A novel solar dual-stage evaporation multigeneration system is proposed, with analysis on the impact of the parabolic trough collector area (APTC) and the volume of the heat storage tank (VHST) on performance under dynamic conditions. The particle swarm optimization- genetic algorithm and the minimum path method optimized the system’s overall performance. Results show that reducing APTC and increasing VHST can enhance energy performance within a certain range, but beyond specific thresholds, changes in APTC and VHST no longer affect it. As APTC and VHST increase, economic performance initially improves but then declines. The particle swarm optimization- genetic algorithm increased optimization efficiency and avoided local optima. When using the minimum path method, the dimensionless cumulative error was 0.63, balancing thermal and economic performance. Using toluene as the working fluid, the optimized system achieved thermal and exergy efficiencies of 56.06 % and 9.15 %, respectively, with a net present value of 58.12 M$, a payback period of 5.23 years, and an equivalent CO2 reduction of 24.8 kt, outperforming the solar organic Rankine cycle system in energy efficiency, economic performance, and carbon reduction potential. The solar dual-stage evaporation multigeneration system achieved the best performance with toluene as the working fluid, while heptane provided longer running time and greater carbon reduction potential. At low rated power generation, performance differences between toluene and heptane were minimal, while as the rated power generation increased, toluene showed significant advantages in thermal and economic performance.
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