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基于多智能体一致性协议的微电网分层分布实时优化策略
作者:
作者单位:

1. 上海交通大学电子信息与电气工程学院, 上海市 200240; 2. 广州供电局有限公司, 广东省广州市 510000

摘要:

经济运行、频率和电压控制及系统稳定性是微电网实时控制的主要内容。基于多智能体系统一致性协议,提出了一种分层分布的实时优化策略。首先,在仅考虑分布式电源出力约束的条件下,应用一阶一致性实现对分布式电源有功出力的控制,优化运行成本;其次,针对下垂控制特性,提出了一种新的二阶一致性协议,用于实现分布式电源功率的精确控制;最后,应用一致性协议实时协调分布式电源的下垂参数,实现了系统频率和电压的优化。通过Lyapunov直接法对所提策略进行稳定性分析,证明系统是渐进稳定的。仿真分析及结果验证了所提策略的有效性。

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基金项目:

国家自然科学基金资助项目(51577115);国家重点研发计划资助项目(2016YFB0901300)

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Hierarchical Distributed Real-time Optimization Strategy for Microgrid Based on Consistency Protocol of Multi-agent System
Author:
Affiliation:

1. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; 2. Guangzhou Power Supply Co. Ltd., Guangzhou 510000, China

Abstract:

Economic dispatch, frequency and voltage control, and system stability are still important problems in real-time control for microgrid. Based on the consensus protocol of multi-agent system, this paper presents a hierarchical distribution real-time optimization strategy. Firstly, a first-order consensus protocol is applied to calculate the active power of distributed generators(DGs)when only the constraint on output power is to be considered. Secondly, based on the secondary-order agent model of active power regulation for DGs, a novel consensus protocol is proposed to make the DG export the reference active power given in the first layer. Finally, the consensus protocol is used to adjust the droop parameters adaptively so that the system frequency and voltage are optimized as expected. The system is in globally asymptotic stability under the proposed strategy through the analysis of Lyapunov direct method. Simulation analysis and results have verified the effectiveness of the proposed strategy.

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引用本文
[1]余志文,艾芊,熊文.基于多智能体一致性协议的微电网分层分布实时优化策略[J].电力系统自动化,2017,41(18):25-31. DOI:10.7500/AEPS20170105009.
YU Zhiwen, AI Qian, XIONG Wen. Hierarchical Distributed Real-time Optimization Strategy for Microgrid Based on Consistency Protocol of Multi-agent System[J]. Automation of Electric Power Systems, 2017, 41(18):25-31. DOI:10.7500/AEPS20170105009.
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  • 收稿日期:2017-01-05
  • 最后修改日期:2017-07-18
  • 录用日期:2017-05-05
  • 在线发布日期: 2017-07-04
  • 出版日期: