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Biomass and Bioenergy Vol.38 Nr.March, 117-127 ; Policy-makers apply multiple policy instruments simultaneously in the climate and energy policy field at both EU and Member State levels. This creates interactions between instruments that can be complementary and synergistic but also conflicting. This article focuses on the interactions of climate policy instruments and their impact on biomass use. The objectives are to examine interactions of the EU Emissions Trading System (EU ETS) with the main national climate policy instruments and to identify the influence of these on biomass use. The work draws experiences from seven EU countries (Austria, Finland, Germany, the Netherlands, Poland, Sweden and the United Kingdom), with a special focus on Finland and Sweden. The analysis explores the effects of policy interactions and is based on an examination of literature, and interviews with biomass experts in research, industry and policy spheres. Results indicate that the combined effects of climate policy instruments have a tangible impact on biomass use, whereas the causal links to the EU ETS are difficult to assess separately. Policy impacts found include increased competition for biomass resources, changes in fuel mixes and a contribution to upward pressure on wood prices. Differences in these effects are linked to differing national policy mixes and energy-carrier portfolios - an example being the relative differences in the importance of peat to the energy mix in Finland and Sweden. Analysis and comparison of the effects in the selected countries can yield insight on how to improve the design of policy interventions that impact biomass use. This study confirms the importance of identifying interactions between policy instruments so as to recognise - and manage - synergies and conflicts. The development of more synergistic and coordinated policy instrument mixes would also be beneficial for the bioenergy field

Improving energy system modeling capabilities can directly affect the quality of applied studies. However, some modeling trade-offs are necessary as the computational capacity and data availability are constrained. In this paper, we demonstrate modeling trade-offs resulting from the modification in the resolution of four modeling capabilities, namely, transitional scope, European electricity interconnection, hourly demand-side flexibility description, and infrastructure representation. We measure the cost of increasing resolution in each capability in terms of computational time and several energy system modeling indicators, notably, system costs, emission prices, and electricity import and export levels. The analyses are performed in a national-level integrated energy system model with a linear programming approach that includes the hourly electricity dispatch with European nodes. We determined that reducing the transitional scope from seven to two periods can reduce the computational time by 75% while underestimating the objective function by only 4.6%. Modelers can assume a single European Union node that dispatches electricity at an aggregated level, which underestimates the objective function by 1% while halving the computational time. Furthermore, the absence of shedding and storage flexibility options can increase the curtailed electricity by 25% and 8%, respectively. Although neglecting flexibility options can drastically decrease the computational time, it can increase the sub-optimality by 31%. We conclude that an increased resolution in modeling flexibility options can significantly improve the results. While reducing the computational time by half, the lack of electricity and gas infrastructure representation can underestimate the objective function by 4% and 6%, respectively.

Improving energy system modeling capabilities can directly affect the quality of applied studies. However, some modeling trade-offs are necessary as the computational capacity and data availability are constrained. In this paper, we demonstrate modeling trade-offs resulting from the modification in the resolution of four modeling capabilities, namely, transitional scope, European electricity interconnection, hourly demand-side flexibility description, and infrastructure representation. We measure the cost of increasing resolution in each capability in terms of computational time and several energy system modeling indicators, notably, system costs, emission prices, and electricity import and export levels. The analyses are performed in a national-level integrated energy system model with a linear programming approach that includes the hourly electricity dispatch with European nodes. We determined that reducing the transitional scope from seven to two periods can reduce the computational time by 75% while underestimating the objective function by only 4.6%. Modelers can assume a single European Union node that dispatches electricity at an aggregated level, which underestimates the objective function by 1% while halving the computational time. Furthermore, the absence of shedding and storage flexibility options can increase the curtailed electricity by 25% and 8%, respectively. Although neglecting flexibility options can drastically decrease the computational time, it can increase the sub-optimality by 31%. We conclude that an increased resolution in modeling flexibility options can significantly improve the results. While reducing the computational time by half, the lack of electricity and gas infrastructure representation can underestimate the objective function by 4% and 6%, respectively.

