Optimal Operation of Virtual Power Plants Based on Stackelberg Game Theory

被引:0
|
作者
Zhang, Weishi [1 ]
He, Chuan [1 ]
Wang, Haichao [1 ]
Qian, Hanhan [1 ]
Lin, Zhemin [1 ]
Qi, Hui [1 ]
机构
[1] Anhui Power Exchange Ctr Co Ltd, Hefei 230022, Peoples R China
关键词
virtual power plant; Stackelberg game; deep reinforcement learning; operation optimization; DEMAND RESPONSE;
D O I
10.3390/en17153612
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
As the scale of units within virtual power plants (VPPs) continues to expand, establishing an effective operational game model for these internal units has become a pressing issue for enhancing management and operations. This paper integrates photovoltaic generation, wind power, energy storage, and constant-temperature responsive loads, and it also considers micro gas turbines as auxiliary units, collectively forming a typical VPP case study. An operational optimization model was developed for the VPP control center and the micro gas turbines, and the game relationship between them was analyzed. A Stackelberg game model between the VPP control center and the micro gas turbines was proposed. Lastly, an improved D3QN (Dueling Double Deep Q-network) algorithm was employed to compute the VPP's optimal operational strategy based on Stackelberg game theory. The results demonstrate that the proposed model can balance the energy complementarity between the VPP control center and the micro gas turbines, thereby enhancing the overall economic efficiency of operations.
引用
收藏
页数:15
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