中国电机工程学报2018，Vol.38Issue(4)：1054-1064,后插10,12.DOI:10.13334/j.0258-8013.pcsee.170472
基于数据挖掘的电动汽车充电设施配置与 两阶段充电优化调度
Electric Vehicle Charging Facilities Planning and Its Two-stage Optimal Charging Based on Data Mining
摘要
Abstract
The greatly increase of electric vehicle charging load brings challenges to the operation of power systems. Based on the data of distribution transformers operation, we proposed the charging facilities configuration method and designed a three phases optimal charging method. The charging facilities configuration depended on two transformer's indexes which resulting from data mining: capacity redundancy rate and deviation degree of different phases. In first stage of optimal charging, determined the electric vehicle ordered charging facility by real time power flow. In second stage, the charging power control was implemented based on the state of system and the trend characteristic value, the latter factor was also came from the distribution transformers operation data. Conducted experiments prove the effectiveness of the proposed method.关键词
数据挖掘/配变运行数据/功率冗余度/相偏差度/走势特征值/充电设施配置/三相优化充电Key words
data mining/distribution transformers operation data/capacity redundancy rate/phase deviation degree/trend characteristic value/charging facilities configuration/three phase optimal charging分类
信息技术与安全科学引用本文复制引用
张程嘉,刘俊勇,向月,刘友波,李蕴,刘定乾..基于数据挖掘的电动汽车充电设施配置与 两阶段充电优化调度[J].中国电机工程学报,2018,38(4):1054-1064,后插10,12.基金项目
国家自然科学基金项目(51377111,51437003) （51377111,51437003）
中央高校基本科研业务费专项资金(YJ201654) （YJ201654）
四川省电力电子节能技术与装备重点实验室开放基金(szjj2017-052). Project Supported by National Natural Science Foundation of China (51377111, 51437003) （szjj2017-052）
Supported by the Fundamental Research Funds for the central Universities (YJ201654) （YJ201654）
Supported by the Open Research Subject of Key Laboratory of Sichuan Power Electronics Energy-saving Technology and Devices (szjj2017-052). （szjj2017-052）
