Artificial Intelligence-Assisted Optimization and Case Study of an Innovative Thermal Design Combined with a Heliostat Field and Compressed Air Energy Storage

نویسندگان

1 Department of Mechanical Engineering, CT.C, Islamic Azad University, Tehran, Iran

2 Department of Mechanical Engineering, CT.C, Islamic Azad University, Tehran, Iran

3 Department of Mechanical Engineering, CT.C, Islamic Azad University, Tehran, Iran

4 Department of Mechanical Engineering, CT.C, Islamic Azad University, Tehran, Iran

5 Department of Mechanical Engineering, CT.C, Islamic Azad University, Tehran, Iran

doi
10.22097/eeer.2026.541824.1377
چکیده

Solar thermal systems depend on efficient heat integration strategies to minimize energy loss. The present study proposes a novel multigeneration configuration. It integrates a heliostat field–driven power source with compressed air energy storage (CAES) for long-term and flexible energy storage. The system also includes a supercritical CO₂ cycle, an absorption chiller, a heating unit, and a multi-effect desalination (MED). A key innovation of this work is the introduction of a three-state operation method. This method was developed using engineering equation solver (EES) and enables adaptive operation across charging, discharging, and storage states, enhancing overall system efficiency. The study also provides a comprehensive sensitivity analysis and uses artificial intelligence–assisted multi-objective optimization based on the non-dominated sorting genetic algorithm II (NSGA-II) combined with the linear programming technique for multidimensional analysis of preference (LINMAP). The exergetic round-trip efficiency (ERTE), unit cost of products, and CO₂ emissions served as objective functions, yielding optimized baseline values of 28.47%, 0.1158 $/kWh, and 31.52 kg/MWh, respectively. Simulation results, using 2024 meteorological data, demonstrate system feasibility under two Iranian climates: Tehran and Yazd. For Tehran, the optimal ERTE, cost, and emission values are 26.97%, 0.1280 $/kWh, and 30.21 kg/MWh. For Yazd, these values are 27.80%, 0.1174 $/kWh, and 30.09 kg/MWh. Compared with conventional CAES-integrated solar systems, the proposed design improves ERTE by about 8–12%. This confirms superior performance and adaptability across diverse operating conditions.