Sustainable Energy and Artificial Intelligence

Integrated Optimization of Solar-Based Multi-Generation Systems for Cooling, Heating, Power, and Freshwater with Different Prime Movers

Document Type : Original Article

Authors

Amin Saleh 1
Hassan Hajabdollahi 2
Vahid Ghamari 1

1 PhD candidate, Department of Mechanical Engineering, Faculty of Engineering, Vali-e-Asr University, Rafsanjan, Iran

2 Professor, Department of Mechanical Engineering, Faculty of Engineering, Vali-e-Asr University, Rafsanjan, Iran

https://doi.org/10.61882/seai.2508-1032
Abstract
The proposed solar-assisted hybrid system integrates decentralized, energy-efficient technologies for multi-vector energy production, delivering key advantages such as improved efficiency, lower emissions, economic feasibility, sustainability, and enhanced reliability. This work investigates the optimal design of a solar–fossil-fuel-based configuration capable of generating cooling, heating, power, and freshwater (CCHPW). The system employs different prime movers for combined heat and power production, namely a gas engine (GE), gas turbine (GT), and solid oxide fuel cell (SOFC). The overall plant consists of a prime mover, two types of chillers, an auxiliary boiler, a reverse osmosis desalination unit, parabolic trough solar collectors, a proton exchange membrane (PEM) electrolyzer, and thermal and cooling energy storage systems. A genetic algorithm is utilized to minimize the total annual cost (TAC). Optimization results demonstrate that the exergy efficiency of the GE-based CCHPW system is about 40.31% and 92.50% higher than that of SOFC- and GT-based systems, respectively. Moreover, the GE configuration achieves reductions in TAC of 27.08% and 23.80% compared to SOFC and GT systems, respectively.

Keywords

Thermo-economic optimization
Solar energy
Energy storage tank
Prime mover
Genetic Algorithm
Subjects
Sustainable Energy and Artificial Intelligence
Volume 2, Issue 1
Winter 2026
Pages 1-14

  • Receive Date 01 August 2025
  • Revise Date 01 September 2025
  • Accept Date 01 October 2025
  • First Publish Date 01 October 2025

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