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The Optimal Share of Variable Renewables: How the Variability of Wind and Solar Power affects their Welfare-optimal Deployment

Lion Hirth

Year: 2015
Volume: Volume 36
Number: Number 1
DOI: 10.5547/01956574.36.1.6
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Abstract:
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.



Why Wind Is Not Coal: On the Economics of Electricity Generation

Lion Hirth, Falko Ueckerdt, and Ottmar Edenhofer

Year: 2016
Volume: Volume 37
Number: Number 3
DOI: 10.5547/01956574.37.3.lhir
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Abstract:
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.



What caused the drop in European electricity prices? A factor decomposition analysis

Lion Hirth

Year: 2018
Volume: Volume 39
Number: Number 1
DOI: 10.5547/01956574.39.1.lhir
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Abstract:
European wholesale electricity prices have dropped by nearly two thirds since their all-time high around 2008. Different factors have been blamed, or praised, for having caused the price slump: the expansion of renewable energy; the near-collapse of the European emissions trading scheme; over-optimistic power plant investments; a decline in final electricity consumption; and cheap coal and natural gas. This ex-post study of European electricity markets from 2008 to 2015 uses a fundamental power market model to quantify their individual contributions on day-ahead prices. The two countries we study in detail, Germany and Sweden, differ significantly: fuel and CO2 prices were important price drivers in Germany, but in Sweden it was electricity demand. This difference is explained by the nature of the hydro-dominate Nordic electricity system. In both countries, however, the single largest factor depressing prices was the expansion of renewable energy. At the same time, Germany's nuclear phase-out had an upward effect on prices. If one defines the Energiewende as the combination of these two policies, its net effect on power prices was negligible.





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