计算机科学

计算机科学 ›› 2024, Vol. 51 ›› Issue (6A): 230600096-6.doi: 10.11896/jsjkx.230600096

• 交叉&应用 • 上一篇    下一篇

基于改进遗传算法的家庭用电调度优化方法

黄飞1, 李永福1, 高杨2, 夏磊1, 廖庆龙1, 戴健1, 向洪1   

  1. 1 国网重庆市电力公司电力科学研究院 重庆 401123
    2 重庆邮电大学通信与信息工程学院 重庆 400065
  • 发布日期:2024-06-06
  • 通讯作者: 高杨(1172506421@qq.com)
  • 作者简介:(huangfei_87@163.com)
  • 基金资助:
    国家电网公司总部科技项目(5700-202141454A-0-0-00)

Scheduling Optimization Method for Household Electricity Consumption Based on Improved Genetic Algorithm

HUANG Fei1, LI Yongfu1, GAO Yang2, XIA Lei1, LIAO Qinglong1, DAI Jian1, XIANG Hong1   

  1. 1 Chongqing Electric Power Research Institute,Chongqing 401123,China
    2 School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
  • Published:2024-06-06
  • About author:HUANG Fei,born in 1987,master,se-nior engineer.His main research inte-rests include smart distribution grid technology and so on.
    GAO Yang,born in 1998,postgraduate.His main research interests include application of intelligent optimization algorithms in power system optimization and so on.
  • Supported by:
    National Grid Corporation Headquarters Technology Project(5700-202141454A-0-0-00).

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摘要： 用电高峰期的用电需求给电力系统带来了巨大压力,因此优化家庭用电调度变得尤为重要。针对用电高峰期用户端存在的用电经济性及舒适度不够的问题,提出了一种基于改进遗传算法的家庭用电调度优化方法。首先以分时电价为基础,建立综合考虑用电经济性与用户满意度的家用电器调度模型,然后对不同类型的电器采取不同的编码方式来替代传统遗传算法的单一编码,并用带惩罚函数的适应度函数来约束各个电器用电任务所需时长等,以对传统遗传算法进行改进和用电行为优化。结果表明,所提算法可有效地依据分时电价实现用电负荷调度优化,在满足用户用电舒适度情况下为用户提供经济性的用电方案,且复杂度较低,能有效解决用电高峰期的用电经济性和舒适度问题。

关键词: 微电网调度, 需求响应, 家庭用电, 多约束条件, 混合编码, 遗传算法

Abstract: In response to the problems of insufficient electricity economy and comfort at the customer side during the peak consumption period,an improved genetic algorithm based on optimization method for household electricity scheduling is proposed.The traditional genetic algorithm is improved and the electricity consumption behavior is optimized by adopting different coding methods for different types of appliances instead of the single coding of the traditional genetic algorithm,and using the fitness function with penalty function to constrain the time required for each appliance’s electricity consumption task.The results show that the proposed algorithm can effectively realize the optimization of electricity load scheduling based on time-of-use tariff,and provide customers with economical electricity concumption solutions with low complexity, it can effectively solve the problem of economic and comfort level of power consumption during the peak period of power consumption.

Key words: Microgrid scheduling, Demand response, Household electricity, Multiple constraints, Hybrid coding, Genetic algorithm

中图分类号: 

  • TP393
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