Multi-objective performance optimization & thermodynamic analysis of solar powered supercritical CO2 power cycles using machine learning methods & genetic algorithm

The present study is focused on multi-objective performance optimization & thermodynamic analysis from the perspectives of energy and exergy for Recompression, Partial Cooling & Main Compression Intercooling supercritical CO2 (sCO2) Brayton cycles for concentrated solar power (CSP) applicati...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Asif Iqbal Turja, Md Mahmudul Hasan, M. Monjurul Ehsan, Yasin Khan
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Elsevier 2024-01-01
Schriftenreihe:	Energy and AI
Schlagworte:	Supercritical CO2 Concentrated solar power Thermodynamic analysis Machine learning Artificial neural network Multi-objective optimization
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S266654682300099X
Tags:	Tag hinzufügen Keine Tags, Fügen Sie das erste Tag hinzu!