Research On Design And Optimal Scheduling Algorithm Of Home Energy Management System Based On Distributed Generation And Energy Storage

With the increasing shortage of traditional fossil energy and environmental protection requirements,in recent years,China began to vigorously promote the construction of distributed renewable energy,issuing a series of laws and regulations to adjust the factors which restricting the development of distributed generation market.With the popularity of distributed generation in ordinary familys as well as the rapid development of smart home,the family's electricity consumption structure also ushered in the opportunity for change.At present,user is lack of information exchange with the grid as well as lack of intelligent scheduling on home electrical equipment,causing inefficient use of renewable energy in the family,and has to buy electricity from the grid during peak-electricity-consumption hours.This unreasonable use of electricity structure not only increases the cost of electricity users,but also to make the large power grid overwhelmed,causing a threat to the stability of the power grid.In order to guide users to better use of electricity,home energy management system(HEMS)came into being.In this paper,the home energy management system is studied from two aspects:frame design and energy optimization scheduling strategy.Firstly,a framework of home energy management system based on advanced measurement system(AMI)is proposed.The framework uses the local information management terminal as the core of data storage and scheduling in the home.Then,the power generation and power equipment in the home are modeled.In this paper,an improved discrete binary particle swarm optimization(DBPSO)algorithm is proposed to optimize the flexible load in the home,and an energy storage scheduling strategy based on real-time electricity price(RTP)is proposed.Finally,the simulation comparison cases are given,and the effectiveness and anti-jamming of the algorithm are analyzed.