基于改进粒子群算法的居民需求响应调度优化与仿真

doi:10.16182/j.issn1004731x.joss.20-FZ0473

系统仿真学报 ›› 2021, Vol. 33 ›› Issue (8): 1969-1979.doi: 10.16182/j.issn1004731x.joss.20-FZ0473

基于改进粒子群算法的居民需求响应调度优化与仿真

李华珍¹, 柳有权¹, 朱家伟¹, 廖强²

1.长安大学信息工程学院,陕西西安 710064;
2.罗克佳华科技集团股份有限公司,北京 101111

收稿日期:2020-03-25 修回日期:2020-06-17 发布日期:2021-08-19
通讯作者: 朱家伟(1988-),男,博士,讲师,研究方向为智能电网。E-mail: jiawei.zhu@chd.edu.cn
作者简介:李华珍(1997-),女,硕士,研究方向为智能电网。E-mail: 2019124057@chd.edu.cn
基金资助:
国家自然科学基金(61902039,61901057); 长安大学中央高校基本科研业务费(300102249110,300102249104)

Residential Demand Response Scheduling Optimization and Simulation based on an Improved PSO Algorithm

Li Huazhen¹, Liu Youquan¹, Zhu Jiawei¹, Liao Qiang²

1. School of Information Engineering, Chang'an University, Xi'an 710064, China;
2. RocKontrol Technology Group Co., Ltd, Beijing 101111, China

Received:2020-03-25 Revised:2020-06-17 Published:2021-08-19

摘要/Abstract

摘要： 针对居民生活用电缺乏系统、高效的管理导致家庭负荷能源利用率低、对电网造成潜在损害等问题,对居民家中可控设备的用电特性以及电动汽车储能特性分别进行建模,建立分时电价下家用设备的调度优化目标函数,并采用改进后的粒子群算法进行优化求解。通过算例仿真,对多种场景下的居民用电调度进行分析对比。实验结果证明,所提出的算法能够在满足居民用电舒适度的同时降低用电成本和平抑电网波动。

关键词: 需求响应, 分时电价, 电动汽车, 用电调度

Abstract: Aiming at the problems of low utilization rate of household load energy and the potential damage to the power grid caused by the lack of systematic and efficient management of household power consumption, the power consumption characteristics of controllable equipment and the energy storage characteristics of electric vehicles are modeled respectively, and the scheduling optimization objective function of household equipment under time of use price is established, and the improved particle swarm optimization algorithm is used to solve the problem. Through the example simulation, the residential power dispatching under various scenarios is analyzed. The experimental results show that the proposed algorithm can satisfy the residents' power consumption comfort, and simultaneously reduce the power consumption cost and suppress the grid fluctuation.

Key words: demand response, time-of-use price, electric vehicle, power scheduling

中图分类号:

TP391

李华珍, 柳有权, 朱家伟, 廖强. 基于改进粒子群算法的居民需求响应调度优化与仿真[J]. 系统仿真学报, 2021, 33(8): 1969-1979.

Li Huazhen, Liu Youquan, Zhu Jiawei, Liao Qiang. Residential Demand Response Scheduling Optimization and Simulation based on an Improved PSO Algorithm[J]. Journal of System Simulation, 2021, 33(8): 1969-1979.

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基于改进粒子群算法的居民需求响应调度优化与仿真

Residential Demand Response Scheduling Optimization and Simulation based on an Improved PSO Algorithm

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