Performance analysis and optimization of photovoltaic-thermal system with direct contact membrane distillation using metaheuristic algorithms

Photovoltaic-Thermal (PV/T) systems integrated with Direct Contact Membrane Distillation (DCMD) offer a promising solution for sustainable water desalination by simultaneously utilizing solar energy for electricity generation and thermal applications. This study presents a dynamic optimization framework to enhance the seasonal performance of PV/T-DCMD systems under variable climatic conditions. The objective is to maximize electrical efficiency, permeate flux, and outlet temperature by considering the effects of flow rates (1–10 L/min), solar irradiation (10–1000 W/m2), and ambient temperatures (291–324 K). Metaheuristic algorithms, including Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), are employed to determine the optimal operating parameters. The results reveal that PSO achieved an optimal outlet temperature of 329.45 K and permeate flux of 19.89 kg/m2·h at a flow rate of 1.0 L/min, solar irradiation of 1000 W/m2, and ambient temperature of 324 K. In comparison, GA yielded a slightly lower outlet temperature of 329.01 K and permeate flux of 19.80 kg/m2·h under the same conditions. Electrical efficiency stabilized at approximately 0.13 for both optimization techniques. These findings highlight the advantages of reduced flow rates and elevated solar irradiation in optimizing the system’s thermal and electrical performance. This comprehensive analysis not only demonstrates the operational characteristics of PV/T-DCMD systems but also establishes a foundation for future advancements in hybrid optimization techniques and material innovations to further enhance system performance under dynamic weather conditions.

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Published in: Separation and Purification Technology
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.seppur.2025.132488