

ES > 0,5·(100 – βR) + βR 0,5·(100 – βR) + βR ≥ ES > βR βR ≥ ES > 0,8 βR 0,8 βR ≥ ES > 0,6 βR 0,6 βR ≥ ES > 0,4 βR 0,4 βR ≥ ES > 0,2 βR 0,2 βR ≥ ES

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effectiveness of both implemented measures the multi-criteria approach should be applied, as any planning and decision-making in this field have to tackle multi dimensionality of the system design problem and the complexity in the technical, economic and social criteria. The above presented informal labelling results indicate rapid positive changes in sustainability of Lithuanian DH sector. However, we cannot say the same about building sector which is the largest heat consumer. Different from some neighbouring EU countries (Sweden, Denmark) basic traditional promotion measures are still not implemented in Lithuania (energy or fuel taxes, obligatory audits, state support programs) to improve energy consumption efficiency. Building stock rehabilitation has started from renovation of public buildings (schools, administration buildings, hospitals, etc.) and hundreds of residential block houses renovation projects started during recent years. This became possible after several governments’ decisions aimed to solve problems with insolvent residents and to reduce financial burden for occupants. However, the process should be fostered bearing in mind presence of more than 30 thousand such buildings in Lithuania. Measures taken on consumption side, basically building renovation, still are sluggish. Reduced heating demand especially during cold season of a year would positively affect sustainability of DH systems due to less fossil fuel required for covering peak loads, thus improving primary non-renewable energy factor, lower carbon dioxide emissions and larger share of renewables. DH and/or DHC is one of energy sectors where implementation of renewable energy sources could be the most effective and increase the sector competitiveness and viability in European heating and cooling market. Here eco-labelling using multiple criteria supports sustainable development of district heating sector via raising public acceptance of district heating, which is considered as the most efficient and environment friendly type of heat supply. Proposed labelling scheme is still missing one important criterion – economic, which can be expressed by heat price. Lithuanian experience shows that in many cases switching from fossil fuel to biomass also reduces heat price and in most cases heat price here is lower than in the companies using fossil fuel – natural gas. Fig. 6 shows heat price tendencies for the past four years (2010–2013) in different DH companies. The trend lines of prices clearly indicate dependence of the heat price versus share of renewable and recycled energy in total energy input. Different slope of trend lines can be explained by the fluctuation of fuel prices; the difference in heat prices is larger when fossil fuel price (e.g. natural gas) is larger. The largest difference between natural gas and biomass price appeared in 2012, and here we can see the largest benefits of biomass. This impact was lessened in 2013 when natural gas price was reduced (Table 4). We should also notify that wider use of biomass permits keeping

Table 3 Rules for determination of labelling classes. Target energy efficiency fP,dh,ref=0.78, carbon dioxide emissions Kdh,ref=215 kgCO2/MWh and percentage of renewables βR=23%. Class

fp

Kdh

Rdh

I II III IV V VI VII

fp < 0.39 0.39≤fp < 0.78 0.78≤fp < 1.17 1.17≤fp < 1.56 1.56≤fp < 1.95 1.95≤fp < 2.34 fp > 2.34

Kdh < 107.5 107.5≤Kdh < 215 215≤Kdh < 322.5 322.5≤Kdh < 430 430≤Kdh < 537.5 537.5≤Kdh < 645 Kdh > 645

Rdh > 61.5 23 > Rdh > 61,5 18,4 > Rdh > 23 13,8 > Rdh > 18,4 9,2 > Rdh > 13,8 4,6 > Rdh > 9,2 4,6 > Rdh

least 23%. In fact, Lithuanian energy strategy has set higher renewability factor value for DH sector, than that used in informal labelling. On average this factor should meet requirements of the labelling class I which means that more than 60% of energy input should come from renewable and recovered energy sources. Fig. 4 shows that the most companies (20 of 28) have met this requirement in 2013 and this number was 19 in 2010. The number of companies, corresponding to I labelling class, when Rdh > 61.5%, increased from 13 in 2010 to 14 in year 2013. The same companies with low primary energy and high CO2 emissions (number 19 and 21) have also smaller renewability factor. We should notify that the whole DH sector in Lithuania is rather efficient – 12 companies of 28 investigated, meet I-II labelling classes in terms of all three factors. These are companies, which use mainly biomass for heat generation and have new and efficient boilers with condensing economizers. Heat suppliers with labelled systems are allowed to use unified EU labels with coloured lapels. The number of coloured lapels shows accordance of each performance criteria to specific labelling class. More exact figures are also provided on the label. Label example for one Lithuanian DH system labelled during pilot labelling is shown in Fig. 5. We should notify that labelling indicators in other systems, which uses fossil fuel, e.g. natural gas, including DH systems of large cities, where renewable makes only small share of energy resources, are significantly worse. This should be the main concern of further development in DH sector for coming years.

