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    Some of Anne's contributions:

  • Another Tipping Point: US Coal Supply Decline So Real Even West Virginia Concurs (REPORT), November 26, 2013
  • SOLAR FOR ME BUT NOT FOR THEE ~ Xcel's Push to Undermine Rooftop Solar, September 20, 2013
  • NEW BILLS AND NEW BIRDS in Colorado's recent session, May 20, 2013
  • Lies, damned lies and politicians (October 8, 2012)
  • Colorado's Elegant Solution to Fracking (April 23, 2012)
  • Shale Gas: From Geologic Bubble to Economic Bubble (March 15, 2012)
  • Taken for granted no more (February 5, 2012)
  • The Republican clown car circus (January 6, 2012)
  • Twenty-Somethings of Colorado With Skin in the Game (November 22, 2011)
  • Occupy, Xcel, and the Mother of All Cliffs (October 31, 2011)
  • Boulder Can Own Its Power With Distributed Generation (June 7, 2011)
  • The Plunging Cost of Renewables and Boulder's Energy Future (April 19, 2011)
  • Paddling Down the River Denial (January 12, 2011)
  • The Fox (News) That Jumped the Shark (December 16, 2010)
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  • TODAY AT NewEnergyNews, March 22:

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    Wednesday, July 09, 2014


    Primary Energy Demand of Renewable Energy Carriers; Part 2 Policy Implications

    Dr. Nesen Surmeli-Anac, Dr. Andreas Hermelink, David de Jager, Heleen Groenenberg, 9 May 2014 (EcoFys and PE International)


    Energy related discussions and policy making, such as defining energy saving targets or energy efficiency measures, are often based on primary energy values. These values express the energy consumption of a country, the energy demand of a system, service or product in primary energy units. International and national energy statistics, energy scenarios or environmental assessments are defining and publishing these values.

    Primary energy values taken from different energy statistics and studies are sometimes compared without considering possible influences from different definitions used for primary energy. Awareness has been raised recently for the influence of different methods to determine primary energy consumption from renewable energy sources in energy statistics. In Moomaw (2011) and Macknick (2011) the differences in energy statistics and future scenarios that occur from the different methods are highlighted as well as the challenges if statistics and scenarios with different accounting methods are compared. In addition, Harmsen (2011) investigated the impact of different methods on energy saving targets in Europe.

    Primary energy factors (PEF)1 , often referred to as conversion factors, are required to calculate the total energy consumption including the total chain of energy generation based on the final energy consumption data. For each type of delivered energy a so called primary energy factor (PEF) is assigned, which can track all energy relevant demand from initial harvesting to the point of energy delivery. Primary energy factors have been developed as a form of comparison on how much primary energy is required to deliver one unit of secondary energy. As every country may have a very different supply chain from exploration to delivery, PEFs may vary significantly between countries.

    A number of EU directives and regulations refer to implementation of primary energy factors. The main aim of the EU directives are to address long term energy and climate challenges and set targets for EU in terms of energy saving and use of renewable energy sources. The use of primary energy factors has influence on the accounting of such targets therefore they have an impact on long term energy policy scenarios and energy generation investments. Although the method for calculating the PEF for fossil fuels are well established, there is no unified approach in European regulation on how to calculate PEFs for renewable energy sources (RE).

    European Copper Institute had therefore commissioned a two paper series focusing on the options for defining primary energy factors for renewables and clarifying the implications of these options in EU energy policy areas. This paper is the second part of the two paper series. The first part of the study “Primary Energy Demand of Renewable Energy Carriers – Part 1 Methodology and Examples” was elaborated by PE International and describes various methods used for calculating PEFs. It is shown that depending on the methodology used the resulting PEFs for different energy sources vary significantly.

    The second part of the study results is presented in this paper. The aim of this paper is to present the current use of PEFs in EU legislation and provide an outlook on possible policy outcomes of using different PEF calculation methods in three energy policy areas and related EU legislation. Although the emphasis is on Renewable energy carriers, nuclear energy is included in some discussions for the sake of completion. In reality nuclear energy exists in the country energy mix and methods applied for determination of primary energy factor of nuclear as well as RE have consequences on the energy policy options. This paper first describes how primary energy factors are used in the EU regulatory framework. Then, the study investigates to what extent different definitions of PEF for RE have implications s on the three energy policy fields: EU Directives– Energy Performance of Buildings Directive (EPBD), Energy Efficiency Directive (EED), Renewable Energy Directive (RED); the influence on the target setting in overarching EU communications and energy accounting (statistics). The case studies address the policy implications and challenges of using different PEF methodology under these three energy policy areas.

