Low-carbon economic dispatch based on improved ISODATA scenario reduction for wind power in IES

As wind power integration increases, its unpredictability challenges the integrated energy system (IES). A low-carbon, 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.