计及光伏不确定性和低碳需求响应的工业园区光-储分布鲁棒规划模型

Photovoltaic-energy Storage Distributed Robust Planning Model for Industrial Parks Considering Photovoltaic Uncertainty and Low-carbon Demand Response

在双碳背景下,工业园区能通过配置光-储发电系统,减少外部购电量,从而降低碳排放水平,但光伏的不确定性给工业园区最优规划带来了一定挑战。基于此,建立了计及光伏不确定性和低碳需求响应的工业园区光-储鲁棒规划模型。该模型以园区年综合成本最小为优化目标,基于碳排放流理论,将动态碳排放因子作为需求响应的实时电价的定价依据,其次,利用光伏出力的历史数据,通过场景聚类,建立典型出力场景和其概率分布,构建基于数据驱动的两阶段分布鲁棒光-储规划模型。最后,利用Cplex商业求解器对某工业园区进行算例仿真,验证了所提模型的有效性。

Under the background of carbon peak and carbon neutralization,industrial parks can reduce external power purchasing by deploying the photovoltaic generation system with energy storage device,thus lowering the carbon emission level.However,photovoltaic uncertainty brings certain challenges to the optimal planning of the industrial parks.Based on this,the paper proposes a photovoltaicenergy storage robust planning model for the industrial parks considering the photovoltaic uncertainty and low-carbon demand response.Firstly,based on the theory of carbon emission flow,the model uses a dynamic carbon emission factor as the pricing basis of real-time electricity price in the demand response with the goal of minimizing the annual comprehensive cost of the parks.Then the historical data of photovoltaic output is used to establish typical output scenarios and their probability distribution through scene clustering,and a data-driven two-stage distributed robust planning model is constructed.Finally,the Cplex commercial solver is used to simulate an industrial park,and the effectiveness of the proposed model is verified.