基于Multi-Agent协作强化学习的分布式发电系统的研究

随着可再生能源技术的飞速发展,风光互补分布式发电系统以其经济性和可靠性得到了越来越广泛的应用。文中提出了一种基于Multi-Agent的以能量管理为主要特征的分布式风光互补发电系统,将联合动作学习（JAL）模式作为多Agent的协作策略,并结合强化学习技术描述了多Agent协作学习的过程。以一个风光互补发电系统为例进行仿真,实验结果证明了这种方法的有效性。

Research of Distributed Power Generation System Based on Multi-Agent Co-operation Strengthens Study

With the development of renewable energy technology, the distributed wind-PV power system has a wider application. This paper proposes a distributed wind-PV power system based on Multi-Agent, whose main character is energy management, and describes the multi-agent cooperative reinforcement learning process using the joint action learning pattern as the cooperative strategy. The experiment of a distributed wind-PV power system shows the efficiency.