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2023 | OriginalPaper | Chapter

6. Optimizing Wind Power Participation in Day-Ahead Electricity Market Using Meta-heuristic Optimization Algorithms

Authors : Hamed Dehghani, Behrooz Vahidi

Published in: Energy Systems Transition

Publisher: Springer International Publishing

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Abstract

Recently, use of wind generation due to its clean and cheap power has been considerably increased. The presence of wind sources in power systems brings several challenges for the operators. They have difficulties to make suitable decisions for electricity market, due to uncertain nature of wind power. In this chapter, a new objective function considering wind power uncertainty is proposed to minimize total expected costs. To do so, a new procedure is presented to quantify probability density function (PDF) of each uncertainty interval based on wind power plant’s information. Considering the derived PDF, the objective function is formed and optimized by using meta-heuristic optimization algorithms. The results reveal a reduction in total expected cost has up to 20%.

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Metadata
Title
Optimizing Wind Power Participation in Day-Ahead Electricity Market Using Meta-heuristic Optimization Algorithms
Authors
Hamed Dehghani
Behrooz Vahidi
Copyright Year
2023
Book
Energy Systems Transition

Print ISBN: 978-3-031-22185-9

Electronic ISBN: 978-3-031-22186-6

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-3-031-22186-6_6