    Review of Directives on Primary Energy Factors…Review on primary energy targets…

    Policy implications of different Primary Energy Factor definitions

    It has been shown in the first part of this paper series that although the primary energy concept is a well-established and defined term in energy accounting, various methods are used in practice to calculate e primary energy factors. The discussions carried out in this section refer mainly to different PEF calculation options summarized in section 3.2 based on the detailed description in Table 5 and Table 6 of the first part of this paper series.

    We have shown in previous sections of this paper that the EU Directives which are the primary tools for EU energy policy due to their direct effect on setting and reaching EU energy targets, namely EED RED and EPBD, lack a clear indication of PEFs for RE or their calculation methods to be used in energy accounting applications. Thus the current situation possibly creates ambiguity in methods applied in Member States and leaves room for different interpretations. Use of different methodologies would lead to significantly different results in energy accounting, and consequently the monitoring and evaluation of EU targets. The important outcomes with regard to use of different PEF definitions and methodologies are discussed in the following paragraphs. To illustrate the implications of different PEF accounting methodologies a series of hypothetical examples are used.

    Impact on the Energy Efficiency Directive The fundamental principle underlying the EED is to reduce the energy demand in the EU. The directive aims for 20% primary energy savings by 2020. However, how the amount of energy saving is calculated depends significantly on which primary energy factor methodology is used.

    For illustration purposes we assume a country that does not use nuclear energy achieves 10% final electricity savings. 50% of the electricity is provided through conventional fossil fuels, and the other 50% of the electricity is provided by a mix of renewable energy sources, where each renewable energy source contributes an equal share of electricity. Figure 1 illustrates how total primary energy is distributed between conventional fossil fuels and different renewable sources depending on the calculation method. Note these calculation methods are explained in the first part of this paper. They all apply the same PEF of 2.5 for electricity from conventional fossil fuels, but very different PEF for different renewable energy sources. Please also note that intentionally for exemplary purpose in these examples non-renewable energy and renewable energy may be shown aggregated as well for options 4a and 4b although their explicit objective is to discern between renewable and non-renewable shares and to show their different potentials for efficiency gains. This is why in Figure 1 the conventional electricity is shown with a diagonal pattern.

    The major insight is that as long as a reduction of electricity consumption is evenly distributed to all energy sources – fossil and renewable – a 10% reduction of electricity use leads to a 10% reduction for each energy source, and consequently to a 10% reduction of total primary energy for all calculation methods. But if the question is: “from which source should we reduce supply most in order to achieve maximum relative primary energy savings” the picture changes significantly. In all options that feature a relative share of renewables in the total PEF of more than 50% it seems to be more attractive –only having the objective of maximum primary energy reduction – to switch off renewable power plants rather than fossil power plants, i.e. in all those options only switching off renewable power plants would lead to primary energy savings of more than 10%. This is the case for options 2b and 2c but especially for options 4a and 4b due to their intentionally improper use.

    For illustration we give another example. As said, fossil and renewable sources each provide 50% of electricity. If in our hypothetical energy system all fossil power stations are switched off, in option 4a 50% reduction of electricity supply, 100% reduction of greenhouse gas emissions but only approx. 33% reduction of total primary energy use would follow. Therefore in 4a it may seem to be more attractive to switch off all renewable power stations, as it seems to lead to approx. 67% reduction of total primary energy use, again 50% reduction of energy supply - but 0% reduction of greenhouse gas emissions.

