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As part of its climate strategy, the EU aims at increasing the share of electricity from renewable energy sources (RES-E) in overall electricity generation. Attaining this target poses a considerable challenge as the electricity sector is “locked” into a carbon-intensive system, which hampers the adoption of RES-E technologies. Electricity generation, transmission and distribution grids as well as storage and demand response are subject to important path dependences, which put existing, non-renewable energy sources at an advantage. This paper examines how an EU framework for RES-E support policies should be designed to facilitate a carbon lock-out. For this purpose, we specify the major technological, economic and institutional barriers to RES-E. For each of the barriers, a policy review is carried out which assesses the performance of existing policy instruments and identifies needs for reform. The review reveals several shortcomings: while policies targeting generation are widely in place, measures to address barriers associated with electricity grids, storage and demand are still in their infancy and have to be extended. Moreover, the implementation of policies has been fragmented across EU Member States. In this respect, national policies should be embedded into an integrated EU-wide planning of the RES-E system with overarching energy scenarios and partially harmonized policy rules.
Levelized costs of electricity (LCOE) are a common metric for comparing power generating technologies. However, there is criticism particularly towards evaluating variable renewables like wind and solar PV power based on LCOE because it ignores variability and integration costs. We propose a new metric System LCOE that accounts for integration and generation costs. For this purpose we develop a new mathematical definition of integration costs that directly relates to economic theory. As a result System LCOE allow the economic comparison of generating technologies and deriving optimal quantities in particular for VRE. To demonstrate the new concept we quantify System LCOE from a simple power system model and literature values. We find that at high wind shares integration costs can be in the same range as generation costs of wind power and conventional plants in particular due to a cost component “profile costs” captured by the new definition. Integration costs increase with growing wind shares and might become an economic barrier to deploying VRE at high shares. System LCOE help understanding and resolving the challenge of integrating VRE and can guide research and policy makers in realizing a cost-efficient transformation towards an energy system with potentially high shares of variable renewables.
With the global expansion of renewable energy (RE) technologies, the provision of optimal RE policy packages becomes an important task. We review pivotal aspects regarding the economics of renewables that are relevant to the design of an optimal RE policy, many of which are to date unresolved. We do so from three interrelated perspectives that a meaningful public policy framework for inquiry must take into account. First, we explore different social objectives justifying the deployment of RE technologies, including potential co-benefits of RE deployment, and review modelbased estimates of the economic potential of RE technologies, i.e. their socially optimal deployment level. Second, we address pivotal market failures that arise in the course of implementing the economic potential of RE sources in decentralized markets. Third, we discuss multiple policy instruments curing these market failures. Our framework reveals the requirements for an assessment of the relevant options for real-world decision makers in the field of RE policies. This review makes it clear that there are remaining white areas on the knowledge map concerning consistent and socially optimal RE policies.
Energy and climate policies are usually seen as measures to internalize externalities. However, as a side effect, the introduction of these policies redistributes wealth between consumers and producers, and within these groups. While redistribution is seldom the focus of the academic literature in energy economics, it plays a central role in public debates and policy decisions. This paper compares the distributional effects of two major electricity policies: support schemes for renewable energy sources, and CO2 pricing. We find that the redistribution effects of both policies are large, and they work in opposed directions. While renewables support transfers wealth from producers to consumers, carbon pricing does the opposite. More specifically, we show that moderate amounts of wind subsidies can increase consumer surplus, even if consumers bear the subsidy costs. CO2 pricing, in contrast, increases aggregated producer surplus, even without free allocation of emission allowances; however, not all types of producers benefit. These findings are derived from an analytical model of electricity markets, and a calibrated numerical model of Northwestern Europe. Our findings imply that if policy makers want to avoid large redistribution they might prefer a mix of policies, even if CO2 pricing alone is the first-best climate policy in terms of allocative efficiency.
