Game-theoretic robust optimization for a small-scale integrated power system

Abstract

The dispatch of an integrated power system involves how to balance the interests of all participants and alleviate the negative effects of uncertainties. In this paper, a game-theoretic robust optimization approach for a small-scale integrated power system is proposed. This optimization approach consists of two stages, i.e. the day ahead dispatch stage and the realtime feedback correction stage. In the day ahead dispatch stage, a game theory based optimal algorithm is established to address the issue that participants in the power system have distinct objectives and their interests are in conflict. Using the gaming results of the day ahead dispatch, a realtime feedback correction algorithm is implemented to enhance the robustness of the power system against the uncertainties of renewable energy resources (RERs) and loads. It is shown that with the communication between the power plant, microgrids and independent end users, the Nash equilibrium can be reached after several iterations and the scheduling plan of each participant is obtained. Meanwhile, with the error prediction over a certain period prescribed in the future, the negative effects of uncertainties are extensively reduced. A small-scale power system is used as a case to illustrate the effectiveness of the proposed optimization approach.