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Computational Management Science

, Volume 13, Issue 1, pp 5–27 | Cite as

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

  • Pedro Crespo Del Granado
  • Stein W. Wallace
  • Zhan Pang
Original Paper

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.

Keywords

Smart grid Wind energy Energy storage Uncertainty Valuation Stochastic programming 

Notes

Acknowledgments

We thank the Facilities Department at Lancaster University for providing information on the campus energy system as well as electricity demand data. Likewise, to the Lancaster Environmental Center for sharing high frequency data on historical wind speeds. Lastly, our acknowledgements to the Department of Management Science at Lancaster University and the Department of Business and Management Science at The Norwegian School of Economics for facilitating research visits.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Energy Science CenterETH ZürichZurichSwitzerland
  2. 2.Department of Management ScienceLancaster University Management SchoolLancasterUK
  3. 3.Department of Business and Management ScienceNorwegian School of EconomicsBergenNorway

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