Multi-objective optimization of a new cogeneration system driven by gas turbine cycle for power and freshwater production

2021 ◽  
Vol 288 ◽  
pp. 125639
Author(s):  
Pan Ding ◽  
Xiaojuan Liu ◽  
Hongling Qi ◽  
Hongtao Shen ◽  
Xiaochan Liu ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cogeneration System ◽  
Gas Turbine Cycle

Multi-objective optimization of a recuperative gas turbine cycle using non-dominated sorting genetic algorithm

2011 ◽  
Vol 225 (8) ◽  
pp. 1041-1051 ◽  
Author(s):  
H Sayyaadi ◽  
H R Aminian
Keyword(s):  
Genetic Algorithm ◽  
Gas Turbine ◽  
Heat Exchangers ◽  
Mixed Integer ◽  
Design Stage ◽  
Tube Length ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Gas Turbine Cycle

A regenerative gas turbine cycle with two particular tubular recuperative heat exchangers in parallel is considered for multi-objective optimization. It is assumed that tubular recuperative heat exchangers and its corresponding gas cycle are in design stage simultaneously. Three objective functions including the purchased equipment cost of recuperators, the unit cost rate of the generated power, and the exergetic efficiency of the gas cycle are considered simultaneously. Geometric specifications of the recuperator including tube length, tube outside/inside diameters, tube pitch, inside shell diameter, outer and inner tube limits of the tube bundle and the total number of disc and doughnut baffles, and main operating parameters of the gas cycle including the compressor pressure ratio, exhaust temperature of the combustion chamber and the air mass flowrate are considered as decision variables. Combination of these objectives anddecision variables with suitable engineering and physical constraints (including NO x and CO emission limitations) comprises a set of mixed integer non-linear problems. Optimization programming in MATLAB is performed using one of the most powerful and robust multi-objective optimization algorithms, namely non-dominated sorting genetic algorithm. This approach is applied to find a set of Pareto optimal solutions. Pareto optimal frontier is obtained, and a final optimal solution is selected in a decision-making process.

Multi-objective optimization for a small biomass cooling and power cogeneration system using binary mixtures

2021 ◽  
Vol 182 ◽  
pp. 116045
Author(s):  
César Adolfo Rodriguez Sotomonte ◽  
Thiago Gotelip Correa Veloso ◽  
Christian J.R. Coronado ◽  
Marco A. Rosa do Nascimento
Keyword(s):  
Binary Mixtures ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cogeneration System

Modeling of Gas Turbine-Based Cogeneration System

2012 ◽  
Author(s):  
Farshid Zabihian ◽  
Alan S. Fung ◽  
Fabio Schuler
Keyword(s):  
Power Plant ◽  
Gas Turbine ◽  
Power Plants ◽  
Superheated Steam ◽  
Hot Water ◽  
Cogeneration System ◽  
Exhaust Stream ◽  
Low Efficiency ◽  
Gas Turbine Cycle ◽  
Wasted Energy

Gas turbine-based power plants generate a significant portion of world’s electricity. This paper presents the modeling of a gas turbine-based cogeneration cycle. One of the reasons for the relatively low efficiency of a single gas turbine cycle is the waste of high-grade energy at its exhaust stream. In order to recover this wasted energy, steam and/or hot water can be cogenerated to improve the cycle efficiency. In this work, a cogeneration power plant is introduced to use this wasted energy to produce superheated steam for industrial processes. The cogeneration system model was developed based on the data from the Whitby cogeneration power plant in ASPEN PLUS®. The model was validated against the operational data of the existing power plant. The electrical and total (both electrical and thermal) efficiencies were around 40% and 70% (LHV), respectively. It is shown that cogenerating electricity and steam not only significantly improve the general efficiency of the cycle but it can also recover the output and efficiency losses of the gas turbine as a result of high ambient temperature by generating more superheated steam. Furthermore, this work shows that the model could capture the operation of the systems with an acceptable accuracy.

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