基于需求响应的家庭能量双层优化调度  

Two-Tier Optimal Scheduling of Household Energy Based on Demand Response

作　　者：王辉[1] 方航 金子蓉 李旭阳 WANG Hui;FANG Hang;JIN Zirong;LI Xuyang(School of Electrical and New Energy,China Three Gorges University,Yichang Hubei 443002,China)

机构地区：[1]三峡大学电气与新能源学院,湖北宜昌443002

出　　处：《广西师范大学学报（自然科学版）》2023年第1期38-47,共10页Journal of Guangxi Normal University:Natural Science Edition

基　　金：国家自然科学基金(52007103)。

摘　　要：随着人民生活水平的提升,家庭用电负荷也在逐渐升高,本文针对降低家庭用电支出问题,考虑需求响应在分时电价环境下,采用双层优化策略。上层是对家庭用电设备分类调度,通过对家庭设备分类调整,将可调度负荷从电价高的时间段调节到低电费的平时段和谷时段运行,从而大大减少家庭用户的用电开支;下层对光伏发电设备和储能设备出力时段进行调整,通过储能设备和光伏设备的配合,合理高效地利用光伏能量。最后通过某典型家庭负荷配置为例,采用改进二阶振荡粒子群算法,分析仅对用电时段优化、用电时段和光伏均优化等不同场景,结果显示该优化算法在迭代23次左右达到稳定,优化后家庭用电支出减少53.64%,验证了文中所采用的双层优化调度有效性。With the improvement of people’s living standards,the household power load is also gradually increasing.Aiming at reducing household power expenditure,and based on the demand responseand and the environment of time phased pricing,a two-tier optimization strategy is adopted.Firstly,the upper layer of the strategy is the classified dispatching of household electrical equipment.Through the classified adjustment of household equipment,the schedulable load can be adjusted from the time period of high electricity price to the normal and valley periods of low electricity price,so as to greatly reduce the power consumption expenditure of household users;Secondly,the lower layer adjusts the output period of photovoltaic power generation equipment and energy storage equipment,and makes rational and efficient use of photovoltaic energy through the cooperation of energy storage equipment and photovoltaic equipment.Finally,taking a typical household load configuration as an example,the improved second-order oscillatory particle swarm optimization algorithm is used to analyze different scenarios such as power consumption period optimization,power consumption period and photovoltaic optimization,and verify the effectiveness of the two-tier optimal scheduling used in this paper.

关 键 词：降低用电支出 双层优化 分时电价 改进二阶振荡粒子群算法 

分 类 号：TM73[电气工程—电力系统及自动化]