供需两侧协同优化的电动汽车充放电自动需求响应方法  

Automated Demand Response Method for Electric Vehicles Charging and Discharging to Achieve Supply-demand Coordinated Optimization

作　　者：杨晓东[1] 张有兵[1] 赵波[2] 周文委[1] 翁国庆[1] 程时杰[3] 

机构地区：[1]浙江工业大学信息工程学院,浙江省杭州市310023 [2]国网浙江省电力公司电力科学研究院,浙江省杭州市310014 [3]强电磁工程与新技术国家重点实验室(华中科技大学),湖北省武汉市430074

出　　处：《中国电机工程学报》2017年第1期120-129,共10页Proceedings of the CSEE

基　　金：国家自然科学基金项目(51207140);浙江省自然科学基金重点项目(Z1110893);浙江省自然科学基金项目(LY16E070005)~~

摘　　要：自动需求响应(automatic demand response,ADR)是能源互联时代需求响应的最新实现形式,研究如何实现电动汽车的充放电ADR,有助于提升响应水平。为此提出供需两侧协同优化的电动汽车充放电ADR方法,该方法在综合考虑用户充电需求和配网负荷水平的条件下,以用户充放电收益最大、平抑系统负荷波动为目标,协调基于价格、激励的需求响应开展ADR项目。在此基础上,采用条件风险价值为风险计量指标,结合用户心理,建立用户响应意愿自动决策模型,以实现配网内电动汽车充放电的ADR。以某配电系统为例的仿真结果表明,相较于无序充电和基于价格的需求响应,所提方法能够协同优化供需两侧,显著提高需求侧车均年收益;有效平抑供电侧负荷波动及削减负荷峰值。Automatic demand response （ADR） is the latest implementation in Energy Internet, and how to achieve it for electric vehicle （EV） charging and discharging helps to improve the response. In this work, an ADR method for EV charging and discharging was proposed to achieve supply-demand coordinated optimization （SDCO-ADR）. Taking the customer charging demands and distribution system load profile into account, the proposed method seeks to achieve the maximum consumers＇ profit and lower load fluctuation by conducting the ADR project with the incentive-based and price-sensitive demand response. On this basis, the automatic decision model for consumers＇ response willingness was built considering their mentality and the risk which takes the conditional value at risk as the measurement index, to realize automatic demand response for EV charging and discharging in distribution system. With a local distribution network as the test system, simulation results indicate that supply-demand coordinated optimization is achieved under the proposed method, the average annual earnings per vehicle can be improved greatly, and load variance and peak load can be reduced effectively.

关 键 词：电动汽车 自动需求响应 协同优化 充放电控制 条件风险价值 响应意愿 

分 类 号：TM73[电气工程—电力系统及自动化]