A Two-stage Intra-day Optimal Operation Optimization Method for Integrated Energy Systems

Abstract In integrated energy systems, significant uncertainties from renewable energy and users’ loads pose challenges to the efficient, stable and low-carbon operation. Therefore, it is urgent to develop precise and real-time operation control and energy management method. This study proposes a two-stage intraday optimal operation optimization method for integrated energy systems by minimizing carbon emission liabilities. Operation status and parameters of primary equipment in the systems are optimized. The first stage is to optimize the operation of cooling systems by minimizing the cooling energy consumption. The second is to optimize the electrical energy system by particle swarm optimization so that the charging and discharging strategy of the electrical storage system can be determined. The method is verified in an integrated energy system for an industrial park. Results demonstrate that the proposed strategy can effectively respond to changes in demands and renewable energy. Meanwhile, the total carbon emission liabilities are reduced by 3.01% and 9.34% when considering the dynamic carbon emission liability factors. This study provides technical support for improving the operation performance of integrated energy systems.