Waste heat recovery cycles integration into a net-Zero emission solar-thermal multi-generation system; Techno-economic analysis and ANN-MOPSO optimization

作者：Pradeep Kumar Singh, Ali Basem, Rebwar Nasir Dara, Mohamed Shaban, Sarminah Samad, Raymond Ghandour, Ahmad Almadhor, Samah G. Babiker, Iskandar Shernazarov, Ibrahim Alsayer · 发表于：Case Studies in Thermal Engineering · 年份：2024 · DOI：10.1016/j.csite.2024.105690 · 被引用次数：17 · 研究领域：Thermodynamic and Exergetic Analyses of Power and Cooling Systems、Solar Thermal and Photovoltaic Systems、Hybrid Renewable Energy Systems

This paper presents a novel solar-powered multi-generation system (MGS) integrated with a fuel cell, designed to enhance both sustainability and operational reliability. A significant limitation of solar energy is its intermittency, as sunlight is only available during specific hours of the day. To address this constraint, hydrogen energy is incorporated into the system to facilitate continuous operation through the fuel cell. The proposed MGS efficiently utilizes waste heat recovery cycles to simultaneously produce electricity, fresh water, cooling, and heating. The system consists of parabolic trough solar collectors, a steam Rankine cycle, an organic Rankine cycle, an absorption chiller, a reverse osmosis desalination unit, and a fuel cell coupled with an organic Rankine cycle-thermoelectric generator. Upon validating the primary components, the system is thoroughly evaluated in terms of energy, exergy, and economic performance, and a parametric study is conducted to assess the influence of key operational parameters. The analysis identifies the solar cycle as having the highest irreversibility, accounting for 55.2 %, and the highest cost rate, contributing 44.1 % among the subsystems. To optimize the system's performance, an artificial neural network is integrated with a multi-objective particle swarm optimization algorithm to reduce computational time from approximately 16 h to 4 min. Finally, under optimal conditions, the system achieves an exergy efficiency of 31.69 %,...