引用本文:许少伦,严 正,冯冬涵,张 良.基于多智能体的电动汽车充电协同控制策略[J].电力自动化设备,2014,34(11):
XU Shaolun,YAN Zheng,FENG Donghan,ZHANG Liang.Cooperative charging control strategy of electric vehicles based on multi-agent[J].Electric Power Automation Equipment,2014,34(11):
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基于多智能体的电动汽车充电协同控制策略
许少伦, 严 正, 冯冬涵, 张 良
上海交通大学 电气工程系 电力传输与功率变换控制教育部重点实验室,上海 200240
摘要:
在分析电动汽车充电负荷特性、管理架构的基础上,借鉴复杂自适应系统的核心思想,提出基于多智能体的电动汽车充电管理模式。建立单台电动汽车的充电负荷模型和基于多智能体系统的电动汽车充电优化模型。采用蒙特卡洛方法模拟电动汽车用户的充电行为。在考虑电动汽车的充电功率、充电时间以及变压器可用容量等约束条件的前提下,针对35 kV片区配电网中电动汽车接入充电的优化问题,提出基于多智能体协同控制的电动汽车充电优化策略。仿真结果表明多智能体协同控制策略能够有效地实现电动汽车充电负荷的“移峰填谷”,减小电网峰谷差。
关键词:  电动汽车  充电优化  多智能体  协同控制  复杂自适应系统  模型  负荷管理
DOI:
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基金项目:国家高技术研究发展计划(863计划)项目(2012AA-050803);新能源电力系统国家重点实验室开放课题(LAPS13009)
Cooperative charging control strategy of electric vehicles based on multi-agent
XU Shaolun, YAN Zheng, FENG Donghan, ZHANG Liang
Key Laboratory of Control of Power Transmission and Conversion,Ministry of Education,Department of Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China
Abstract:
Based on the analysis of charging load characteristics and management structure of EV(Electric Vehicle),a charging management mode of EV based on multi-agent is proposed according to the core idea of complex adaptive system. A charging load model of a single EV and an optimal charging model of EV based on multi-agent are built. The Monte Carlo method is applied to simulate the charging performance of EV customers. With the consideration of constraints such as charging power,charging time and available capacity of transformer,an optimal cooperative control charging strategy of EV based on multi-agent is proposed for the problem of EV charging from a 35 kV distribution network. Simulative results show that,the strategy can effectively realize load shifting of EV charging load,reducing peak-valley difference.
Key words:  electric vehicles  charging optimization  multi-agent  cooperative control  complex adaptive system  models  electric load management

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