Study On The Energy Optimization Scheduling Model And Algorithm For Home Energy Management System

With the increasingly serious global warming and fossil fuel gas emissions,the problem,which is reducding carbon dioxide emissions and saving energy consumption is more and more important.Considering the earth’s fossil energy is limited,the problem that how to manage energy effectively is one of the important topics.With the increasing of domestic demand for electricity,home energy management system HEMS related energy-saving emission reduction technology is arousing more and more people’s attention.The focus of this paper is on the optimization of energy in the HEMS scheduling problem.The goal which is saving electricity,reducing carbon dioxide emissions through the optimization of scheduling to ensure user satisfaction is achieved.This paper presents an 0-1 integer linear programming method for energy optimization scheduling which can be applied to the Home Energy Management System(HEMS)that equipped with distributed energy storage system.The proposed approach can minimize the expenses of electricity and maximize the comfort level of users,or minimize CO2 emissions,respectively,according to users’ needs.And it can achieve optimal results in a very short period of time.At the end of this paper,simulation experiments show that the proposed method is effective and it can be used to cope with the peak load demand of the power company.Finally,simulation results demonstrate the proposed method can achieve better results than exist method in saving the cost and reducing the effect of carbon dioxide emissions.Basing on 0-1 linear integer programming approach for the optimal home appliances scheduling model considering the photovoltaic power generation forecasing error,this paper puts forward a appliance optimization scheduling algorithm which is under the PV prediction error.The algorithm uses 0-1 linear integer programming method for electricity costs,scheduling based scheduling model combined with rolling optimization method to finish tasks of household electrical appliances and storage equipment.Finally the simulation experiments verify the effectiveness of the proposed method.For example,in the experiments of most economical in electricity costs,which is verifing the algorithm which can well solve the photovoltaic power generation prediction error problem,at the same time to achieve cost savings.The scheduling model and algorithm in this paper give full consideration to the type of home appliances in the family.Furthermore,the popularization of solar power generation systems,distributed energy storage equipment and allowed online sale of the remaining power will be unified consideration.It is of great practical significance to consider time-of-use electricity price and power company’s demand response limit and other factors.