A comprehensive techno-economic analysis and multi-criteria optimization of a compressed air energy storage (CAES) hybridized with solar and desalination units

•A novel integration of compressed air energy storage, solar, and desalination units.•Comprehensive thermodynamic, exergoeconomic, and economic analyses of the system.•Multi-objective optimization based on artificial neural network and genetic algorithm.•A precise case study based on real solar radi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Energy conversion and management 2021-05, Vol.236, p.114053, Article 114053
Hauptverfasser: Alirahmi, Seyed Mojtaba, Bashiri Mousavi, Shadi, Razmi, Amir Reza, Ahmadi, Pouria
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•A novel integration of compressed air energy storage, solar, and desalination units.•Comprehensive thermodynamic, exergoeconomic, and economic analyses of the system.•Multi-objective optimization based on artificial neural network and genetic algorithm.•A precise case study based on real solar radiation and electricity prices in San Fransisco.•Achieving a payback period of 2.67 years with total profit of 112 M$ for the case study. In this paper, a novel dual-purpose green energy storage system with the aim of power and potable water production is proposed and investigated from the thermodynamic and economic points of view. The proposed system is based on an innovative combination of compressed air energy storage with solar heliostat and multi-effect thermal vapor compression desalination units that provides power and clean water without any emissions. This system not only stores low price electricity as compressed air during off-peak times for peak shaving at high demand periods, but it also produces freshwater by recovering the waste heat that is a byproduct of the system at both charging and discharging periods. Exploiting solar energy for increasing the air turbine inlet temperature instead of using the conventional combustion chambers makes the system entirely environmentally friendly. Performing energy, exergy, and exergoeconomic analyses, an artificial neural network algorithm is developed to predict round trip efficiency and total cost rate as the leading indicators for energy and economic performance of the proposed system. Then, the obtained relations are introduced to the genetic algorithm for multi-objective optimization that considers both technical and economic aspects. The round trip efficiency and total cost rate are calculated to be 48.7% and 3056 $/h under the optimal design condition, respectively. Finally, utilizing the proposed system in the case study of San Francisco, United States of America, a total potable water production of 226,782 m3 and power generation of 27,551 MWh in a year with a payback period of 2.65 years were achieved.
ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2021.114053