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

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 %, freshwater production of 19.53 kg/s, cooling production of 441.6 kW, and a total cost rate of $87.2/h.

Authors

Institutions

Publication Details

Journal
Case Studies in Thermal Engineering
Published
2024-12-26
DOI
https://doi.org/10.1016/j.csite.2024.105690
Citations
12
Primary Topic
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
Type
article
Field-Weighted Citation Impact
2.55
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Ali Basem, Raymond Ghandour, Sarminah Samad, Ahmad Almadhor et al.
12 citations
Case Studies in Thermal Engineering
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
2.55
article

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

Ali Basem, Raymond Ghandour, Sarminah Samad, Ahmad Almadhor, Ibrahim Alsayer, Mohamed Shaban, Samah G. Babiker, Rebwar Nasir Dara, Pradeep Kumar Singh, Iskandar Shernazarov
article en
12 citations

Abstract

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 %, freshwater production of 19.53 kg/s, cooling production of 441.6 kW, and a total cost rate of $87.2/h.

Case Studies in Thermal EngineeringVol. 66
Princess Nourah bint Abdulrahman University (SA), Northern Border University (SA), Jouf University (SA), American University of the Middle East (KW), University of Kerbala (IQ), Islamic University of Madinah (SA), National Pedagogical University of Uzbekistan named after Nizami (UZ), University of Business and Technology (SA), University of Warith Al-Anbiyaa, Salahaddin University-Erbil (IQ), GLA University (IN), Red Sea University (SD)
Affordable and clean energy
Openalex Percentile: Top 10%
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
2.55
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.