Abstract
This paper applies bilevel optimization techniques and fuzzy set theory to model and support bidding strategy making in electricity markets. By analyzing the strategic bidding behavior of generating companies, we build up a fuzzy bilevel optimization model for day-ahead electricity market strategy making. In this model, each generating company chooses the bids to maximize the individual profit. A market operator solves an optimization problem based on the minimization purchase electricity fare to determine the output power for each unit and uniform marginal price. Then, a particle swarm optimization (PSO)-based algorithm is developed for solving problems defined by this model.
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© 2009 Springer-Verlag Berlin Heidelberg
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Zhang, G., Zhang, G., Gao, Y., Lu, J. (2009). A Fuzzy Bilevel Model and a PSO-Based Algorithm for Day-Ahead Electricity Market Strategy Making. In: Velásquez, J.D., RÃos, S.A., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science(), vol 5712. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04592-9_91
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DOI: https://doi.org/10.1007/978-3-642-04592-9_91
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04591-2
Online ISBN: 978-3-642-04592-9
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