Wind Farm Portfolio Optimization under Network Capacity Constraints
Résumé
In this article, we provide a new methodology for optimizing a portfolio of wind farms in a Market Coupling organization, for two Market Designs (exogenous prices and endogenous prices). Our model is built on an agent based representation of a certain number of interacting geographic demand markets, each facing a bilevel program to optimize its production level and bilateral trades with the others while anticipating the grid congestion. The Nash Equilibria resulting from this Signaling Game are characterized using Algorithmic Game Theory. The Markowitz Frontier, containing the set of efficient wind farm portfolios, is derived theoretically as a function of the number of wind farms and of their concentration. Finally, using France-Germany-Belgium real life data, we simulate the Markowitz Frontier contour in the expected cost-conditional variance plane.
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