Optimal economic dispatch of a virtual power plant based on gated recurrent unit proximal policy optimization - Gao, Zhiping; Kang, Wenwen; Chen, Xinghua; Gong, Siru; Liu, Zongxiong; He, Degang; Shi, Shen; Shangguan, Xing-Chen (Frontiers in Energy Research, 2024)
The intermittent renewable energy in virtual power plant (VPP) brings generation uncertainties, which prevents the VPP from providing a reliable and friendly power supply. This paper proposes a gated recurrent unit proximal policy optimization (GRUPPO) based optimal VPP economic dispatch. Firstly, electrical generation, storage, and consumption are established to form a VPP framework by considering the accessibility of VPP state information. The optimal VPP economic dispatch can then be expressed as a partially observable Markov decision process (POMDP) problem. A novel deep reinforcement learning method, called GRUPPO is further developed based on VPP time series characteristics. Finally, cased studies are conducted with 24-hour based on the actual historical data. The tested results illustrate that the proposed economic dispatch can achieve at most 6.5% operation cost reduction and effectively smooth the uncertain supply-demand