电工技术学报2012，Vol.27Issue(4)：185-192,8.
基于分布式多步回溯Q（λ）学习的复杂电网最优潮流算法
Optimal Power Flow for Complex Power Grid Using Distributed Multi-Step Backtrack Q（λ） Learning
摘要
Abstract
As for the problem that usual optimal power flow algorithm can not meet the timely demand of the complex power grid.,this paper presents a novel distributed Q（λ） learning algorithm based on complex districted power grid,which deals no auxiliary process with the optimal power flow（OPF） mathematical model and whose internal agent independently undertakes each district＇s learning duty with the standard multi-step Q（λ） learning algorithm,and then coordinately cooperate to reach the optimization of the whole system.The result of the application in IEEE118 bus bar demonstrates that the distributed Q（λ） learning algorithm provides a new feasible and effective method to the complex grid OPF problem.关键词
最优潮流/Q（λ）学习/多目标优化/分布式强化学习Key words
Optimal power flow/Q(λ) learning/multi-objective optimization/distributed reinforcement learning分类
信息技术与安全科学引用本文复制引用
余涛,刘靖,胡细兵..基于分布式多步回溯Q（λ）学习的复杂电网最优潮流算法[J].电工技术学报,2012,27(4):185-192,8.基金项目
国家自然科学基金 （）
清华大学国家重点实验室开放项目 （）
中央高校基本业务费重点项目资助 （）
