OPTIMIZATION OF MICRO GAS TURBINE BY ECONOMIC, EXERGY AND ENVIRONMENT ANALYSIS USING GENETIC, BEE COLONY AND SEARCHING ALGORITHMS

Year 2020, Volume: 6 Issue: 1, 117 - 140, 06.01.2020

Mehdi A. Aliehyaei

https://doi.org/10.18186/thermal.672054

Cited By: 8

Abstract

In this paper it was dealt with optimization of micro gas turbine with natural gas fuel in four configurations of simple, with regenerator, combined heat and power (CHP) and CHP with regenerator. Target function included energy and exergy efficiencies and electricity cost by considering effects of environmental pollution. Optimization procedures were genetic, bee colony and searching algorithms. Results showed that optimum air fuel ratio calculated by searching method for micro gas turbine with above-mentioned cycles were 1.7, 1.3, 1.6 and 2.3 respectively. By applying Genetic algorithm, optimum air fuel ratios were 1.40, 1.21, 1.42 and 1.82 respectively. At these points, energy efficiency obtained as 29, 34.4, 39.4 and 38.2 %, second law efficiency obtained as 61.4, 74.9, 85.4 and 57.2 %, electricity cost obtained as 0.102, 0.086, 0.075 and 0.029 US$/kWh respectively. By using bee colony algorithm, optimum air fuel ratios were 1.36, 1.13, 1.32 and 1.61 respectively. At these points, energy efficiency are 28.2, 34.3, 40.5 and 35.6 %, second law efficiency are 60.9, 75.67, 81.80 and 56.65 %, electricity costs are 0.105, 0.087, 0.073 and 0.03 US$/kWh respectively. Among these methods, Genetic algorithm was selected as best method because of best answer in optimization.

Keywords

Micro Gas Turbine, Exergy, Air Pollution, Optimization, Genetic, Honey Bees, Ant Colony

