基于数据驱动结合充电波动的建筑综合能源系统长期优化研究OA

Modern commercial buildings use integrated energy systems to complete the overall energy supply of electricity and cooling and heating.However,the actual application of integrated energy systems is affected by the charging fluctuations of electric vehicles.In order to solve the negative problems such as the reduction of the economy of the comprehensive energy system and the increase of carbon emissions caused by charging fluctuations,this paper establishes a mathematical model of the charging load of electric vehicles.Supported by actual weather data,the Latin hypercube sampling method is used to obtain a uniform commercial building.A data set of charging load fluctuation scenarios within the building.Based on this data set and combined with the various equipment components involved in the comprehensive energy system of the commercial building,a mathematical model of the comprehensive energy system of the commercial building is constructed.The system energy balance of the model is constrained,the system cost calculation is completed,and the model is finally solved by two-stage stochastic programming for long-term optimization.Taking the actual scenario of a commercial building in Beijing City over the past 10 years as a simulation case,the simulation results verify that the proposed long-term optimization model is reasonable and effective.Compared with short-term optimization,the total cost of the long-term optimization model is reduced by 31.16%,and the total carbon emissions are reduced by 26.97%.