2023
DOI: 10.1016/j.heliyon.2023.e13697
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Thermo-economic and environmental optimization using PSO of solar organic Rankine cycle with flat plate solar collector

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Cited by 8 publications
(2 citation statements)
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“…In recent years, the solar-based ORC technology has been the subject of numerous studies, many of which have focused on the choice of working fluid and components [12]: Tzivanidis et al [13] carried out a thermo-economic analysis of an ORC plant considering nine different working fluids; Yang et al [14] proposed an energy, economic and environmental analysis of an ORC unit considering three low-GWP working fluids; Sonsaree et al [15] compared the power obtained and the environmental and economic impact of a small-scale ORC-based unit considering three types of non-concentrating solar collectors. Many studies have also focused on parameters optimization, control strategies, and improved plant architectures: Cioccolanti et al [16] investigated the overall performance of a prototype ORC plant with a phase change material storage tank; Ochoa et al [17] evaluated the energy, environmental, and economic performance of two different configurations, basic and recuperative; Javed et al [18] compared the energetic and economic performance of three different ORC plant configurations (regenerative, recuperative and basic) with four working fluids. Despite theoretical and numerical analysis assessed that the effects of the recuperative preheating allow the introduction of significant thermodynamic and economic benefits, few experimental analysis on this topic have been provided, [19].…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, the solar-based ORC technology has been the subject of numerous studies, many of which have focused on the choice of working fluid and components [12]: Tzivanidis et al [13] carried out a thermo-economic analysis of an ORC plant considering nine different working fluids; Yang et al [14] proposed an energy, economic and environmental analysis of an ORC unit considering three low-GWP working fluids; Sonsaree et al [15] compared the power obtained and the environmental and economic impact of a small-scale ORC-based unit considering three types of non-concentrating solar collectors. Many studies have also focused on parameters optimization, control strategies, and improved plant architectures: Cioccolanti et al [16] investigated the overall performance of a prototype ORC plant with a phase change material storage tank; Ochoa et al [17] evaluated the energy, environmental, and economic performance of two different configurations, basic and recuperative; Javed et al [18] compared the energetic and economic performance of three different ORC plant configurations (regenerative, recuperative and basic) with four working fluids. Despite theoretical and numerical analysis assessed that the effects of the recuperative preheating allow the introduction of significant thermodynamic and economic benefits, few experimental analysis on this topic have been provided, [19].…”
Section: Introductionmentioning
confidence: 99%
“…In addition, due to the rapid development of meta-heuristic algorithms, many scholars use algorithms to optimize all aspects of energy systems. For example, the optimization of the thermal comfort of the house [ 16 ], the optimization of the stability of the nuclear-renewable energy hybrid system [ 17 ], the optimization of the utilization of renewable energy in the building [ 18 ], the optimization of the equipment capacity configuration of combined heat and power plant [ 19 ], the optimization of the energy cost of the HVAC energy terminal [ 20 ], the optimization of the energy management of the micro-grid [ 21 ], the optimization of the photovoltaic distribution system [ 22 ], carbon emission optimization [ 23 ], thermo-economic and environmental optimization of solar collector [ 24 ], energy subsidy optimization [ 25 ], economic transaction optimization of energy system [ 26 ], Multi-objective optimization of integrated energy systems [ 27 , 28 ], etc. By using the optimization algorithm to optimize the energy system, the energy system is more economical, energy-saving and stable.…”
Section: Introductionmentioning
confidence: 99%