scholarly journals Power density analysis and multi-objective optimization for a modified endoreversible simple closed Brayton cycle with one isothermal heating process

2020 ◽  
Vol 6 ◽  
pp. 1648-1657 ◽  
Author(s):  
Chenqi Tang ◽  
Huijun Feng ◽  
Lingen Chen ◽  
Wenhua Wang
Keyword(s):  
Power Density ◽  
Heating Process ◽  
Brayton Cycle ◽  
Multi Objective Optimization ◽  
Isothermal Heating ◽  
Multi Objective ◽  
Density Analysis

scholarly journals Power, Efficiency, Power Density and Ecological Function Optimization for an Irreversible Modified Closed Variable-Temperature Reservoir Regenerative Brayton Cycle with One Isothermal Heating Process

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5133 ◽  
Author(s):  
Lingen Chen ◽  
Chenqi Tang ◽  
Huijun Feng ◽  
Yanlin Ge
Keyword(s):  
Power Density ◽  
Heat Exchangers ◽  
Variable Temperature ◽  
Pressure Ratio ◽  
Ecological Function ◽  
Function Optimization ◽  
Cycle Performance ◽  
Heating Process ◽  
Brayton Cycle ◽  
Isothermal Heating

One or more isothermal heating process was introduced to modify single and regenerative Brayton cycles by some scholars, which effectively improved the thermal efficiency and significantly reduced the emissions. To analyze and optimize the performance of this type of Brayton cycle, a regenerative modified Brayton cycle with an isothermal heating process is established in this paper based on finite time thermodynamics. The isothermal pressure drop ratio is variable. The irreversibilities of the compressor, turbine and all heat exchangers are considered in the cycle, and the heat reservoirs are variable-temperature ones. The function expressions of four performance indexes; that is, dimensionless power output, thermal efficiency, dimensionless power density and dimensionless ecological function are obtained. With the dimensionless power density as the optimization objective, the heat conductance distributions among all heat exchangers and the thermal capacitance rate matching among the working fluid and heat reservoir are optimized. Based on the NSGA-II algorithm, the cycle’s double-, triple- and quadruple-objective optimization are conducted with the total pressure ratio and the heat conductance distributions among heat exchangers as design variables. The optimal value is chosen from the Pareto frontier by applying the LINMAP, TOPSIS and Shannon entropy methods. The results show that when the pressure ratio in the compressor is less than 12.0, it is beneficial to add the regenerator to improve the cycle performance; when the pressure ratio is greater than 12.0, adding the regenerator will reduce the cycle performance. For single-objective optimization, the four performance indexes could be maximized under the optimal pressure ratios, respectively. When the pressure ratio is greater than 9.2, the cycle is simplified to a closed irreversible simple modified Brayton cycle with one isothermal heating process and coupled to variable-temperature heat reservoirs. Therefore, when the regenerator is used, the range of pressure ratio is limited, and a suitable pressure ratio should be selected. The triple objective (dimensionless power output, dimensionless power density and dimensionless ecological function) optimization’ deviation index gained by LINMAP or TOPSIS method is the smallest. The optimization results gained in this paper could offer some new pointers for the regenerative Brayton cycles’ optimal designs.

Thermodynamic and Economic Analysis and Multi-Objective Optimization of Supercritical CO2 Brayton Cycles

2015 ◽  
Author(s):  
Hang Zhao ◽  
Qinghua Deng ◽  
Wenting Huang ◽  
Zhenping Feng
Keyword(s):  
Supercritical Co2 ◽  
Exergy Efficiency ◽  
Temperature Cycle ◽  
Inlet Temperature ◽  
Brayton Cycle ◽  
Multi Objective Optimization ◽  
Turbine Inlet Temperature ◽  
Multi Objective ◽  
Turbine Inlet ◽  
Thermodynamic Performance

