基于改进遗传算法的家庭用电调度优化方法  

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

作　　者：黄飞 李永福 高杨 夏磊 廖庆龙 戴健 向洪 HUANG Fei;LI Yongfu;GAO Yang;XIA Lei;LIAO Qinglong;DAI Jian;XIANG Hong(Chongqing Electric Power Research Institute,Chongqing 401123,China;School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[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

出　　处：《计算机科学》2024年第S01期1157-1162,共6页Computer Science

基　　金：国家电网公司总部科技项目(5700-202141454A-0-0-00)。

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。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 sowtionswith low complexity,it can effectively solve the problem of economic and comfort level of power consumption during the peak period of power consumption.

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 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]