Wind Farm Portfolio Optimization under Network Capacity Constraints

Hélène Le Cadre (1) , Anthony Papavasiliou (2) , Yves Smeers (2)

1 CMA - Centre de Mathématiques Appliquées
2 UCL - Université Catholique de Louvain = Catholic University of Louvain

In this article, we provide a new methodology for optimizing a portfolio of wind farms within a market environ- ment, 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 other markets, 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 a case study of France, Germany and Belgium, we simulate the Markowitz Frontier contour in the expected cost-conditional variance plane.

Mots clés: Algorithmic Game Theory; Market Design; Renewable Capacity Investment; Markowitz Frontier

Domaines: Recherche opérationnelle [math.OC]; Économie et finance quantitative [q-fin]; Sciences de l'ingénieur [physics]

Hélène Le Cadre, Anthony Papavasiliou, Yves Smeers. Wind Farm Portfolio Optimization under Network Capacity Constraints. 2014. ⟨hal-01007992v2⟩