Adaptive mixed strategy load management in dc microgrids for wireless communications systems

Abstract

This paper proposes an adaptive mixed game control algorithm to realize optimal load planning in cell sites forming a microgrid powered by renewable sources. Cell site controllers use renewable sources power generation and local load predictions to plan future coordinated load management, renewable power generation and local energy storage. Mixed game methods have been proved to offer an adequate solution for optimal load planning in a dc microgrid powered by renewable energy sources, but it tends to require significant knowledge of system characteristics and accurate estimation of renewable source generated power and load, in this case due to communications traffic. In this paper, we explore necessary system conditions for implementing a mixed game control strategy. Additionally, an adaptive controller is introduced to improve performance by updating renewable power generation and communication traffic load models by providing the controller a better estimation and, thus, improving the performance of the game control method when actual renewable power and communication traffic load deviate from the preset model. The adaptive control scheme is designed based on Lyapunov stability theory. Simulation results show the adaptive controller can significantly improve mixed game method performance.