5. Conclusion and policy implications Sustainable energy development in DH sector is based on replacement of fossil fuels by RES and improvement of energy efficiency on both production and consumption sides. For assessment of the

Fig. 2. Primary non-renewable energy factor.

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Fig. 3. Carbon dioxide emission factors.

Fig. 4. Renewable energy fraction.

Fig. 5. Example of the label for one of Lithuanian DH systems and translated information.

in Lithuania is not exploited due to low market price of imported electricity and limited support possibilities for this technology. Thus, there is still room for further energy efficiency improvement and lessening harmful impact from energy production to environment. Three criteria are used for labelling: environmental criterion – CO2 emission factor; resources consumption efficiency criterion – primary energy factor; and renewability criterion - renewable and recycled

more stable heat prices comparing to companies using mainly fossil fuels, because biomass price is less sensitive to fluctuation of international prices for energy resources which is the case for natural gas. DHC enables to use co-generation and/or alternative fuel such as solid biomass instead of fossil fuel – heavy fuel oil and natural gas, which is technically and economically not feasible in autonomous heating systems in the buildings. Nevertheless, existing CHP potential 234

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Fig. 6. Heat price tendencies depending on the share of renewables.

and development of innovative features. Promoting primary energy factor as the basis for evaluating the efficiency of end-user solutions, and creating a level playing field on the market are amongst the priority areas of attention. Although heat is a difficult commodity to regulate, the label can be an effective alternative. A collective energy solution for the benefit of all requires local government and urban planners to take on a pivotal role. Specifically, upgrading of the public building stock should go hand in hand with the establishment of heating and cooling plans. Guidelines distributed among DH companies contain description of specific improvements and good practices for making the systems more attractive thus widening the potential market expansion especially in countries with low share of DH technology. As for DH companies a comprehensive approach to local energy supply and demand and the development of eco-districts will help to keep costs for the citizens at affordable levels. The Central and Eastern European Member States feature some of the oldest and also largest systems, such as in Lithuania, where more than half of the population's heat needs are covered by district heating systems.

Table 4 Average fuel prices, €/toe. Year

2010 2012 2013

Average fuel price, €/toe Heavy fuel oil

Natural gas

Biomass fuel

339 417 540

368 535 460

181 223 170

energy factor are used together with the scale for labelling which is related to reference system. Above indicators of the reference system meets minimum efficiency and environmental requirements which mean that such system meets the goals of EU 2020 energy policy. The criteria are related to national circumstances and policy goals. Common labelling criteria for all EU member states might be developed, however very big gap exists between countries in the use of renewables starting with the United Kingdom with several percentage of renewables and small share of DH in total heating to Sweden having well developed DH sector where renewable and recycled energy make almost half of total energy input. Labelling indicators disclose 3 sustainability factors, and correspondence to labelling classes. Informal labelling shows, that nearly 2/ 3rds of all DH companies in Lithuania meet the requirements of I and II labelling classes in terms of primary non-renewable energy factor, where fp < =0,78 in year 2013. However, situation is somehow worse with respect to carbon dioxide emissions factor, as here only 1/3rd of companies correspond to I –II labelling classes with Kdh > =215 kg/ MWh in year 2010 and about half of all companies in year 2013. The third factor, renewable energy fraction, shows renewability of the DH system, and target value in Lithuania's case should exceed 23%. Most companies, over 2/3rd, have met this requirement in 2013. Labelling results were calculated using default values and scaling, adjusted to national conditions. With further development of DHC the criteria values of labelling classes will need adjustment or new classes should be introduced, like energy efficiency labels for appliances does. The above results demonstrate successful government policy of rehabilitation and upgrading DH sector in Lithuania. Essential factors were the strategical decision for switching of DH sector to indigenous and RES, the support for investment and strong promotion of green heating. High prices of imported fossil fuels also played a significant role there. Energy labels should be proposed to policy frameworks at national and municipal levels. This will be focused on ensuring that the benefits of district heating and district cooling are correctly accounted for considering exergy as well as energy and that they assist to the growth

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