    First, this highlights the importance to reflect on the adequate application of the different methods to avoid unintended and misleading results. Second, it highlights that a “primary energy only” focus may lead to conclusions or decisions that clearly contradict climate targets, which aim at maximum reduction of greenhouse gas emissions rather than of primary energy use. The method used to deal with the share of renewable energy within energy statistics is important for discussing the contribution of RE for achieving primary energy savings from another perspective. Harmsen et al. (2011) discuss the interaction between EU’s renewable energy and primary energy savings target. They explain that when electricity is produced from fossil fuels, typically a primary energy factor of 2.5 is used. This means that if a smaller primary energy factor is used in energy statistics for renewable energy sources (e.g. option 2b uses 1 for hydro, solar PV and wind) then an increased relative share of such renewable energy sources will lead to primary energy savings without any final energy savings. They state “…for example: replacing 1 unit of fossil electricity (=2.5 units of primary energy) by 1 unit of wind, hydro and solar electricity (=1 unit primary energy) leads to 1.5 units of primary energy savings.” Following the same principle the potential impact of different PEFs on indirect total primary energy use, i.e. changes in total primary energy use that don’t directly follow from an actual reduction of electricity use but only from replacing fossil fuel by another energy carrier is shown in Figure 2. The figure shows the indirect total primary energy change for all calculation methods. Only the PEF calculation methods featuring PEFs for renewables that are smaller than 2.5 may end up in a reduced total primary energy balance by reducing fossil fuel electricity by renewable electricity. Figure 2 may be interpreted as follows: ten different energy carriers are shown. If 10 units of electricity from fossil power plants would be replaced by one unit of electricity from each of those 10 alternative power plants the net change in the total primary energy balance would be the positive part in each option minus the corresponding negative part. This means while in option 2a total primary energy would decrease by approx. 5 units, in option 4a it would increase by approx. 15 units. With this analysis it is visualized that the RE sources which remain competitive against fossil electricity varies (or seems to vary) within each calculation method. From this perspective larger PEFs for renewable energy (especially values bigger than 2.5) will risk to hamper the RE development as this would seem to imply an increase in primary energy use especially for biomass, geothermal and solar thermal and waste energy options.

    Harmsen et al. (2011) show that based on the 100% conversion efficiencies used in Eurostat energy statistics for wind, solar and hydroelectricity, renewable energy provides primary energy savings and as a result contributes to Europe’s 20% primary energy savings target. However, care must be taken in EU policy whenever such interaction between energy saving and renewable energy targets exists. In the context of the EED there is a risk of limited policy focus on meeting real progress in energy efficiency when booking increased renewable shares to the benefit of primary energy savings. Remember that the fundamental aim of the EED is energy savings on demand side in transport, industry and buildings with additional benefits such as lower energy bills, increase of the renewable energy share without investing in new renewable capacity, and long-term climate targets to reduce greenhouse gas emissions.

    Impact on the Renewable Energy Directive

    While we focused on primary energy factor within the context of the EED, now the focus switches to the share of renewables to match the context of the RED. The RED directive sets binding targets for the percentage of renewable energy in 2020. The method of calculation and choice of PEFs have a potentially large impact on the calculation of share of renewable energy and consequently on energy markets. We use a hypothetical situation to illustrate the impacts of different PEFs on calculating the share of renewable energy and on energy systems. The situation assumes a total gross inland consumption of 100 units of final energy from fossil fuels and 10 units of renewable energy from each renewable energy source concerned in this paper. Table 2 shows remarkable differences for the share of renewable energy from using different methods; all previously shown energy carriers are included, except waste (as sometimes being doubtful if renewable or not) and nuclear. Option 3 was left out as it only shows the non-renewable primary energy…

    Thus for the same situation different methods can create the illusion of very different achievement levels of renewable energy targets. The highest share of renewable energy is communicated by the two LCA based methods, Option 4a and Option 4b. A more detailed view of the percentages shown in Table 2 is presented in Figure 3. Among all the methods the share of hydroelectricity remains quite stable between different options. Option 2c- substitution method - clearly favours hydroelectricity to any other method. The share of wind energy shows little variation, mostly favoured by Option 4a. Both photovoltaics and solar thermal reach their highest shares also in Option 4a. Geothermal reaches its highest share with physical energy content methods, namely 17.3% (2b) or 14.3% (4b) respectively. For biomass Option 4a and Option 4b produce quite close percentages.

    Impact on the Energy Performance of Buildings Directive

    Renewable energy sources are a necessity for reducing the fossil based energy consumption in buildings, achieving nZEBs and beyond. The EPBD defines a nearly Zero-Energy Building as follows: [A nearly Zero-Energy Building is a] “building that has a very high energy performance… [ ]. The nearly zero or very low amount of energy required should to a very significant extent be covered by energy from renewable sources, including renewable energy produced on-site or nearby.” Therefore, it is extremely important that renewable energy applications are considered accurately in the national calculation methods or requirements in order to provide a sound basis for comparison, evaluation and monitoring.