References

• [1] Aliehyaei M, Atabi F, Khorshidvand M, Rosen MA. Exergy, economic and environmental analysis for simple and combined heat and power IC engines. Sustainability. 2015;7:4411-24 DOI:10.3390/su7044411
• [2] Ashari G, Ehyaei M, Mozafari A, Atabi F, Hajidavalloo E, Shalbaf S. Exergy, economic, and environmental analysis of a PEM fuel cell power system to meet electrical and thermal energy needs of residential buildings. Jour of Fuel Cell Sci and Tech. 2012;9:051001 DOI: 10.1115/1.4006049.
• [3] Ehyaei M, Ahmadi P, Atabi F, Heibati M, Khorshidvand M. Feasibility study of applying internal combustion engines in residential buildings by exergy, economic and environmental analysis. Energy Build. 2012;55:405-13 DOI:10.1016/j.enbuild.2012.09.002.
• [4] Ehyaei M, Bahadori M. Selection of micro turbines to meet electrical and thermal energy needs of residential buildings in Iran. Energy Build. 2007;39:1227-34 DOI:10.016/j.enbuild.2007.01.006.
• [5] Ehyaei M, Hakimzadeh S, Enadi N, Ahmadi P. Exergy, economic and environment (3E) analysis of absorption chiller inlet air cooler used in gas turbine power plants. Int J of Energy Res. 2012;36:486-98 DOI:/10.1002/er.814.
• [6] Ehyaei M, Mozafari A, Ahmadi A, Esmaili P, Shayesteh M, Sarkhosh M, et al. Potential use of cold thermal energy storage systems for better efficiency and cost effectiveness. Energy Build. 2010;42:2296-303 DOI:10.1016/j.enbuild.2010.07.013.
• [7] Ehyaei M, Mozafari A, Alibiglou M. Exergy, economic & environmental (3E) analysis of inlet fogging for gas turbine power plant. Energy. 2011;36:6851-61 DOI: 10.1016/j.energy.2011.10.011.
• [8] Ehyaei MA, Tahani M, Ahmadi P, Esfandiari M. Optimization of fog inlet air cooling system for combined cycle power plants using genetic algorithm. Appl Ther Eng. 2015;76:449-61 10.1016/j.applthermaleng.2014.11.032.
• [9] Mohammadnezami MH, Ehyaei MA, Rosen MA, Ahmadi MH. Meeting the electrical energy needs of a residential building with a wind-photovoltaic hybrid system. Sustainability. 2015;7:2554-69 DOI:10.3390/su7032554.
• [10] Mozafari A, Ahmadi A, Ehyaei M. Optimisation of micro gas turbine by exergy, economic and environmental (3E) analysis. IntJ Exergy. 2010;7:1 DOI:10.1504/IJEX.2010.029611.
• [11] Saidi M, Abbassi A, Ehyaei M. Exergetic optimization of a PEM fuel cell for domestic hot water heater. Journal Fuel Cell Sci and Tech. 2005;2:284-9 DOI: 10.1115/1.2041672.
• [12] Saidi M, Ehyaei M, Abbasi A. Optimization of a combined heat and power PEFC by exergy analysis. J Power Sources. 2005;143:179-84 DOI:10.1016/j.jpowsour.2004.11.061.
• [13] Shamoushaki M, Ehyaei M, Ghanatir F. Exergy, economic and environmental analysis and multi-objective optimization of a SOFC-GT power plant. Energy. 2017;134:515-31 DOI:10.1016/j.energy.2017.06.058.
• [14] Yazdi BA, Yazdi BA, Ehyaei MA, Ahmadi A. Optimization of micro combined heat and power gas turbine by genetic algorithm. Ther Sci. 2015;19:207-18 DOI:10.2298/TSCI121218141.
• [15] Ponce-Ortega JM, Serna-González M, Jiménez-Gutiérrez A. Use of genetic algorithms for the optimal design of shell-and-tube heat exchangers. Appl Ther Eng. 2009;29:203-9 DOI:/10.1016/j.applthermaleng.2007.06.040.
• [16] Ravagnani MASS, Caballero JA. Optimal heat exchanger network synthesis with the detailed heat transfer equipment design. Comp & Ch Eng. 2007;31:1432-48 DOI:10.016/j.compchemeng.2006.12.005.
• [17] Mozafari A, Ehyaei M. Effects of regeneration heat exchanger on entropy, electricity cost, and environmental pollution produced by micro gas turbine system. IntJ green energy. 2012;9:51-70 DOI:10.1080/15435075.2011.617021.
• [18] Shamoushaki M, EHYAEI MA. EXERGY, ECONOMIC, AND ENVIRONMENTAL (3E) ANALYSIS OF A GAS TURBINE POWER PLANT AND OPTIMIZATION BY MOPSO ALGORITHM. Therl Sci. 2018;22:2641-51 DOI:10.298/TSCI161011091S.
