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Distributed optimization and game theoretical analysis in energy markets applications


S. Curi

Semester Thesis, FS16 (10524)

In this project the energy market is analyzed using game theoretical methods. A free market and two markets with price intervention are modeled as games. The difference between selecting the dispatch as the game equilibrium or as the point that maximizes the social welfare in the Pareto sense is discussed for each model. In these games, the players are producers and consumers who want to minimize their cost and maximize their utility, respectively. The players’ decision variables is an energy production (or consumption) schedule for a given time horizon. A particular feature of this market is that at every time instant the energy consumption and production have to meet. This imposes a constraint in the game that couples the schedule of the different players. An independent system operator is present in these games to ensure this constraint to be met. To find a solution to these games the variational inequality framework is used. This set of tools introduces centralized and distributed algorithms to find the variational equilibria. Finally, these models are simulated for homogeneous and heterogeneous producers. The difference of the dispatch profile and of the resulting price between the different models is discussed.

Supervisors: Francesca Parise, Basilio Gentile, Maryam Kamgarpour, John Lygeros


Type of Publication:

(13)Semester/Bachelor Thesis

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2016:IFA_5450
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