摘要
无功电压调控是保障电网区域电压稳定的重要措施,现有基于强化学习的单一智能体设计方式存在架构设计不合理等问题。文中提出了一种考虑节点电压幅值与电容器投切状况的电网综合运行状态描述方法,设计了面向电网无功电压调控的强化学习智能体群组架构。该群组根据电网当前综合运行状态确定智能体成员,并给出相应的无功调控动作,各智能体成员将相邻时段电网状态改善程度作为奖励机制。算例表明该方法可应用于电网无功电压调控环境,相较于单一智能体设计方式,可以有效减少动作集数量,更好地应对各种无功电压调控工况。
Reactive voltage regulation is an important control measure to ensure voltage stability in the power grid area.The existing single agent design method based on reinforcement learning has many problems,such as high coupling between state and action,various combinations of reactive power compensation devices,and unreasonable reward design based on target deviation model.Aiming at these problems,a method for describing the integrated operation state of the grid considering the node voltage amplitude and capacitor switching condition is proposed.The reinforcement learning agent group architecture for grid reactive voltage regulation is designed.The group determines the members of the agent according to the current comprehensive operating state of the grid,and gives corresponding reactive power regulation actions.Each agent member uses the improvement degree of the grid state in the adjacent time period as a reward mechanism.The example shows that the method can be applied to the grid reactive voltage regulation environment.Compared with the single agent design method,the number of action sets can be effectively reduced,and various reactive voltage regulation conditions can be better dealt with.
作者
范士雄
刘幸蔚
魏智慧
刘瑞叶
王松岩
于继来
FAN Shixiong;LIU Xingwei;WEI Zhihui;LIU Ruiye;WANG Songyan;YU Jilai(China Electric Power Research Institute Co.,Ltd.,Beijing 100192,China;School of Electrical Engineering and Automation,Harbin Institute of Technology,Harbin 150001,China)
出处
《电力工程技术》
2020年第2期10-17,共8页
Electric Power Engineering Technology
基金
国家电网有限公司科技项目“基于人工智能技术的电网调控体系架构及电网无功电压控制典型应用技术研究”。
关键词
无功电压
强化学习
人工智能
智能体群组
电容器投切
reactive power and voltage
reinforcement learning
artificial intelligence
agent group
capacitor switch