This paper provides a comprehensive discussion of the market value of variable renewable energy (VRE). The inherent variability of wind speeds and solar radiation affects the price that VRE generators receive on the market (market value). During windy and sunny times the additional electricity supply reduces the prices. Because the drop is larger with more installed capacity, the market value of VRE falls with higher penetration rate. This study aims to develop a better understanding on how the market value with penetration, and how policies and prices affect the market value. Quantitative evidence is derived from a review of published studies, regression analysis of market data, and the calibrated model of the European electricity market EMMA. We find the value of wind power to fall from 110% of the average power price to 50–80% as wind penetration increases from zero to 30% of total electricity consumption. For solar power, similarly low value levels are reached already at 15% penetration. Hence, competitive large-scale renewable deployment will be more difficult to accomplish than as many anticipate.
This paper estimates the welfare-optimal market share of wind and solar power, explicitly taking into account their output variability. We present a theoretical valuation framework that consistently accounts for the impact of fluctuations over time, forecast errors, and the location of generators in the power grid on the marginal value of electricity from renewables. Then the optimal share of wind and solar power in Northwestern Europe's generation mix is estimated from a calibrated numerical model. We find the optimal long-term wind share to be 20%, three times more than today; however, we also find significant parameter uncertainty. Variability significantly impacts results: if winds were constant, the optimal share would be 60%. In addition, the effect of technological change, price shocks, and policies on the optimal share is assessed. We present and explain several surprising findings, including a negative impact of CO2 prices on optimal wind deployment.
This paper reviews the economics of solar power as a source of grid-connected electricity generation. It is widely acknowledged that costs of solar power have declined, but there is disagreement how its economic value should be calculated. ‘Grid parity’, comparing generation costs to the retail price, is an often used yet flawed metric for economic assessment, as it ignores grid fees, levies, and taxes. It also fails to account for the fact that electricity is more valuable at some points in time and at some locations than that at others. A better yardstick than the retail price is solar power's ‘market value’. This paper explains why, and provides empirical estimates of the solar market value from a literature review, German spot market analysis, and the numerical electricity market model EMMA. At low penetration rates (<2–5%) solar power's market value turns out to be higher than the average wholesale electricity price – mainly, because the sun tends to shine when electricity demand is high. With increasing penetration, the market value declines – the solar premium turns into a solar penalty. In Germany, the value of solar power has fallen from 133% of the average electricity price to 98% as solar penetration increased from zero to 4.7%. This value drop is steeper than wind power's value drop, because solar generation is more concentrated in time. As a consequence, large-scale solar deployment without subsidies will be more difficult to accomplish than many observers have anticipated.
Balancing power is used to quickly restore the supply-demand balance in power systems. The need for this tends to be increased by the use of variable renewable energy sources (VRE) such as wind and solar power. This paper reviews three channels through which VRE and balancing systems interact: the impact of VRE forecast errors on balancing reserve requirements; the supply of balancing services by VRE generators; and the incentives to improve forecasting provided by imbalance charges. The paper reviews the literature, provides stylized facts from German market data, and suggests policy options. Surprisingly, while German wind and solar capacity has tripled since 2008, balancing reserves have been reduced by 15%, and costs by 50%.
The integration of wind and solar generators into power systems causes “integration costs” – for grids, balancing services, more flexible operation of thermal plants, and reduced utilization of the capital stock embodied in infrastructure, among other things. This paper proposes a framework to analyze and quantify these costs. We propose a definition of integration costs based on the marginal economic value of electricity, or market value – as such a definition can be more easily used in economic cost-benefit assessment than previous approaches. We suggest decomposing integration costs intro three components, according to the principal characteristics of wind and solar power: temporal variability, uncertainty, and location-constraints. Quantitative estimates of these components are extracted from a review of 100 + published studies. At high penetration rates, say a wind market share of 30–40%, integration costs are found to be 25–35 €/MWh, i.e. up to 50% of generation costs. While these estimates are system-specific and subject to significant uncertainty, integration costs are certainly too large to be ignored in high-penetration assessments (but might be ignored at low penetration). The largest single factor is reduced utilization of capital embodied in thermal plants, a cost component that has not been accounted for in most previous integration studies.
