Journal
CLIMATIC CHANGE
Volume 167, Issue 1-2, Pages -Publisher
SPRINGER
DOI: 10.1007/s10584-021-03163-4
Keywords
Clean energy investments; Cost of capital; Weighted average cost of capital; Electricity system
Funding
- EU [730403]
- Swiss State Secretariat for Education, Research and Innovation (SERI) [16.0222]
- EU (European Research Council) [948220]
- European Research Council (ERC) [948220] Funding Source: European Research Council (ERC)
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The cost of capital varies significantly across EU countries and energy technologies, affecting the technology mix, deployment, carbon emissions, and electricity system costs. By differentiating these costs in energy models, policymakers can better engineer an effective and efficient energy transition.
Cost of capital is an important driver of investment decisions, including the large investments needed to execute the low-carbon energy transition. Most models, however, abstract from country or technology differences in cost of capital and use uniform assumptions. These might lead to biased results regarding the transition of certain countries towards renewables in the power mix and potentially to a sub-optimal use of public resources. In this paper, we differentiate the cost of capital per country and technology for European Union (EU) countries to more accurately reflect real-world market conditions. Using empirical data from the EU, we find significant differences in the cost of capital across countries and energy technologies. Implementing these differentiated costs of capital in an energy model, we show large implications for the technology mix, deployment, carbon emissions and electricity system costs. Cost-reducing effects stemming from financing experience are observed in all EU countries and their impact is larger in the presence of high carbon prices. In sum, we contribute to the development of energy system models with a method to differentiate the cost of capital for incumbent fossil fuel technologies as well as novel renewable technologies. The increasingly accurate projections of such models can help policymakers engineer a more effective and efficient energy transition.
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