    In principle very high performance buildings and nZEBs can be self-sufficient in terms of their energy needs. However, the difference between the time of use and the time of generation of “on-site” or “nearby” renewable electricity hinders the possibility to use it fully for self-consumption. Grid connection is usually necessary to enable the true physical zero energy balance. The energy performance is calculated based on the balance or the difference between the energy consumption and energy production of a building. (Net) Primary energy demand (or consumption) is the EPBD’s primary measure of energy performance, and it is derived from delivered energy and the respective primary energy factors. Therefore, one area where application of PEFs will have a significant impact is the metric of balance used to calculate the energy balance of nZEBs between imported and exported energy.

    Energy use in buildings is one of the areas where PEFs may influence the end-user choices between various energy sources. The building owner can select among different energy sources to fulfil the nZEB requirements. Different fuels having different primary energy factors may be used within one building, and also different buildings will run on different fuel-mixes. The method of calculating PEFs influences the respective choices.

    A recent paper by (ECOFYS, 2012) lists the possible implications of different PEFs on the technologies used in the building sector. The paper outlines the consequences of increased use of renewables and consequent changes in PEFs from two perspectives: electricity delivered to the building and electricity produced on-site or nearby. Below we further elaborate that discussion based on each PEF methodology and related PEF values…

    As to electricity delivered to the building (left side of equation (1) in chapter 2.4), the increasing share of renewable energy in the electricity mix will lead to decreasing total PEFs for electricity. (Baake et al, 2012) estimate total PEFs for electricity generation in Europe to drop from 2.5 today, to 2.05 by 2020, 1.65 by 2030 and 1.2 by 2050. Consequently electricity consumption will contribute less primary energy to the overall energy performance indicator of a building resulting in an increasing competitive advantage for electric heating over oil and gas. Note that such development is plausible in the case of PEF accounting options 2a, 2b, and 4b. Option 2c will not work towards lowering the total PEF for electricity as it assigns equal PEFs to renewables and conventional resources. Depending on the total share of renewable energy in the electricity mix, for countries with high RE share, the total decrease of PEF for electricity may not be reached due to high PEFs provided in option 4a for renewable energy sources. In that situation the high PEFs (compared to the given electricity supply mix in that country) used by some EU Member States may hamper the development of grid-coupled renewable energy in the long run. Consequently the competitive advantage of electricity over the fossil fuel heating will not be reached. Although the required energy for heating will be comparatively low in high performance buildings, it is likely that end-users will supply it from local fossil fuel burners instead of using the increasingly renewable grid electricity. In a nutshell, depending on the PEF calculation method used people may use different fuel mixes for minimising their building’s primary energy balance.

    As to electricity produced on-site or nearby (right side of equation (1) in chapter 2.4), the PEFs assigned to renewable energy will have a direct influence on calculating the total primary energy. For low-energy buildings and nZEBs the aim is to maximise this amount in order to lower the total primary energy consumption. Having this target, option 2c and option 4a will be most beneficial, due to their high PEFs for electricity produced on-site or nearby, especially if it comes from PV or wind energy.

    It should be emphasized that the influence of PEFs on the accounting of energy performance of buildings will have a dual effect on electricity delivered to the building and electricity produced on-site or nearby simultaneously. Therefore the impact of any PEF option on building performance accounting will heavily depend on the actual energy mix in a country and which renewable energy sources are used for energy production for nZEBs. For illustration purposes, based on the PEF values provided in the first part of this paper, we discuss three examples featuring significantly different electricity mixes: high share of renewables (e.g. Norway), high share of fossil fuels (e.g. Poland) and renewable and fossil fuels (e.g. Spain). For these three countries we compare the PEF of grid mix electricity with PEF of various energy sources under different methods. Table 3 provides the list of renewable energy sources which have equal or higher PEF than grid mix electricity, therefore equal or higher impact on primary energy demand equation compared to grid mix electricity. The renewable energy choices given in Table 3 will push the balance towards zero or positive energy buildings. Please compare Table 6 from Part 1 of this study for more details on grid mix PEF for these countries when using different methodologies for calculating PEFs…Norway…Poland…Spain…


    The major European directives we discussed have different objectives:

    • Energy Efficiency Directive: this is to improve end–use energy efficiency, but which is measured in terms of total primary energy use which – as demonstrated in this paper - is not the most adequate indicator. Therefore there is a danger that without actually reducing final energy use, still improvements in energy efficiency in terms of primary energy can be shown, depending on the accounting method which is used; in specific cases even increased greenhouse gas emissions may occur concurrently with reduced primary energy use. v • Renewable Energy Directive: this is to increase the share of renewable energy, but depending on the accounting method very different shares of renewable energy will be demonstrated. This means that by just changing the methodology significant “virtual” improvements could be achieved.