Das Ende der Grundlast
(2015)
Energy policy often builds on insights gained from quantitative energy models and their underlying data. As climate change mitigation and economic concerns drive a sustained transformation of the energy sector, transparent and well-founded analyses are more important than ever. We assert that models and their associated data must be openly available to facilitate higher quality science, greater productivity through less duplicated effort, and a more effective science-policy boundary. There are also valid reasons why data and code are not open: ethical and security concerns, unwanted exposure, additional workload, and institutional or personal inertia. Overall, energy policy research ostensibly lags behind other fields in promoting more open and reproducible science. We take stock of the status quo and propose actionable steps forward for the energy research community to ensure that it can better engage with decision-makers and continues to deliver robust policy advice in a transparent and reproducible way.
Low-carbon electricity generation, i.e. renewable energy, nuclear power and carbon capture and storage, is more capital intensive than electricity generation through carbon emitting fossil fuel power stations. High capital costs, expressed as high weighted average cost of capital (WACC), thus tend to encourage the use of fossil fuels. To achieve the same degree of decarbonization, countries with high capital costs therefore need to impose a higher price on carbon emissions than countries with low capital costs. This is particularly relevant for developing and emerging economies, where capital costs tend to be higher than in rich countries. In this paper we quantitatively evaluate how high capital costs impact the transformation of the energy system under climate policy, applying a numerical techno-economic model of the power system. We find that high capital costs can significantly reduce the effectiveness of carbon prices: if carbon emissions are priced at USD 50 per ton and the WACC is 3%, the cost-optimal electricity mix comprises 40% renewable energy. At the same carbon price and a WACC of 15%, the cost-optimal mix comprises almost no renewable energy. At 15% WACC, there is no significant emission mitigation with carbon pricing up to USD 50 per ton, but at 3% WACC and the same carbon price, emissions are reduced by almost half. These results have implications for climate policy; carbon pricing might need to be combined with policies to reduce capital costs of low-carbon options in order to decarbonize power systems.
Previous studies find that the economic value of electricity (USD/MWh) generated by wind power drops with increasing market share. Different measures can help mitigate the value drop, including electricity storage, flexible conventional plants, expansion of transmission, and demand response. This study assesses another option: a change in design of wind power plants. “Advanced” wind turbines that are higher and have a larger rotor compared to rated capacity (lower specific rating) generate electricity more constantly than “classical” turbines. Recent years have witnessed a significant shift towards such advanced technology. Our model-based analysis for Northwestern Europe shows that such design can substantially increase the spot market value of generated electricity. At a 30% penetration rate, the value of 1 MWh of electricity generated from a fleet of advanced turbines is estimated to be 15% higher than the value of 1 MWh from classical turbines. The additional value is large, whether compared to wind generation costs, to the value drop, or to the effect of alternative measures such as electricity storage. Extensive sensitivity tests indicate that this finding is remarkably robust. The increase in bulk power value is not the only advantage of advanced turbines: additional benefits might accrue from reduced costs for power grids and balancing services. To fully realize this potential, power markets and support policies need to be appropriately designed and signal scarcity investors.
Electricity is a paradoxical economic good: it is highly homogeneous and heterogeneous at the same time. Electricity prices vary dramatically between moments in time, between location, and according to lead-time between contract and delivery. This three-dimensional heterogeneity has implication for the economic assessment of power generation technologies: different technologies, such as coal-fired plants and wind turbines, produce electricity that has, on average, a different economic value. Several tools that are used to evaluate generators in practice ignore these value differences, including "levelized electricity costs", "grid parity", and simple macroeconomic models. This paper provides a rigorous and general discussion of heterogeneity and its implications for the economic assessment of electricity generating technologies. It shows that these tools are biased, specifically, they tend to favor wind and solar power over dispatchable generators where these renewable generators have a high market share. A literature review shows that, at a wind market share of 30-40%, the value of a megawatt-hour of electricity from a wind turbine can be 20-50% lower than the value of one megawatt-hour as demanded by consumers. We introduce "System LCOE" as one way of comparing generation technologies economically.