The European Council has proposed to stick to a more ambitious GHG target but to scrap a binding RES target for the post-2020 period. This is in line with many existing assessments which demonstrate that additional RES policies impair the cost-effectiveness of addressing a single CO2 externality, and should therefore be abolished. Our analysis explores to what extent this reasoning holds in a secondbest setting with multiple externalities related to fossil and nuclear power generation and policy constraints. In this context, an additional RES policy may help to address externalities for which firstbest policy responses are not available. We use a fully integrated combination of two separate models the top-down, global macro-economic model E3MG and the bottom-up, global electricity sector model FTT:Power - to test this hypothesis. Our quantitative analysis confirms that pursuing an ambitious RES target may mitigate nuclear risks and at least partly also negative non-carbon externalities associated with the production, import and use of fossil fuels. In addition, we demonstrate that an additional RES target does not necessarily impair GDP and other macro-economic measures if rigid assumptions of purely rational behaviour of market participants and perfect market clearing are relaxed. Overall, our analysis thus demonstrates that RES policies implemented in addition to GHG policies are not per se welfare decreasing. There are plausible settings in which an additional RES policy may outperform a single GHG/ETS strategy. Due to the fact, however, that i) policies may have a multiplicity of impacts, ii) the size of these impacts is subject to uncertainties and iii) their valuation is contingent on individual preferences, an unambiguous, "objective" economic assessment is impossible. Thus, the eventual decision on the optimal choice and design of climate and energy policies can only be taken politically.

The European Council has proposed to stick to a more ambitious GHG target but to scrap a binding RES target for the post-2020 period. This is in line with many existing assessments which demonstrate that additional RES policies impair the cost-effectiveness of addressing a single CO2 externality, and should therefore be abolished. Our analysis explores to what extent this reasoning holds in a secondbest setting with multiple externalities related to fossil and nuclear power generation and policy constraints. In this context, an additional RES policy may help to address externalities for which firstbest policy responses are not available. We use a fully integrated combination of two separate models the top-down, global macro-economic model E3MG and the bottom-up, global electricity sector model FTT:Power - to test this hypothesis. Our quantitative analysis confirms that pursuing an ambitious RES target may mitigate nuclear risks and at least partly also negative non-carbon externalities associated with the production, import and use of fossil fuels. In addition, we demonstrate that an additional RES target does not necessarily impair GDP and other macro-economic measures if rigid assumptions of purely rational behaviour of market participants and perfect market clearing are relaxed. Overall, our analysis thus demonstrates that RES policies implemented in addition to GHG policies are not per se welfare decreasing. There are plausible settings in which an additional RES policy may outperform a single GHG/ETS strategy. Due to the fact, however, that i) policies may have a multiplicity of impacts, ii) the size of these impacts is subject to uncertainties and iii) their valuation is contingent on individual preferences, an unambiguous, "objective" economic assessment is impossible. Thus, the eventual decision on the optimal choice and design of climate and energy policies can only be taken politically.

The European Council has proposed to stick to a more ambitious GHG target but to scrap a binding RES target for the post-2020 period. This is in line with many existing assessments which demonstrate that additional RES policies impair the cost-effectiveness of addressing a single CO2 externality, and should therefore be abolished. Our analysis explores to what extent this reasoning holds in a secondbest setting with multiple externalities related to fossil and nuclear power generation and policy constraints. In this context, an additional RES policy may help to address externalities for which firstbest policy responses are not available. We use a fully integrated combination of two separate models the top-down, global macro-economic model E3MG and the bottom-up, global electricity sector model FTT:Power – to test this hypothesis. Our quantitative analysis confirms that pursuing an ambitious RES target may mitigate nuclear risks and at least partly also negative non-carbon externalities associated with the production, import and use of fossil fuels. In addition, we demonstrate that an additional RES target does not necessarily impair GDP and other macro-economic measures if rigid assumptions of purely rational behaviour of market participants and perfect market clearing are relaxed. Overall, our analysis thus demonstrates that RES policies implemented in addition to GHG policies are not per se welfare decreasing. There are plausible settings in which an additional RES policy may outperform a single GHG/ETS strategy. Due to the fact, however, that i) policies may have a multiplicity of impacts, ii) the size of these impacts is subject to uncertainties and iii) their valuation is contingent on individual preferences, an unambiguous, "objective" economic assessment is impossible. Thus, the eventual decision on the optimal choice and design of climate and energy policies can only be taken politically.

ABSTRACT: Driven by climate change concerns, Europe has taken significant initiatives toward the decarbonization of its energy system. The European Commission (EC) has set targets for 2030 to achieve at least 40% reduction in greenhouse gas emissions with respect to the 1990 baseline level and cover at least 32% of the total energy consumption in the European Union (EU) through renewable energy sources, predominantly wind and solar generation. However, these technologies are inherently characterized by high variability, limited predictability and controllability, and lack of inertia, significantly increasing the balancing requirements of the system with respect to historical levels. The flexibility burden is currently carried by flexible fossil-fueled conventional generators (mainly gas), which are required to produce significantly less energy (as low operating cost and CO2-free renewable and nuclear generation are prioritized in the merit order) and operate part loaded with frequent startup and shut-down cycles, with devastating effects on their cost efficiency. ; info:eu-repo/semantics/publishedVersion