Real-time operational optimization for flexible multi-energy complementary integrated energy systems

Multi-energy complementary integrated energy system (MCIES) has gained widespread attentions due to its utilization of diverse energy sources, enhancing energy efficiency, and reducing carbon emissions. The scheduling optimization of MCIESs needs to address multiple factors, including solar/wind energy potential, fluctuating load demand, and prediction errors, to maintain its highly flexible and decarbonized operation. This study presents a scheduling optimization model based on a mixed integer nonlinear programming model (MINLP) with a novel flexibility index as the objective function. A case study of a MCIES in a swimming pool in Changsha is provided. The results demonstrate that real-time operational scheduling considering flexibility enhances the system flexibility of the MCIESs from 0.608 to 0.623 comparing with the day-ahead scheduling, maintaining superior performance across multiple dimensions. The coupling between the power grid and the natural gas network is also improved, significantly reducing the carbon dioxide emissions of the MCIES by 127.67kgCO2 per day. Furthermore, the study reveals that the flexibility-aware real-time operational scheduling for MCIES outperforms day-ahead scheduling in responding to weather and equipment failures, sustaining high flexibility operation, economic viability, and notably improved environmental performance. CO2 emissions are reduced by 21.088% and 14.638%, respectively. The proposed operational optimization approach in this study can enhance the flexibility and coordinated operation of MCIESs, leading to reduced carbon emissions.