Game Theoretic Receding Horizon Cooperative Network Formation for Distributed Microgrids: Variability Reduction of Photovoltaics

This paper investigates cooperative energy network formation for distributed autonomous microgrids based on receding horizon control and game theoretic cooperative control. In particular, we focus on photovoltaics and aim at minimizing its temporal and spatial variability while reducing transmission losses over the whole network by forming an appropriate network of power transmissions. We first formulate a novel optimal network formation problem in the form of resource allocation games so that the welfare function reflects the above objectives. Then, the problem is reduced to a potential game through an existing utility design technique. The paper next presents a variation of a learning algorithm presented in one of the authors' previous works and newly provide a proof of convergence in probability to potential function maximizers. Moreover, we consider real time implementation of the presented framework based on receding horizon control, where it is shown that the information processing of the learning algorithm is almost distributed with the helps of a solar radiation forecasting/estimation system. Finally, this paper illustrates the effectiveness of the present approach through simulation using real data of a solar radiation estimation system.