【摘要】 随着风电并网规模的不断增长，其出力不确定性给综合能源系统（integrated energy system, IES）的稳定经济运行带来了巨大挑战。对此，文中提出基于改进风电场景削减算法的IES低碳经济调度方法。首先，采用改进的迭代自组织数据分析算法（iterative self-organizing data analysis technique algorithm, ISODATA）对大量历史风电场景进行聚类削减，克服传统聚类算法在聚类中心确定和数据内在特征考虑上的不足。然后，以改进阶梯碳价模型计算碳交易成本，针对含电转气-碳捕集（power to gas and carbon capture system, P2G-CCS）耦合设备的IES，建立以提升其经济性、低碳性为目标的IES优化调度模型。最后，仿真结果表明，该模型在保证系统低碳排放的同时可有效降低综合运行成本。更多还原

【Abstract】 As wind power integration increases, its unpredictability challenges the integrated energy system(IES). A lowcarbon, economic dispatch method for IES using an enhanced wind power scenario reduction algorithm is introduced in this paper. It employs an improved iterative self-organizing data analysis technique algorithm(ISODATA) for clustering historical wind power scenarios, addressing the limitations of traditional clustering algorithms in determining cluster centers and analyzing inherent data features. Then, an integrated energy model is established and it optimized using an improved stepwise carbon trading and power to gas and carbon capture system(P2G-CCS) coupling model. Finally, an IES model is developed with the goals of improving economic efficiency, reducing carbon emissions. Simulation results demonstrate that this model reduces comprehensive operational costs while ensuring low carbon emissions in the system.更多还原