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Reformulations of a Bilevel Model for Detection of Tacit Collusion in Deregulated Electricity Markets

Authors: Çelebi, Emre; Şahin, Güvenç; Esmaeilialiabadi, Danial;

Reformulations of a Bilevel Model for Detection of Tacit Collusion in Deregulated Electricity Markets

Abstract

In this study, we consider a collusion model for competitive pool based electricity markets operated by an independent system operator (ISO), where it aims to prevent tacit collusion among generators. In order to determine the existence of tacit collusion in the market, we have employed the the game-theoretic bilevel optimization model proposed by [1]. This model represents the market clearing mechanism, where generators determine their bids in order to maximize their profit while the system operator allocates power and determine locational electricity prices. The resulting optimization problem is a bilevel multi-criteria problem with non-linear terms, which is already complex and difficult to solve. We provide reformulations and linearization methods to obtain equivalent problems, e.g., a mathematical problem with equilibrium constraints (MPEC), a mixed integer non-linear problem (MINLP) and a mixed integer problem (MIP). A simple 6-bus system is used to test the rate of detection for collusive states for the reformulations and the results are presented. We have found that MIP models and reformulations detect strong collusive states. This model can guide ISOs in identifying and preventing cases of generator collusion.

Country
Turkey
Keywords

Electricity markets, Bilevel optimization, Tacit collusion, T57.6-57.97 Operations research. Systems analysis, Game theory, Reformulations

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green