Decarbonizing Europe's power sector by 2050 — Analyzing the economic implications of alternative decarbonization pathways
Introduction
In October 2009, the European Council endorsed the objective of the European Union (EU) to reduce greenhouse gas (GHG) emissions by 80–95% in 2050 compared to 1990 levels (EU Council, 2009). Given the power sector's dominant share of CO2 emissions in Europe and its comparatively high technological potential for abating CO2 emissions, the transition towards a low-carbon economy implies an almost complete decarbonization of Europe's power sector.1 The decarbonization could be achieved through various technology mixes that all allow for massive CO2 savings in comparison to today's electricity systems, as shown by a number of recent studies (e.g., EC, 2011, ECF, 2010, Eurelectric, 2010, EWI/Energynautics, 2011, Greenpeace, 2010, Greenpeace, 2012).
Aside from the European Emissions Trading System (EU ETS) – which acts as the cornerstone of EU climate policy for electricity generation and energy-intensive industries (EU, 2009b) – the EU has implemented mandatory renewable energy targets. In 2020, renewable energy technologies are supposed to supply 20% of the EU's energy consumption (EU, 2009a) and at least 34% of the EU's electricity consumption (EC, 2010b).2
If supplementary renewable energy targets are implemented to reduce GHG emissions, the issue of counterproductive overlapping regulation arises. First-best economic principles – based on the seminal work of Crocker (1966), Dales (1968) and Montgomery (1972) – suggest that GHG reduction targets could be achieved at least-cost by the implementation of a stand-alone cap-and-trade system covering all sources of GHG emissions. A market for tradable emission certificates is cost-efficient as it establishes a uniform GHG emission price, which serves as a common benchmark for the marginal costs of each potential GHG abatement option. Boeters and Koornneef (2011) argue that supplementary instruments, such as mandatory renewable energy targets, interfere with this least-cost principle by exempting renewables as a particular GHG abatement option from the common benchmark price. Thus, given the assumption of perfect markets, supplementary renewable energy targets are either redundant or associated with excess costs. This argumentation is in line with Tinbergen (1952), who showed that a number of policy targets are best addressed by an equal number of policy instruments.3
In this paper, we analyze the costs of decarbonization and the excess costs of supplementary renewable energy (RES-E) targets for Europe's power sector in over 36 scenarios up to 2050. Our analysis contributes to the literature in several ways. First, we explicitly account for the fact that the costs of decarbonization and the excess costs of supplementary RES-E targets depend on two key conditions: the acceptance of alternative low-carbon technologies (such as new nuclear power plants and CCS technologies) and the development of the economic conditions (mostly defined by the EU's electricity demand, renewable energy investment costs and fossil fuel prices). Second, we apply a dynamic linear electricity system optimization model for Europe, which is characterized by a comparatively high technological and regional resolution, to analyze the implications of alternative decarbonization pathways for Europe's power sector. Hence, we are able to accurately capture the technological and economic consequences of political interference up to 2050.4
Our work complements a number of recent articles published in peer-reviewed journals (Capros et al., 2012a, Capros et al., 2012b, Fürsch et al., 2013, Haller et al., 2012) and studies (Dii, 2012, Dii, 2013, EC, 2011, Eurelectric, 2010, Realisegrid, 2010, RES2020, 2009) analyzing the decarbonization of Europe's power sector. All of these articles and studies show that the achievement of ambitious emission reduction targets for Europe's power (energy) sector in 2050 is technically feasible. However, none of these articles or studies quantifies the costs of decarbonizing Europe's power sector together with the excess costs of supplementary RES-E targets up to 2050, accounting for the availability of alternative low-carbon technologies such as nuclear power and CCS.5
In the base-case economic scenarios, we find that the decarbonization of Europe's power sector in 2050 could be achieved at minimal costs of 171 bn €2010 if competition between all low-carbon technologies is ensured and no restrictions on the use of nuclear power and CCS are implemented. However, if renewables are exempted from competition with alternative low-carbon technologies by prescribing supplementary RES-E targets the costs of decarbonization significantly rise to at least 408 bn €2010 — corresponding to an increase of 140% compared to the minimal costs of decarbonization. The excess costs of supplementary RES-E targets, on the other hand, can be as high as 237 bn €2010 or as little as 15 bn €2010 — depending on the acceptance of new nuclear power plants and CCS technologies. For example, given a complete nuclear phase-out in Europe by 2050 and politically implemented restrictions on the application of CCS to conventional power plants, supplementary RES-E targets are redundant. While in such a scenario the overall costs of decarbonization are comparatively high, the excess costs of supplementary RES-E targets are close to zero (in comparison to a stand-alone CO2 reduction target).
The structure of the paper is as follows: Section 2 relates the paper to existing literature. Section 3 provides a short description of the dynamic linear electricity system optimization model for Europe's power sector used in the analysis. Section 4 defines the scenarios and Section 5 presents the results of our analysis. Conclusions are drawn in Section 6.
Section snippets
Related literature
A wide range of models can be applied to analyze the consequences of policy interference for the energy system or sub-systems (such as the power system).6 In general, two classes of energy system models can be distinguished, as done in Fig. 1. Following the explanation of Götz et al. (2012),
Model description
In order to quantify the cost implications of alternative decarbonization pathways, we use a dynamic linear electricity system optimization model for Europe. The model is an extended version of the dynamic linear electricity system optimization model of the Institute of Energy Economics (University of Cologne) as presented in Richter (2011). Earlier versions of the model have been applied e.g. by Paulus and Borggrefe (2011) and Nagl et al. (2011b). The possibility of endogenous investments in
Scenario definitions
The decarbonization of Europe's power sector can be achieved through various technology mixes, each allowing for massive CO2 savings in comparison to today's electricity system. To systematically analyze the implications of alternative decarbonization pathways for Europe's power sector under different economic conditions to 2050, a matrix of 36 scenarios is defined (Table 2).
The scenarios differ with regard to political regulations (‘CO2’, ‘RES-E’, ‘Nuclear’ and ‘CCS’) and economic conditions
Scenario results
The subsequent analysis is structured as follows: Section 5.1 provides a general overview of the total system costs associated with the alternative decarbonization pathways for different economic framework conditions. Section 5.2 analyzes the minimal costs of decarbonization given a stand-alone CO2 reduction target of 90% in 2050 (compared to 1990 levels) and discusses the cost implications of both the economic framework conditions and politically implemented restrictions on the use of nuclear
Concluding remarks
The applied electricity system optimization model is a profound tool to derive a comprehensive set of technically feasible development pathways for Europe's power sector up to 2050. Specifically, the implications of alternative decarbonization pathways are accurately captured from a technical perspective, as the model encompasses current and future electricity generation technologies in detail, is characterized by a high regional resolution and accounts for increased flexibility requirements of
Acknowledgments
The authors would like to thank Tim Mennel and Marc Oliver Bettzüge for helpful comments and suggestions. This paper also benefited from the discussions of the research seminar of the Institute of Energy Economics at the University of Cologne in 2012.
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