A Day-Ahead Economic Dispatch Scheme for Transmission System With High Penetration of Renewable Energy

Abstract

The great uncertainty caused by the high penetration of renewable energy brings severe challenges to the economic dispatch of transmission systems. In this study, a day-ahead economic dispatch model is proposed. The model is based on the coordination framework of transmission and distribution, and it fully considers the response potential of the distribution network. The scenario generation method based on the Copula function is used to describe the uncertainty of the energy output of renewable energy sources such as wind power, and then, the response potential of the distribution network is analyzed. A day-ahead economic scheduling framework for transmission and distribution coordination is proposed, which is solved by a deep reinforcement learning algorithm. Finally, the effectiveness of the proposed method is verified through application to the IEEE 6-bus transmission network and the IEEE 7-bus distribution network.

Keywords

• The high penetration of renewable energy
• a day-ahead economic dispatch model
• transmission and distribution
• response potential
• deep reinforcement learning