摘要
多区域互联系统通常是水火电自动发电控制(AGC)机组并存系统,系统的非线性因素及复杂性使得基于线性理论的比例积分调节方式不能适应智能电网的要求。文中针对水轮机系统的非线性特点,将环境知识转化成强化学习算法的先验知识以加快AGC的调整速度。在此基础上,完整阐述了水火电混杂的多区域系统基于强化学习算法的自动发电智能化控制设计思想。为使模型更具一般性,建立了三区域混杂系统仿真模型,仿真结果验证了该方法的可行性。
Normally,the hydro and thermal automatic generation control （AGC） units exist simultaneously in a multi-area interconnected system. Owing to the inherent non-linearity and complexity of the system,it＇s hard for an AGC system based on classical linear control theory to meet the requirements for smart grid development. In light of the non-linear characteristics of the hydro unit system,the reinforcement learning method is employed to transform AGC environment knowledge into prior knowledge to develop the AGC controller of a hydro-unit. A detailed analysis is made of the AGC controller design for the multi-area hybrid system of a hydro-power unit and thermal-power unit. In order to generalize the model proposed,a typical three-area hybrid system model is developed with the feasibility of the design method shown by simulation results.
出处
《电力系统自动化》
EI
CSCD
北大核心
2010年第9期39-43,共5页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(90612018)~~
关键词
自动发电控制(AGC)
水火混杂系统
非线性
先验知识
Q学习
automatic generation control （AGC）
hydro-thermal hybrid system
non-linearity
prior knowledge
Q-learning