• [19] Shamoushaki M, Ghanatir F, Ehyaei M, Ahmadi A. Exergy and exergoeconomic analysis and multi-objective optimisation of gas turbine power plant by evolutionary algorithms. Case study: Aliabad Katoul power plant. Int J Exergy. 2017;22:279-307 DOI:10.1504/IJEX.2017.083160.
• [20] Labinov S, Zaltash A, Rizy DT, Fairchild PD, DeVault R, Vineyard E. Predictive algorithms for microturbine performance for BCHP systems. ASHRAE Trans. 2002;108:670-81 DOI:10.1.1.488.301.
• [21] Ahmadi A, Ehyaei M. Exergy analysis of a wind turbine. Int J Exergy. 2009;6:457-76 DOI:10.1504/IJEX.2009.026672.
• [22] Ali Ehyaei M, Tanehkar M, Rosen MA. Analysis of an Internal Combustion Engine Using Porous Foams for Thermal Energy Recovery. Sustainability. 2016;8:267 DOI:10.3390/su8030267.
• [23] Asgari E, Ehyaei M. Exergy analysis and optimisation of a wind turbine using genetic and searching algorithms. Int J Exergy. 2015;16:293-314 DOI:10.1504/IJEX.2015.068228.
• [24] Chegini S, Ehyaei M. Economic, exergy, and the environmental analysis of the use of internal combustion engines in parallel-to-network mode for office buildings. J Brazilian Soc of Mech Sci and Eng. 2018;40:433 DOI:10.1007/s40430-018-1349-4.
• [25] Darvish K, Ehyaei MA, Atabi F, Rosen MA. Selection of optimum working fluid for Organic Rankine Cycles by exergy and exergy-economic analyses. Sustainability. 2015;7:15362-83 DOI:10.3390/su71115362.
• [26] Ehyaei M, Bahadori M. Internalizing the social cost of noise pollution in the cost analysis of electricity generated by wind turbines. Wind Eng. 2006;30:521-9 DOI: 10.1260/030952406779994114.
• [27] Ehyaei M, Rosen MA. Optimization of a triple cycle based on a solid oxide fuel cell and gas and steam cycles with a multiobjective genetic algorithm and energy, exergy and economic analyses. Energy Con and Manag. 2019;180:689-708 DOI:10.1016/j.enconman.2018.11.023.
• [28] Ehyaei MA. Estimation of condensate mass flow rate during purging time in heat recovery steam generator of combined cycle power plant. Ther Sci. 2014;18:1389-97 DOI:10.2298/tsci111031102e.
• [29] Ghasemian E, Ehyaei M. Evaluation and optimization of organic Rankine cycle (ORC) with algorithms NSGA-II, MOPSO, and MOEA for eight coolant fluids. Int J of Energy and Environ Eng. 2018;9:39-57 10.1007/s40095-017-0251-7.
• [30] Hamid Kazemi MAE. Energy, exergy, and economic analysis of a geothermal power plant. adv geo-energy research. 2018;2:190-209 DOI:10.26804/ager.2018.02.07.
• [31] Yousefi M, Ehyaei M. Feasibility study of using organic Rankine and reciprocating engine systems for supplying demand loads of a residential building. Adv in Build Ener Rese. 2017:1-17 DOI:0.1080/17512549.2017.1354779.
• [32] Kaikko J, Backman J. Technical and economic performance analysis for a microturbine in combined heat and power generation. Energy. 2007;32:378-87 DOI:10.1016/j.energy.2006.06.013
• [33] Haugwitz S. Modelling of microturbine systems. 2003 European Control Conference (ECC): IEEE; 2003. p. 1234-9
• [34] Bergman TL, Incropera FP, Lavine AS, Dewitt DP. Introduction to heat transfer: John Wiley & Sons; 2011.
• [35] Bejan A. Fundamentals of exergy analysis, entropy generation minimization, and the generation of flow architecture. Int J Energy Res. 2002;26: 0-43 DOI:10.1002/er.804.
• [36] Frangopoulos CA. Thermo-economic functional analysis and optimization. Energy. 1987;12:563-71 10.1016/0360-5442(87)90097-1.
• [37] Horngren CT, Foster G, Datar SM. Cost Accounting: A Managerial Emphasis, Prentice Hall. Inc; 2003.
• [38] Glover F. Future paths for integer programming and links to artificial intelligence. Comp & oper resea. 1986;13:533-49 DOI: /10.1016/0305-548(86)90048-1.
• [39] Rohaninejad M, Kheirkhah AS, Vahedi Nouri B, Fattahi P. Two hybrid tabu search–firefly algorithms for the capacitated job shop scheduling problem with sequence-dependent setup cost. Int JComputer Integ Manuf. 2015;28:470-87 DOI:10.1080/0951192X.2014.880808.
• [40] Karaboga D, Basturk B. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J glob optim. 2007;39:459-71 DOI:10.1007/s10898-007-9149-x.