基于集成学习的孤岛微电网源—荷协同频率控制  

Ensemble Learning for Generation-Consumption Coordinated Frequency Control in an Islanded Microgrid

作　　者：王德志[1,2] 张孝顺 刘前进[1,2] 余涛[1,2] 潘振宁[1,2] WANG Dezhi;ZHANG Xiaoshun;LIU Qianjin;YU Tao;PAN Zhenning(School of Electric Power, South China University of Technology, Guangzhou 510640, China;Guangdong Key Laboratory of Green Energy Technology, School of Electric Power, South China University of Technology, Guangzhou 510640, China)

机构地区：[1]华南理工大学电力学院,广东省广州市510640 [2]广东省绿色能源技术重点实验室华南理工大学电力学院,广东省广州市510640

出　　处：《电力系统自动化》2018年第10期46-52,共7页Automation of Electric Power Systems

基　　金：国家自然科学基金资助项目(51777078)~~

摘　　要：提出一种基于集体智慧的集成学习算法,以实现孤岛微电网下分布式电源与负荷的协同频率控制。通过引入负荷聚合商来对大规模家庭用户进行聚合,解决源—荷协同频率控制下的"维数灾难"问题。负荷聚合商根据每个家庭中温控设备的运行状态,可以连续地评估其可参与辅助调频的储备能力。集成学习算法由多个子优化器和一个学习集中器组成,子优化器发挥集体智慧能力为学习集中器提供探索和开发样本,而强化学习主要用于知识学习与迁移。通过孤岛微电网的仿真算例可以验证集成学习能够有效满足源—荷协同频率控制的周期要求和质量要求。A novel ensemble learning（EL）method is proposed to achieve an optimal generation-consumption coordinated frequency control in an islanded microgrid.To solve the ＂dimension disaster＂under the optimal generation-consumption coordinated frequency control,a large number of household consumers are aggregated as a load aggregator（LA）,which can be equivalent to a generator.The LA can continuously evaluate the minimal and maximal reserve capabilities according to the operation state of each thermostatically controlled load.The EL is composed of multiple sub-optimizers and a learning concentrator,where each sub-optimizer is responsible for providing the exploitation and exploration samples to the learning concentrator,while the reinforcement learning based concentrator is mainly used for knowledge learning and transfer.Case studies are thoroughly carried out to verify the performance of EL for the generation-consumption coordinated frequency control in an islanded microgrid.

关 键 词：源-荷协同 频率控制 集成学习 强化学习 

分 类 号：TM727[电气工程—电力系统及自动化]