    • Energy Performance of Buildings Directive: this is to improve the energy efficiency of new and existing buildings, primary energy use being the main indicator for the energy performance. The applied accounting methodology will have significant effects on the calculated energy performance and thus on the chosen fuel mix and share of renewables in buildings.

    There are significant reasons to set up a transparent, scientifically based methodology for determining primary energy factors for all energy sources all over the EU MS which is in line with over-arching climate targets. As pointed out, there are different methodologies for determining PEFs that lead to significantly different PEF for different energy carriers including energy from renewable sources.

    Our analysis revealed that a too strong focus on primary energy may even have adverse effects on climate targets. There are different commonly used methodologies for determining primary energy factors which may even lead to an increase in primary energy use by replacing fossil fuel based power generation with power generation from renewable sources. Equally a decrease in total primary energy use may be achieved without saving a single kWh of electricity by just replacing fossil fuels with energy from renewable sources in power generation. This may disguise a standstill in energy efficiency improvements.

    On top, there are some issues with the EC’s currently used default primary energy factor for electricity, which is 2.5 and used amongst others in the Energy Efficiency Directive and Eco-Design regulations:

    • Lack of unambiguous scientific values: The conversion factor of 2.5 was introduced in the footnote to Annex II of the Directive on energy end-use efficiency and energy services (Directive 2006/32/EC). This value of 2.5 was already present in the Commission Proposal for a Directive of the European Parliament and of the Council on energy end-use efficiency and energy y services, published on 10 December 2003 in the EU Official Journal (COM(2003) 739 final) (European Commission, 2003). It is reasonable to expect that, in December 2003, available Eurostat figures were referring to the year 2001, at the latest and therefore there is a strong need for updating this value.

    • Lack of consistency: Where PEFs are mentioned, the EU directives state that the Member States are free to choose PEFs. Energy Efficiency Directive (EED) (2012/27/EU) Annex IV, footnote 3 to the conversion table, states: “For savings in kWh electricity Member States may apply a default coefficient of 2.5. Member States may apply a different coefficient provided they can justify it.” A similar hint is also included in the EPBD. This means that those directives actually provide considerable space for Member States to deviate from the suggested values rather than mandating a specific value.

    • Lack of transparency: A recent study by Ecofys (2012) concluded that primary energy factors are not commonly based entirely on scientific arguments and clear algorithms. It is highly likely that the values used as substitution factors will be debatable. Given the significant changes ahead in electricity supply, the PEF for electricity should be regularly revised and its method of calculation clearly documented and eventually harmonized. This provides the opportunity to present arguments feeding into national discussions for establishing PEFs.

    Therefore the final conclusions are:

    • For monitoring the progress in Europe all Member States should use the same or a very similar methodology for determining primary energy factors for renewable and non-renewable energy sources.

    • Utmost care has to be taken that methods are not abused – be it intended or unintended – for promoting fossil fuels versus renewable sources. This danger is especially relevant for methods 4a and 4b which are mainly designed for illustrating efficiency potentials separately for energy from conventional and renewable sources, which of course is not meant to suggest preferring conventional over renewable sources.

    • Such methodology needs to be transparent and should be based on available data.

    • In order to provide a consistent insight into the effect of replacing conventional power generation by renewable power generation a solid, scientifically based determination of primary energy factors for renewable, conventional, fossil or nuclear based power supply must be available and commonly applied.

    • The method used for determining primary energy factors for energy from renewable sources must be in line with climate policy targets. Changes in the power system which lead to reductions in greenhouse gas emissions generally should lead to reductions in primary energy use.

    • Primary energy factors should be determined and applied in a way that enables to clearly differentiate between direct primary energy savings - stemming from actual final energy savings - and indirect primary energy savings – stemming from changes in the energy mix.

    • Finally care should be taken, that renewable energy sources are treated equally relative to their effect on reducing greenhouse gas emissions and the calculated share of renewables in an energy mix. Generally it does not seem helpful for achieving a well-balanced mix of different renewable sources when one zero-emission source is outpaced by another zero-emission source by assigning very different primary energy factors to these sources.

    All directives we discussed in this paper aim at improving the environmental quality in Europe. Applying the above given guidelines in determining a suitable, common methodology for calculating primary energy factors would ensure that the policy targets included in these directives will be in harmony with each other rather than having the risk of them being in disharmony or even competition with each other.


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