A Game Theory Based Optimal Planning for a Hybrid Energy System Considering Time of Use Tariffs

Abstract

In this paper, a game theory based optimization algorithm is presented for optimal planning of hybrid energy systems. Considering wind turbine, photovoltaic, and battery energy storage systems as rational players, all feasible cooperative game models are defined to find the Nash equilibrium point and maximize the profit of the players, while the real data for solar irradiation, wind speed, and power consumption of local load are considered. As the main contribution of this paper, different time of use (ToU) tariffs for covering different time intervals of a day including off-peak, shoulder, and peak hours are utilized to determine the cost of purchasing power from the grid, and consequently, to enhance the accuracy of the developed optimal planning compared with the recently presented approaches. The effectiveness of proposed strategy is verified using MATLAB software and compared with the fixed tariff based solutions. The simulation results confirms impact of ToU tariffs on the planning's results so that the accuracy of the developed optimal planning is improved using the proposed strategy.