Application Research Of Demand Response In Energy Management Of Large-Scale Intelligent Commercial Buildings

The "13th Five-Year Plan for Electric Power Development" proposes to vigorously develop new energy sources,and to promote the acceptance and consumption of renewable energy,which makes upgrading the distribution network and promoting the construction of smart grids become the main points of current energy construction.The construction of smart grid needs to fully enhance the two-way interaction between power supply and users.Commercial building load is an important demand response resource.Energy management strategies and demand response solutions for large-scale intelligent commercial buildings with distributed power,energy storage and flexible loads will help to build cost-effective,technologically advanced and environmentally friendly commercial buildings,promote the construction of active distribution networks,improve the safety and reliability of the power grid and the utilization of social energy,and realize a resource-saving and environment-friendly society.This paper focus on large intelligent commercial buildings and demand response.The following are the main work and achievements of this paper:1)According to the load classification of large-scale intelligent commercial buildings based on user behaviors,this paper established the time distribution model of each type of load and proposed the load forecasting method for large-scale intelligent commercial buildings.An experiment is made to measure the time distribution characteristics of various loads in commercial building offices.The results verify the established loads model.2)By establishing an aggregation model for air conditioning load of large-scale intelligent commercial buildings,this paper proposed a demand response scheme for the aggregate of air-conditionings loads.The proposed scheme has the advantage of low dependence on communication and control of each air-conditioning.Meanwhile,the proposed scheme can realize the load control while retain the difference temperature seting in each air-conditioning.The detailed model of the air-conditioning aggregator established by GridLAB-D software shows that the proposed aggregate model has good applicability,and the proposed demand response scheme has good load control ability.3)To solve the long-term scale optimization of energy storage capacity configuration,a two-layer optimization algorithm of genetic algorithm-linear programming is proposed in this paper.Then,the impact of the demand response on the energy storage capacity allocation is analyzed under considering the demand response and the coordinated control of the energy storage system.The results show that the coordination of demand response and energy storage can reduce the capacity requirements of the energy storage system and improve the utilization efficiency of the energy storage device.The V2 B mode of electric vehicles in commercial building blocks with distributed generation is studied.V2 B can improve the load characteristics of commercial buildings and improve the grid interconnection of wind power.4)The potential demand response ability of large-scale intelligent commercial buildings is evaluated in this paper.Then an optimization model of the commercial building energy management system is proposed with taking the source-storage-load resources in the system into consideration.According to the simulation results,the proposed energy management strategy and real-time electricity price scheme can effectively reduce the power operation cost of commercial buildings and the power consumption cost of users.