Collaborative optimization method and operation performances for a novel integrated energy system containing adiabatic compressed air energy storage and organic Rankine cycle

Integrated energy system (IES) coupled with advanced adiabatic compressed air energy storage (AA-CAES) and organic Rankine cycle (ORC) has the superiority to peak-load regulation and improve system performance. Therefore, a novel IES-ORC-CAES system, which includes AA-CAES, ORC and ICE, is proposed in this paper. In this system, the user return water is used to recover the compression heat generated by AA-CAES. The ICE exhaust smoke flows through three parts successively, the heat exchangers of AA-CAES energy release side, the ORC and absorption heat pump arranged in parallel and the tail heat exchanger, realizing the cascade utilization of energy and meeting the diversified energy demand of users. Considering the time of use electricity price and aiming at economy, environmental protection and energy efficiency, a collaborative optimization method that can dynamically adjust the energy output of the system is proposed. The results indicate that compared with the IES-ORC system (without AA-CAES), the annual operation cost, CO2 emission and primary energy consumption of the IES ORC-CAES system can be reduced by 14.84%, 13.06% and 11.69% under the economic, environmental and energy efficiency objectives. Furthermore, by coordinating the regulation of ICE, AA-CAES and ORC, the flexibility of the system energy supply is realized, and the matching of the electric-heat ratio on the source and load side is improved. Finally, the thermodynamic analysis of the IES-ORC-CAES system is carried out through parameter analysis. The research results can provide the reference for the operation optimization of the complex IES.

Automated summary

The study proposes a novel integrated energy system incorporating advanced energy storage technology and thermal energy conversion cycle, meeting diverse user demands through cascaded energy utilization. By considering economic, environmental, and energy efficiency objectives, a collaborative optimization method is introduced, significantly reducing operating costs, CO2 emissions, and primary energy consumption.