| Household electricity consumption accounts for about 17% of the whole world’s electricity consumption.The research of home energy management system plays an important role in solving energy efficiency problems and directing residents to use electricity rationally.Control strategy and algorithm of home energy management based on comfort,by establishing a multi-objective optimization model,using intelligent algorithm to properly control the load power consumption time,can save electricity costs to the greatest extent,and maintain high user comfort,while maintaining high user comfort.At the same time,the purpose of peak load shifting and power resource utilization improving can be achieved.The main work of this paper is:A comfort-based home energy management system model is established.Based on the analysis of the factors affecting the user comfort,a user comfort evaluation model is built,which includes thermal comfort and load transfer comfort.The load is classified into three types(namely,uninterruptible load,interruptible power constant load and interruptible power variable load)for classification modeling.The control strategy and algorithm research for home energy management based on comfort are conducted.A multi-objective optimization function model with a goal of reducing electricity charges and improving user comfort is proposed.The characteristics of firefly algorithm and particle swarm optimization algorithm are analyzed,and a hybrid firefly and particle swarm optimization algorithm is proposed to find the optimal solution for the system model.A simulation study is conducted.The simulation results show that the control strategy and algorithm for home energy management based on comfort can save 29% of the electricity charges;the thermal comfort and load transfer comfort can be increased by 31% and by 57% respectively;and the daily load standard deviation can be reduced by 7%,so that the peak-valley fluctuation can be significantly reduced. |
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