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The impact of wind uncertainty on the strategic valuation of distributed electricity storage

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  • Pedro Crespo Del Granado
  • Stein Wallace
  • Zhan Pang

Abstract

The intermittent nature of wind energy generation has introduced a new degree of uncertainty to the tactical planning of energy systems. Short-term energy balancing decisions are no longer (fully) known, and it is this lack of knowledge that causes the need for strategic thinking. But despite this observation, strategic models are rarely set in an uncertain environment. And even if they are, the approach used is often inappropriate, based on some variant of scenario analysis—what-if analysis. In this paper we develop a deterministic strategic model for the valuation of electricity storage (a battery), and ask: “Though leaving out wind speed uncertainty clearly is a simplification, does it really matter for the valuation of storage?”. We answer this question by formulating a stochastic programming model, and compare its valuation to that of its deterministic counterpart. Both models capture the arbitrage value of storage, but only the stochastic model captures the battery value stemming from wind speed uncertainty. Is the difference important? The model is tested on a case from Lancaster University’s campus energy system where a wind turbine is installed. From our analysis, we conclude that considering wind speed uncertainty can increase the estimated value of storage with up to 50 % relative to a deterministic estimate. However, we also observe cases where wind speed uncertainty is insignificant for storage valuation. Copyright Springer-Verlag Berlin Heidelberg 2016

Suggested Citation

  • Pedro Crespo Del Granado & Stein Wallace & Zhan Pang, 2016. "The impact of wind uncertainty on the strategic valuation of distributed electricity storage," Computational Management Science, Springer, vol. 13(1), pages 5-27, January.
    • Handle: RePEc:spr:comgts:v:13:y:2016:i:1:p:5-27
    DOI: 10.1007/s10287-015-0235-0
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    References listed on IDEAS

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    1. He, Xian & Delarue, Erik & D'haeseleer, William & Glachant, Jean-Michel, 2011. "A novel business model for aggregating the values of electricity storage," Energy Policy, Elsevier, vol. 39(3), pages 1575-1585, March.
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    Cited by:

    1. Iver Bakken Sperstad & Magnus Korpås, 2019. "Energy Storage Scheduling in Distribution Systems Considering Wind and Photovoltaic Generation Uncertainties," Energies, MDPI, vol. 12(7), pages 1-24, March.
    2. Ida Bakke & Stein-Erik Fleten & Lars Ivar Hagfors & Verena Hagspiel & Beate Norheim & Sonja Wogrin, 2016. "Investment in electric energy storage under uncertainty: a real options approach," Computational Management Science, Springer, vol. 13(3), pages 483-500, July.
    3. Hashemipour, Naser & Crespo del Granado, Pedro & Aghaei, Jamshid, 2021. "Dynamic allocation of peer-to-peer clusters in virtual local electricity markets: A marketplace for EV flexibility," Energy, Elsevier, vol. 236(C).

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