Optimal Scheduling of Power System with Flexible Carbon Capture Power Plants Based on Fuzzy Chance Constrained Planning

Carbon capture power plants have the potential to mitigate the impact of clean energy fluctuations and reduce the system's carbon emissions. Among different carbon capture power plant designs, those incorporating a bypass flue and solvent storage offer greater scheduling flexibility compared to solvent-stored and split-flow plants. Hence, given the uncertainty associated with wind and solar power outputs, we aim to explore scheduling strategies for an integrated energy system incorporating a flexible carbon capture plant, using fuzzy chance constraints planning. Firstly, we focus on refining the modeling of the carbon capture process within a solvent-stored carbon capture power plant's operational mode. Secondly, we employ fuzzy theory to analyze and cluster scenarios, estimating prediction errors for wind and solar power generation. Then, we introduce credibility measures and fuzzy chance constraints to develop an optimal dispatch model for the power system integrating flexible carbon capture power plants. Finally, Finally, the effectiveness of the method is validated through case analysis.