首页> 外文会议>2010 IEEE International Conference on Control Applications >Reinforcement Learning based multi-agent LFC design concerning the integration of wind farms
【24h】

Reinforcement Learning based multi-agent LFC design concerning the integration of wind farms

机译:基于增强学习的多主体LFC设计,涉及风电场的集成

获取原文

摘要

Frequency regulation in interconnected networks is one of the main challenges posed by wind turbines in modern power systems. The wind power fluctuation negatively contributes to the power imbalance and frequency deviation. This paper presents an intelligent agent based load frequency control (LFC) for a multi-area power system in the presence of a high penetration of wind farms, using multi-agent reinforcement learning (MARL). Nonlinear time-domain simulations on a 39-bus test power system are used to demonstrate the capability of the proposed control scheme.
机译:互连网络中的频率调节是现代电力系统中风力涡轮机带来的主要挑战之一。风力波动会对功率不平衡和频率偏差产生负面影响。本文提出了一种基于智能代理的多区域电力系统负载频率控制(LFC),该系统使用多智能体强化学习(MARL)在高渗透率风电场的情况下使用。在39总线测试电源系统上的非线性时域仿真被用来证明所提出的控制方案的能力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号