Research on Optimal Strategy of Peak-shaving of Photovoltaic Grid-connected System Based on Simulated Annealing-Q Learning Algorithm

Abstract

In order to alleviate the problem of large-scale grid-connected photovoltaics and increase the pressure of grid peak regulation, this paper proposes a dynamic economic dispatch method considering the system peak regulation margin. The system peak shaving margin is proposed to deal with the flexibility problem in economic dispatch and improve the enthusiasm of thermal power unit peak shaving. The economic dispatch model is transformed into a dynamic programming model and solved by the simulated annealing-Q learning algorithm. The analysis of the results shows that the proposed dynamic programming strategy can effectively improve the operating economy of the system and increase the flexibility of peak shaving of thermal power units.