| 基于集成学习的孤岛微电网源-荷协同频率控制 |
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| 引用本文： | 王德志,张孝顺,刘前进,余涛,潘振宁.基于集成学习的孤岛微电网源-荷协同频率控制[J].电力系统自动化,2018,42(10):46-52. |
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| 作者姓名： | 王德志 张孝顺 刘前进 余涛 潘振宁 |
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| 作者单位： | 华南理工大学电力学院;广东省绿色能源技术重点实验室华南理工大学电力学院 |
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| 基金项目： | 国家自然科学基金资助项目(51777078) |
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| 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。
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| 关 键 词： | 源-荷协同 频率控制 集成学习 强化学习 |
| 收稿时间： | 2017/12/26 0:00:00 |
| 修稿时间： | 2018/4/9 0:00:00 |
Ensemble Learning for Generation-Consumption Coordinated Frequency Control in an Islanded Microgrid |
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| WANG Dezhi,ZHANG Xiaoshun,LIU Qianjin,YU Tao and PAN Zhenning.Ensemble Learning for Generation-Consumption Coordinated Frequency Control in an Islanded Microgrid[J].Automation of Electric Power Systems,2018,42(10):46-52. |
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| Authors: | WANG Dezhi ZHANG Xiaoshun LIU Qianjin YU Tao and PAN Zhenning |
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| Affiliation: | School of Electric Power, South China University of Technology, Guangzhou 510641, China; Guangdong Key Laboratory of Green Energy Technology, School of Electric Power, South China University of Technology, Guangzhou 510640, China,School of Electric Power, South China University of Technology, Guangzhou 510641, China; Guangdong Key Laboratory of Green Energy Technology, School of Electric Power, South China University of Technology, Guangzhou 510640, China,School of Electric Power, South China University of Technology, Guangzhou 510641, China; Guangdong Key Laboratory of Green Energy Technology, School of Electric Power, South China University of Technology, Guangzhou 510640, China,School of Electric Power, South China University of Technology, Guangzhou 510641, China; Guangdong Key Laboratory of Green Energy Technology, School of Electric Power, South China University of Technology, Guangzhou 510640, China and School of Electric Power, South China University of Technology, Guangzhou 510641, China; Guangdong Key Laboratory of Green Energy Technology, School of Electric Power, South China University of Technology, Guangzhou 510640, China |
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| Abstract: | |
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| Keywords: | generation-consumption coordination frequency control ensemble learning reinforcement learning |
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