考虑风光不确定性的综合能源系统容量-成本两阶段规划优化研究OA北大核心CSTPCD

The integrated energy system(IES)planning and optimization faces multiple challenges such as high volatility of new energy sources and large uncertainty of output.In view of this,this paper proposes a two-stage capacity-cost planning and optimization method for integrated energy systems considering scenery uncertainty.Firstly,Latin hypercube sampling is applied to generate the base wind and solar scenarios set,and the scenarios are reduced based on the improved k-means algorithm.Secondly,a multi-objective optimization model is constructed with the lowest operating cost,optimal carbon emission reduction,and optimal pollutant emission reduction;finally,the system capacity-cost two-stage planning and optimization solution strategy is proposed,and a business park in the south is selected for the planning simulation.The simulation example shows that the two-stage planning model of integrated energy system constructed in this paper can ensure the economy of system and environmental protection at the same time,and meet the multiple energy demands of users.