Thermoecology-based performance simulation of a Gas-Mercury-Steam power generation system (GMSPGS)

Gonca, Güven; Genc, Ibrahim

doi:10.1016/j.enconman.2019.02.081

Cited by 23 publications

(6 citation statements)

References 89 publications

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“…Isentropic temperature ratios: where k 1 is specific heat ratio dependent on C p1 and C v1 ; k 2 is specific heat ratio dependent on C p2 and C v2 ; k 1 and k 2 are also called isentropic exponents [79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94][95][96][97][98]:…”

Section: Theoretical Modelmentioning

confidence: 99%

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Multi-criteria performance optimization and analysis of a gas–steam combined power system

Gonca

Başhan

2019

J Braz. Soc. Mech. Sci. Eng.

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This paper reports a comprehensive investigation of performances for a gas-steam combined power system (GSCPS) by considering exergy and thermo-ecology criteria. The most known and important parameters such as power density, power output, exergy destruction, exergetic efficiency, ecological coefficient performance (ECOP) and effective ecological power density (EFECPOD) are investigated. The influences of turbine design parameters such as turbine speed, mass flow rate of the working fluid, pressure ratio, equivalence ratio, intake air temperatures and pressures, residual gas fraction, fluid temperatures in heat exchanger, the pressure of high-pressure steam turbine, the pressure of medium-pressure steam turbine, the pressure of low-pressure steam turbine, the pressure of open feedwater heater, the pressure of condenser on the performance specifications have been evaluated. The results indicated that the component properties have remarkable impacts on the performance parameters of the GSCPS.

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Section: Theoretical Modelmentioning

confidence: 99%

“…The exergetic efficiency of each system component is attained by using the following equations [95][96][97][98][99][100].…”

Section: Theoretical Modelmentioning

confidence: 99%

Multi-criteria performance optimization and analysis of a gas–steam combined power system

Gonca

Başhan

2019

J Braz. Soc. Mech. Sci. Eng.

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“…Chen et al [ 54 ] provided a unified definition of

for heat engines, refrigerators and heat pumps. Gonca and Genc [ 55 ] investigated the

, power generation and density of power generation of a gas–mercury–steam system. Jin et al [ 56 ] optimized

performance of an irreversible recompression S-CO 2 cycle and analyzed the influence of the mass flow rate, pressure ratio and diversion coefficient on

performance.…”

Section: Introductionmentioning

confidence: 99%

Four-Objective Optimization for an Irreversible Porous Medium Cycle with Linear Variation in Working Fluid’s Specific Heat

Zang

Chen

et al. 2022

Entropy

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Considering that the specific heat of the working fluid varies linearly with its temperature, this paper applies finite time thermodynamic theory and NSGA-II to conduct thermodynamic analysis and multi-objective optimization for irreversible porous medium cycle. The effects of working fluid’s variable-specific heat characteristics, heat transfer, friction and internal irreversibility losses on cycle power density and ecological function characteristics are analyzed. The relationship between power density and ecological function versus compression ratio or thermal efficiency are obtained. When operating in the circumstances of maximum power density, the thermal efficiency of the porous medium cycle engine is higher and its size is less than when operating in the circumstances of maximum power output, and it is also more efficient when operating in the circumstances of maximum ecological function. The four objectives of dimensionless power density, dimensionless power output, thermal efficiency and dimensionless ecological function are optimized simultaneously, and the Pareto front with a set of solutions is obtained. The best results are obtained in two-objective optimization, targeting power output and thermal efficiency, which indicates that the optimal results of the multi-objective are better than that of one-objective.

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“…Finite time thermodynamics (FTT) [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ] has developed and emerged since the mid-1970s. With the continuous development and improvement of the theory, its research objects have expanded from Carnot heat engine to almost all engineering thermal devices and systems, which include the Stirling heat engine (SHE).…”

Section: Introductionmentioning

confidence: 99%

Four-Objective Optimization of an Irreversible Stirling Heat Engine with Linear Phenomenological Heat-Transfer Law

Chen

et al. 2022

Entropy

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This paper combines the mechanical efficiency theory and finite time thermodynamic theory to perform optimization on an irreversible Stirling heat-engine cycle, in which heat transfer between working fluid and heat reservoir obeys linear phenomenological heat-transfer law. There are mechanical losses, as well as heat leakage, thermal resistance, and regeneration loss. We treated temperature ratio x of working fluid and volume compression ratio λ as optimization variables, and used the NSGA-II algorithm to carry out multi-objective optimization on four optimization objectives, namely, dimensionless shaft power output P¯s, braking thermal efficiency ηs, dimensionless efficient power E¯p and dimensionless power density P¯d. The optimal solutions of four-, three-, two-, and single-objective optimizations are reached by selecting the minimum deviation indexes D with the three decision-making strategies, namely, TOPSIS, LINMAP, and Shannon Entropy. The optimization results show that the D reached by TOPSIS and LINMAP strategies are both 0.1683 and better than the Shannon Entropy strategy for four-objective optimization, while the Ds reached for single-objective optimizations at maximum P¯s, ηs, E¯p, and P¯d conditions are 0.1978, 0.8624, 0.3319, and 0.3032, which are all bigger than 0.1683. This indicates that multi-objective optimization results are better when choosing appropriate decision-making strategies.

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Thermoecology-based performance simulation of a Gas-Mercury-Steam power generation system (GMSPGS)

Cited by 23 publications

References 89 publications

Multi-criteria performance optimization and analysis of a gas–steam combined power system

Multi-criteria performance optimization and analysis of a gas–steam combined power system

Four-Objective Optimization for an Irreversible Porous Medium Cycle with Linear Variation in Working Fluid’s Specific Heat

Four-Objective Optimization of an Irreversible Stirling Heat Engine with Linear Phenomenological Heat-Transfer Law

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