智能电网环境下家庭能源管理系统优化调度算法  

A scheduling algorithm for home energy management system in smart grid

作　　者：张延宇[1,2,3] 曾鹏[1] 臧传治[1] 

机构地区：[1]网络化控制系统重点实验室,中国科学院沈阳自动化研究所,辽宁沈阳110016 [2]河南大学计算机与信息工程学院,河南开封475004 [3]中国科学院大学,北京100049

出　　处：《电力系统保护与控制》2016年第2期18-26,共9页Power System Protection and Control

基　　金：国家高技术研究发展计划资助项目(863计划)(2011AA040103);国家自然科学基金资助项目(61233007,61300215);国家科技重大专项基金资助项目(2013ZX03005004)~~

摘　　要：在智能电网环境下,提出了一种家庭能源管理系统框架和优化调度算法。根据室外温度预测值、可再生能源功率输出预测值、日前电价信号和用户偏好,算法对可调度用电负载、电动汽车、储能系统的运行进行优化调度从而最小化用户用电费用。算法考虑了电动汽车在高电价时段通过V2H(vehicle to home,V2H)功能向负载供电的情形,采用情景分析法处理室外温度和可再生能源功率输出预测的不确定性。通过仿真实验验证了算法性能,结果表明与只对负载或家庭能源管理系统部分组成部件进行优化调度的算法相比,所提算法显著降低了用电费用。To minimize electricity fee of a residential user, a framework and a scheduling algorithm for home energy management system（HEMS） in smart grid are proposed. The algorithm controls loads, plug-in hybrid electric vehicle（PHEV）, and energy storage system according to predicted outdoor temperature, renewable resource power output, day-ahead electricity price, and user preferences. In this algorithm, the PHEV can supply stored power to other loads through V2H（vehicle to home, V2H） in high electricity price periods. Scenario analysis technique is utilized to cope with the uncertainty due to the error of predicted outdoor temperature and renewable resource power output. The effectiveness of the algorithm is verified by simulation, and simulation results show that compared to other algorithms which only control loads or parts of HEMS, it can reduce the electricity fee significantly.

关 键 词：智能电网 需求响应 家庭能源管理系统 粒子群算法 V2H 

分 类 号：TM73[电气工程—电力系统及自动化]