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

Hirth, Lion

doi:10.5547/01956574.36.1.6

Cited by 125 publications

(56 citation statements)

References 78 publications

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“…This fits to a result of a pricing study carried out byHirth (2016). Using Swedish data, the author shows that the value of wind power declines with an increasing market share, but less so the more hydro power is available.…”

supporting

confidence: 74%

“…Based on a complex model of the European energy market, Bertsch et al (2016) predict that, as wind and solar energy is expanded, market forces would automatically provide more gas power plants, even without explicit pricing schemes awarding the flexibility such plants would offer. Hirth (2015) argues that the need to hold back-up power in reserve may limit the optimal wind share to only 20%.…”

Section: The Double-structure Strategymentioning

confidence: 99%

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Buffering volatility: A study on the limits of Germany's energy revolution

Sinn

2017

European Economic Review

112

115

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is gratefully acknowledged. Helmut Alt, Ralph Schuster and Christoph Weissbart kindly provided background data and information. The author is emeritus professor at Ludwig-Maximilian University of Munich. He has no financial interests in the nuclear, fossil fuel or green energy industries nor is he affiliated with a political party. He wishes to thank the editors and three anonymous referees for their extremely useful advice. The paper is dedicated to Wolfgang Meister who has served the ifo Institute for many years with commitment, precision and care and who is now retiring. The views expressed herein are those of the author and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

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supporting

confidence: 74%

Section: The Double-structure Strategymentioning

confidence: 99%

Buffering volatility: A study on the limits of Germany's energy revolution

Sinn

2017

European Economic Review

112

115

View full text Add to dashboard Cite

show abstract

“…This varies from hour to hour and between locations. The economic value of wind and solar energy is often less than that of other sources, because the availability of electricity fluctuates with wind speeds and solar radiation [19][20][21][22][23][24][25]. Moreover, weather-dependent power generation, such as wind and solar power, is subject to forecast errors.…”

Section: Methods and Datamentioning

confidence: 99%

“…Fossil fuel prices were 2015 market prices, and we varied carbon prices and the WACC. EMMA has been used for various peer-reviewed publications to address a range of research questions [21,22,[37][38][39][40]. EMMA is also open-source; the model code can be downloaded from http://neon-energie.…”

Section: Data and Calibrationmentioning

confidence: 99%

The role of capital costs in decarbonizing the electricity sector

Hirth

Steckel

2016

Environ. Res. Lett.

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157

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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 technoeconomic 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 lowcarbon options in order to decarbonize power systems.

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“…Many existing studies of high wind and solar penetration assess the role of a couple of drivers in isolation or with a limited number of joint sensitivities (e.g. Fell and Linn 2013, Shearer et al 2014, Hirth 2015, MacDonald et al 2016, Craig et al 2018, Eshraghi et al 2018, Sepulveda et al 2018, as shown in SI appendix, table 1. Although these one-way sensitivities are valuable ceteris paribus experiments, they do not comprehensively assess the relative impact of a range of factors by jointly varying all drivers simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Economic drivers of wind and solar penetration in the US

Bistline

Young

2019

Environ. Res. Lett.

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Much has been made of the potential for wind and solar generation to supply cheap, low-emissions electricity, but considerable disagreement exists as to which combinations of many potential drivers will enable deep penetration of these technologies. Most existing analyses consider limited factors in isolation, such as investment costs or energy storage, and do not provide rigorous support for understanding which combinations of factors could underpin a leading role for wind and solar. This study addresses this gap by undertaking a systematic sensitivity analysis using a state-of-the-art energy-economic model to comprehensively evaluate the relative magnitudes of five key drivers that may influence future wind and solar deployment in the United States. We find future wind and solar capital costs and carbon policy are the dominant factors, causing the average wind and solar share to vary by 38 and 31 percentage points, respectively. Transmission and storage availability have much smaller effects, causing the average share to vary by no more than 15 and 5 percentage points, respectively. No single factor unilaterally determines wind and solar deployment. The variable renewable share of electricity generation never reaches 100% nationally in any scenario even with lowcost storage, as decreasing marginal returns at higher deployments eventually outpace cost reductions. Average wind and solar shares and ranges of possible outcomes are higher in this study relative to recent multi-model comparison studies due to lower renewable costs and the potential for more stringent policies. Understanding drivers and barriers to renewable deployment has important ramifications for technology developers, infrastructure, market design, and policymakers, and this research provides insights as to which combinations of drivers lead to the greatest share of economic wind and solar deployment and why.

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

Cited by 125 publications

References 78 publications

Buffering volatility: A study on the limits of Germany's energy revolution

Buffering volatility: A study on the limits of Germany's energy revolution

The role of capital costs in decarbonizing the electricity sector

Economic drivers of wind and solar penetration in the US

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