Open AccessResearch on Optimal Scheduling of Home Energy Management System Based on NSGA III Multi-Objective Optimization Algorithm
Author(s) -
Xingxiang Zhang,
Fēi Li,
Songsong Chen,
Kai Zhang,
Jianyong Feng
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/585/1/012008
Subject(s) - energy management system , electricity , computer science , smart grid , photovoltaic system , scheduling (production processes) , mathematical optimization , energy management , multi objective optimization , automotive engineering , engineering , energy (signal processing) , electrical engineering , statistics , mathematics , machine learning
With the rapid development of smart grid, more and more scholars pay attention to the Home Energy Management System (HEMS). In order to reduce the user’s electricity cost and improve the user’s electricity comfort, this paper proposes a multi-objective optimization strategy of HEMS based on NSGA III multi-objective optimization algorithm. First of all, this paper designs the basic structure of the HEMS, and builds the temperature-controlled load model, the uninterruptible load model, the photovoltaic power generation model and the battery and electric vehicle model. Then, the improved NSGA III multi-objective optimization algorithm is used to solve the model, and the working state of the schedulable load and the output power of the photovoltaic system are obtained in each period. Finally, the simulation results show that the scheme can effectively reduce the user’s electricity cost and improve the user’s electricity comfort. At the same time, the proposed optimal scheduling strategy can also achieve the optimization goal of the HEMS, which proves that the strategy can provide the safe and reliable optimal electricity consumption mode for the home.