Optimization and Scheduling of Integrated Energy Systems With Carbon Capture and Storage-Power to Gas Based on Information Gap Decision Theory

Abstract

ObjectivesThe main issue in the current rational optimization of integrated energy systems is to adopt technological means to improve energy conversion efficiency, reduce system energy waste and regional environmental pollution, in order to scientifically coordinate the optimization goals of economic, stability, and low-carbon operation of the integrated energy system. To this end, a low-carbon optimization strategy for a carbon capture and storage (CCS)two-stage power to gas (P2G)integrated energy system based on scenario generation and information gap decision theory (IGDT) was proposed.MethodsAt the technical level, by finely modeling the two-stage conversion from power to gas, the efficiency of hydrogen energy utilization was improved, and a combined heating and power (CHP)-CCS-P2G coupling model was established. At the market mechanism level, a tiered carbon trading model was introduced to reduce CO2 emissions in the system. Finally, based on the IGDT, an optimization scheduling model was constructed for different risk preferences.ResultsTaking a typical integrated energy system as an example, the simulation results show that the proposed model can improve the wind and solar energy consumption rate, achieve low-carbon, economic, and stable operation of the system.ConclusionsThis optimization strategy can effectively help decision-makers develop scheduling plans under risk avoidance and risk pursuit strategies based on their risk preferences, achieving a balance between system uncertainty and economy.

Keywords

• integrated energy system
• scenario generation
• information gap decision theory(igdt)
• carbon capture and storage(ccs)
• power to gas(p2g)
• stepped carbon trading