Multi-objective optimization analysis on gas-steam combined cycle system with exergy theory

Gu, Hui; Cui, Xiaobo; Zhu, Hongxia; Si, Fengqi; Kong, Yu

doi:10.1016/j.jclepro.2020.123939

Cited by 10 publications

(2 citation statements)

References 24 publications

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“…Pan et al [11] proposed a waste heat exchanger that includes a supercritical CO 2 cycle, an organic Rankine cycle, and a vapor absorption refrigeration cycle and optimized the integrated system in respect to its thermodynamic, economic, and environmental parameters. Many researchers performed multi-objective optimization of gas-steam cycle applying non-dominated sorting genetic algorithm (NSGA-II) optimization technique for augmenting thermodynamic performance and minimizing exergoeconomic cost, environmental impact, and heat transfer component cost [2,[12][13][14][15][16][17][18]. Nadir et al [19] optimized the thermodynamic configuration of the heat recovery steam generator for maximizing the net specific work output of the steam cycle and the net present worth as an objective function using the Particle Swarm Optimization technique.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis and optimization of thermodynamic behavior of combined gas-steam power plant using grey-taguchi and artificial neural network

Madan

Singh

2023

Journal of Thermal Engineering

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In the published studies, to the best of the authors’ understanding, the grey Taguchi-based statistical technique has not been applied for the optimization of combined gas-steam power plants. In view of this, seven essential input parameters namely compressor inlet air temperature, pressure ratio, fuel temperature, volumetric flow rate of fuel, gas turbine maximum temperature, compressor efficiency, and turbine efficiency are chosen with the aim of determining the optimal combination of design variables that maximize the net power generation, thermal efficiency, exergetic effciency, and minimize the specific fuel consumption. Also, the impact weight of each parameter on output indicators has been evaluated. While the Taguchi approach helps to create an orthogonal array of L27 (3^7), the ANOVA method determines the contribution of each input argument on the objective function. Unlike the Taguchi and ANOVA optimization methodology, the grey relational analysis is performed to transform the multi-objective function into a single objective by way of estimating its grey relational grade. The most favorable combination of input parameters is determined as A1B1C1D1E3F3G3 and under this state, the optimum values of power generation, thermal efficiency, exergetic efficiency, and specific fuel consumption are found to be 259911 kW, 64.9 %, 66.27 %, and 0.1839 kg/kWh respectively. Moreover, the contribution ratio on the output characteristic of the combined cycle is found to be maximum for turbine efficiency (42.41 %) and minimum for fuel temperature (0.59 %). The effectiveness of the grey-Taguchi method is acknowledged and validated using an artificial neural network technique in MATLAB.

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Section: Introductionmentioning

confidence: 99%

Comparative analysis and optimization of thermodynamic behavior of combined gas-steam power plant using grey-taguchi and artificial neural network

Madan

Singh

2023

Journal of Thermal Engineering

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“…By using the ε-NTU analysis method, the model of a heat exchanger in a triple pressure reheat HRSG was established, and the pressure values of high, intermediate and low pressure steam in the HRSG were optimized with the aim of the highest system efficiency of CCGT [8]. Hui et al [9], with the aim of three objective functions (higher efficiency, less cost and lower emission), optimized the pressure values of HP, IP and LP steam in the HRSG based on a genetic algorithm. Yang [10] aimed to maximize the efficiency of the combined cycle and used genetic algorithms to optimize the pressure values of the HP, IP and LP steam in the HRSG.…”

Section: Introductionmentioning

confidence: 99%

Thermoeconomic Optimization of Steam Pressure of Heat Recovery Steam Generator in Combined Cycle Gas Turbine under Different Operation Strategies

Wang

Duan

2021

Energies

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The optimization of the steam parameters of the heat recovery steam generators (HRSG) of Combined Cycle Gas Turbines (CCGT) has become one of the important means to reduce the power generation cost of combined cycle units. Based on the structural theory of thermoeconomics, a thermoeconomic optimization model for a triple pressure reheat HRSG is established. Taking the minimization of the power generation cost of the combined cycle system as the optimization objective, an optimization algorithm based on three factors and six levels of orthogonal experimental samples to determine the optimal solution for the high, intermediate and low pressure steam pressures under different gas turbine (GT) operation strategies. The variation law and influencing factors of the system power generation cost with the steam pressure level under all operation strategies are analyzed. The research results show that the system power generation cost decreases as the GT load rate increases, T4 plays a dominant role in the selection of the optimal pressure level for high pressure (HP) steam and, in order to obtain the optimum power generation cost, the IGV T3-650-F mode should be adopted to keep the T4 at a high level under different GT load rates.

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Design and Part Load Performance Simulation of Natural Gas Combined Cycle with New Operating Regulation for Gas Turbine

Pattanayak

Padhi

2022

Arab J Sci Eng

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Multi-objective optimization analysis on gas-steam combined cycle system with exergy theory

Cited by 10 publications

References 24 publications

Comparative analysis and optimization of thermodynamic behavior of combined gas-steam power plant using grey-taguchi and artificial neural network

Comparative analysis and optimization of thermodynamic behavior of combined gas-steam power plant using grey-taguchi and artificial neural network

Thermoeconomic Optimization of Steam Pressure of Heat Recovery Steam Generator in Combined Cycle Gas Turbine under Different Operation Strategies

Design and Part Load Performance Simulation of Natural Gas Combined Cycle with New Operating Regulation for Gas Turbine

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