Article (Scientific journals)
Performance improvement of hybrid photovoltaic/thermal systems: A metaheuristic artificial intelligence approach to select the best model using 10E analysis
Kenfack, Armel Zambou; Simo, Elie; Chara-Dackou, Venant Sorel et al.
2024In Solar Energy Advances, 4, p. 100061
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Keywords :
10 E analysis; Comparative study; GA/MOPSO; PV/T optimal model; Simplified modeling; Energy Engineering and Power Technology; Environmental Science (miscellaneous); Renewable Energy, Sustainability and the Environment
Abstract :
[en] Photovoltaic/thermal (PV/T) hybrid systems have until now encountered a real problem of sustainability-energy-cost concordance. Faced with this situation, new types of designs are in full expansion aimed at filling the limits of some. This therefore involves a very appropriate decision-making process. The energy, exergy, economic, environmental, energo-environmental, exergo-environmental, enviro-economic, energy-enviro-economic, exergo-enviro-economic and ergonomic analysis is carried out on seven PV/T configurations and therefore the simplified models are presented for a better interpretation of the mechanisms from different perspectives and the integration of a selection algorithm. Thus, an optimal selection methodology using the hybridization of genetic algorithms and multi-objective optimization by particle swarms based on ten performance indicators is proposed. The results obtained with good convergence and precision allow us to observe that the Air PV/T model is better. However, the study shows good viability of PV/T models with a cost of energy and a return on investment time all lower than 0.1$/kWh and 3 years, respectively. Models with phase change materials (PCM) minimize thermal losses better than those with air, nanofluids or thermoelectric generator (TEG). The bifacial model stands out with a good energy-environmental balance compared to the water model which has a better durability index greater than 2.0 and a good ergonomic factor.
Precision for document type :
Critical notes/Edition
Disciplines :
Civil engineering
Author, co-author :
Kenfack, Armel Zambou ;  Energy and Environment Laboratory, Department of Physics, Faculty of Science, University of Yaoundé I, Cameroon
Simo, Elie;  Energy and Environment Laboratory, Department of Physics, Faculty of Science, University of Yaoundé I, Cameroon
Chara-Dackou, Venant Sorel;  Energy and Environment Laboratory, Department of Physics, Faculty of Science, University of Yaoundé I, Cameroon ; Carnot Energy Laboratory(CEL), Department of Physics, Faculty of Science, University of Bangui, Bangui, Central African Republic
Pemi, Boris Abeli Pekarou;  Energy and Environment Laboratory, Department of Physics, Faculty of Science, University of Yaoundé I, Cameroon
Kameni Nematchoua, Modeste ;  Université de Liège - ULiège > Département ArGEnCo > Urbanisme et aménagement du territoire ; Université de Liège - ULiège > Urban and Environmental Engineering
Language :
English
Title :
Performance improvement of hybrid photovoltaic/thermal systems: A metaheuristic artificial intelligence approach to select the best model using 10E analysis
Publication date :
2024
Journal title :
Solar Energy Advances
eISSN :
2667-1131
Publisher :
Elsevier Ltd
Volume :
4
Pages :
100061
Peer reviewed :
Peer Reviewed verified by ORBi
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