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Virtual Power Plants Read chapter Read first chapter

2020 | OriginalPaper | Chapter

6. Price-Maker Virtual Power Plants

Authors : Luis Baringo, Morteza Rahimiyan

Published in: Virtual Power Plants and Electricity Markets

Publisher: Springer International Publishing

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Abstract

This chapter provides equilibrium-based mathematical models that can be used for scheduling price-maker virtual power plants (VPPs) participating in energy and reserve electricity markets. These mathematical models allow price-maker VPPs to influence the prices in these markets to their own benefit, i.e., the proposed models allow VPPs to exercise market power. Uncertainties in market prices, production levels of stochastic renewable generating units, and reserve deployment requests are addressed in the problem using two different methods based on deterministic and stochastic programming approaches.

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previous chapter Optimal Scheduling of a Virtual Power Plant in Energy and Reserve Markets
next chapter Expansion Planning of Virtual Power Plants
Literature
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Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge, University Press (2009)MATH
2.
Conejo, A.J., Carrión, M., Morales, J.M.: Decision Making Under Uncertainty in Electricity Markets. Springer, New York, US (2010)CrossRef
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Gabriel, S.A., Conejo, A.J., Fuller, J.D., Hobbs, B.F., Ruiz, C.: Complementarity Modeling in Energy Markets. Springer, New York, US (2013)CrossRef
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Kardakos, E.G., Simoglou, C.K., Bakirtzis, A.G.: Optimal offering strategy of a virtual power plant: a stochastic bi-level approach. IEEE Trans. Power Syst. 7(2), 794–806 (2016)
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Pourghaderi, N., Fotuhi-Firuzabad, M., Moeini-Aghtaie, M., Kabirifar, M.: Commercial demand response programs in bidding of a technical virtual power plant. IEEE Trans. Ind. Inf. 14(11), 5100–5111 (2018)CrossRef
Metadata
Title
Price-Maker Virtual Power Plants
Authors
Luis Baringo
Morteza Rahimiyan
Copyright Year
2020
Book
Virtual Power Plants and Electricity Markets

Print ISBN: 978-3-030-47601-4

Electronic ISBN: 978-3-030-47602-1

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-47602-1_6