Supercritical CO2 Brayton cycles (SCO2BC) offer the potential of better economy and higher practicability due to their high power conversion efficiency, moderate turbine inlet temperature, compact size as compared with some traditional working fluids cycles. In this paper, the SCO2BC including the SCO2 single-recuperated Brayton cycle (RBC) and recompression recuperated Brayton cycle (RRBC) are considered, and flexible thermodynamic and economic modeling methodologies are presented. The influences of the key cycle parameters on thermodynamic performance of SCO2BC are studied, and the comparative analyses on RBC and RRBC are conducted. Based on the thermodynamic and economic models and the given conditions, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used for the Pareto-based multi-objective optimization of the RRBC, with the maximum exergy efficiency and the lowest cost per power ($/kW) as its objectives. In addition, the Artificial Neural Network (ANN) is chosen to establish the relationship between the input, output, and the key cycle parameters, which could accelerate the parameters query process. It is observed in the thermodynamic analysis process that the cycle parameters such as heat source temperature, turbine inlet temperature, cycle pressure ratio, and pinch temperature difference of heat exchangers have significant effects on the cycle exergy efficiency. And the exergy destruction of heat exchanger is the main reason why the exergy efficiency of RRBC is higher than that of RBC under the same cycle conditions. Compared with the two kinds of SCO2BC, RBC has a cost advantage from economic perspective, while RRBC has a much better thermodynamic performance, and could rectify the temperature pinching problem that exists in RBC. Therefore, RRBC is recommended in this paper. Furthermore, the Pareto front curve between the cycle cost/ cycle power (CWR) and the cycle exergy efficiency is obtained by multi-objective optimization, which indicates that there is a conflicting relation between them. The optimization results could provide an optimum trade-off curve enabling cycle designers to choose their desired combination between the efficiency and cost. Moreover, the optimum thermodynamic parameters of RRBC can be predicted with good accuracy using ANN, which could help the users to find the SCO2BC parameters fast and accurately.

Thermodynamic and Economic Analysis and Multi-objective Optimization of Supercritical CO2 Brayton Cycles

2016 ◽  
Vol 138 (8) ◽  
Author(s):  
Hang Zhao ◽  
Qinghua Deng ◽  
Wenting Huang ◽  
Dian Wang ◽  
Zhenping Feng
Keyword(s):  
Supercritical Co2 ◽  
Pressure Ratio ◽  
Economic Modeling ◽  
Exergy Efficiency ◽  
Temperature Cycle ◽  
Inlet Temperature ◽  
Brayton Cycle ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Thermodynamic Performance

Supercritical CO2 Brayton cycles (SCO2BC) including the SCO2 single-recuperated Brayton cycle (RBC) and recompression recuperated Brayton cycle (RRBC) are considered, and flexible thermodynamic and economic modeling methodologies are presented. The influences of the key cycle parameters on thermodynamic performance of SCO2BC are studied, and the comparative analyses on RBC and RRBC are conducted. Nondominated Sorting Genetic Algorithm II (NSGA-II) is selected for the Pareto-based multi-objective optimization of the RRBC, with the maximum exergy efficiency and the lowest cost per power (k$/kW) as its objectives. Artificial neural network (ANN) is chosen to accelerate the parameters query process. It is shown that the cycle parameters such as heat source temperature, turbine inlet temperature, cycle pressure ratio, and pinch temperature difference of heat exchangers have significant effects on the cycle exergy efficiency. The exergy destruction of heat exchanger is the main reason why the exergy efficiency of RRBC is higher than that of the RBC under the same cycle conditions. RBC has a cost advantage from economic perspective, while RRBC has a much better thermodynamic performance, and could rectify the temperature pinching problem that exists in RBC. It is also shown that there is a conflicting relationship between the cycle cost/cycle power (CWR) and the cycle exergy efficiency. The optimization results could provide an optimum tradeoff curve enabling cycle designers to choose their desired combination between the efficiency and cost. ANN could help the users to find the SCO2BC parameters fast and accurately.

scholarly journals Multi-objective optimization on supercritical CO2 recompression brayton cycle using Kriging surrogate model

2017 ◽  
Vol 21 (suppl. 1) ◽  
pp. 309-316
Author(s):  
Lei Sun ◽  
Chongyu Wang ◽  
Di Zhang
Keyword(s):  
Supercritical Co2 ◽  
Thermodynamic Cycle ◽  
Brayton Cycle ◽  
Time Cost ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Research Fields ◽  
Cycle Efficiency ◽  
Recompression Cycle ◽  
Selection Of

Supercritical CO2 cycle has become one of the most popular research fields of thermal science. The selection of operation parameters on thermodynamic cycle process is an important task. The computational model of supercritical CO2 recompression cycle is built to solve the multi-objective problem in this paper. Then, the optimization of parameters is performed based on genetic algorithm. Several Kriging models are also used to reduce the quantity of samples. According to the calculation, the influence of sample quantity on the result and the time cost is obtained. The results show that it is required to improve the heat transfer when improvement of the cycle efficiency is desired.

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