1. Ahmadi P, Dincer I, Rosen MA. Thermodynamic modeling and multi-objective evolutionary-based optimization of a new multigeneration energy system. Energy Conversion and Management, 2013;76:282-300. [
Link] [
DOI:10.1016/j.enconman.2013.07.049]
2. Taheri M, Mosaffa A, Farshi LG. Energy, exergy and economic assessments of a novel integrated biomass based multigeneration energy system with hydrogen production and LNG regasification cycle. Energy. 2017;125:162-177. [
Link] [
DOI:10.1016/j.energy.2017.02.124]
3. Khalid F, Dincer I, Rosen MA. Energy and exergy analyses of a solar-biomass integrated cycle for multigeneration. Solar Energy. 2015;112:290-299. [
Link] [
DOI:10.1016/j.solener.2014.11.027]
4. Nami H, Akrami E. Analysis of a gas turbine based hybrid system by utilizing energy, exergy and exergoeconomic methodologies for steam, power and hydrogen production. Energy Conversion and Management. 2017;143:326-337. [
Link] [
DOI:10.1016/j.enconman.2017.04.020]
5. Chen Q, Han W, Zheng JJ, Sui J, Jin HG. The exergy and energy level analysis of a combined cooling, heating and power system driven by a small scale gas turbine at off design condition. Applied Thermal Engineering. 2014;66(1-2):590-602. [
Link] [
DOI:10.1016/j.applthermaleng.2014.02.066]
6. Ezzat M. Dincer I. Energy and exergy analyses of a new geothermal–solar energy based system. Solar Energy. 2016;134:95-106. [
Link] [
DOI:10.1016/j.solener.2016.04.029]
7. Abbasi M, Chahartaghi M, Hashemian SM. Energy, exergy, and economic evaluations of a CCHP system by using the internal combustion engines and gas turbine as prime movers. Energy Conversion and Management. 2018;173:359-374. [
Link] [
DOI:10.1016/j.enconman.2018.07.095]
8. Zeng R, Li H, Liu L, Zhang X, Zhang G. A novel method based on multi-population genetic algorithm for CCHP–GSHP coupling system optimization. Energy Conversion and Management. 2015;105:1138-1148. [
Link] [
DOI:10.1016/j.enconman.2015.08.057]
9. Siddiqui O, Dincer I. Examination of a new solar-based integrated system for desalination, electricity generation and hydrogen production. Solar Energy. 2018;163:224-234. [
Link] [
DOI:10.1016/j.solener.2018.01.077]
10. Khalid F, Dincer I, Rosen MA. Techno-economic assessment of a solar-geothermal multigeneration system for buildings. International Journal of Hydrogen Energy. 2017;42(33):21454-21462. [
Link] [
DOI:10.1016/j.ijhydene.2017.03.185]
11. Sanaye S, Hajabdollahi H. Thermo-economic optimization of solar CCHP using both genetic and particle swarm algorithms. Journal of Solar Energy Engineering. 2015;137(1):011001. [
Link] [
DOI:10.1115/1.4027932]
12. Hajabdollahi H, Ganjehkaviri A, Jaafar MNM. Assessment of new operational strategy in optimization of CCHP plant for different climates using evolutionary algorithms. Applied Thermal Engineering. 2015;75:468-480. [
Link] [
DOI:10.1016/j.applthermaleng.2014.09.033]
13. Zhang H, Chen R, Wang F, Wang H, Wang Y. Multi-objective optimization for operational parameters of a micro-turbine CCHP system based on genetic algorithm. Procedia Engineering. 2017;205:1807-1814. [
Link] [
DOI:10.1016/j.proeng.2017.10.236]
14. Sadeghzadeh H, Ehyaei M, Rosen M. Techno-economic optimization of a shell and tube heat exchanger by genetic and particle swarm algorithms. Energy Conversion and Management. 2015;93:84-91. [
Link] [
DOI:10.1016/j.enconman.2015.01.007]
15. Lorestani A, Ardehali M. Optimal integration of renewable energy sources for autonomous tri-generation combined cooling, heating and power system based on evolutionary particle swarm optimization algorithm. Energy. 2018;145:839-855. [
Link] [
DOI:10.1016/j.energy.2017.12.155]
16. Lorestani A, Ardehali M. Optimization of autonomous combined heat and power system including PVT, WT, storages, and electric heat utilizing novel evolutionary particle swarm optimization algorithm. Renewable Energy. 2018;119:490-503. [
Link] [
DOI:10.1016/j.renene.2017.12.037]
17. Tichi S, Ardehali M, Nazari M. Examination of energy price policies in Iran for optimal configuration of CHP and CCHP systems based on particle swarm optimization algorithm. Energy Policy. 2010;38(10):6240-6250. [
Link] [
DOI:10.1016/j.enpol.2010.06.012]
18. Wang L, Yang Y, Dong C, Morosuk T, Tsatsaronis G. Parametric optimization of supercritical coal-fired power plants by MINLP and differential evolution. Energy Conversion and Management. 2014;85:828-838. [
Link] [
DOI:10.1016/j.enconman.2014.01.006]
19. Fetanat A, Khorasaninejad E. Size optimization for hybrid photovoltaic–wind energy system using ant colony optimization for continuous domains based integer programming. Applied Soft Computing. 2015;31:196-209. [
Link] [
DOI:10.1016/j.asoc.2015.02.047]
20. Guo L, Liu W, Cai J, Hong B, Wang C. A two-stage optimal planning and design method for combined cooling, heat and power microgrid system. Energy Conversion and Management. 2013;74:433-445. [
Link] [
DOI:10.1016/j.enconman.2013.06.051]
21. Ahmadi P, Dincer I, Rosen MA. Multi-objective optimization of a novel solar-based multigeneration energy system. Solar Energy. 2014;108:576-591. [
Link] [
DOI:10.1016/j.solener.2014.07.022]
22. Ahmadi P, Dincer I, Rosen MA. Multi-objective optimization of an ocean thermal energy conversion system for hydrogen production. International Journal of Hydrogen Energy. 2015;40(24):7601-7608. [
Link] [
DOI:10.1016/j.ijhydene.2014.10.056]
23. Imran M, Usman M, Park BS, Kim HJ, Lee DH. Multi-objective optimization of evaporator of organic Rankine cycle (ORC) for low temperature geothermal heat source. Applied Thermal Engineering. 2015;80:1-9. [
Link] [
DOI:10.1016/j.applthermaleng.2015.01.034]
24. Wang M, Wang J, Zhao P, Dai Y. Multi-objective optimization of a combined cooling, heating and power system driven by solar energy. Energy Conversion and Management. 2015;89:289-297. [
Link] [
DOI:10.1016/j.enconman.2014.10.009]
25. Sanaye S, Hajabdollahi H. 4E analysis and multi-objective optimization of CCHP using MOPSOA. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. 2014;228(1):43-60. [
Link] [
DOI:10.1177/0954408912471001]
26. Soheyli S, Mayam MH, Mehrjoo M. Modeling a novel CCHP system including solar and wind renewable energy resources and sizing by a CC-MOPSO algorithm. Applied Energy. 2016;184:375-395. [
Link] [
DOI:10.1016/j.apenergy.2016.09.110]
27. Rashidi H, Khorshidi J. Exergy analysis and multiobjective optimization of a biomass gasification based multigeneration system. International Journal of Hydrogen Energy. 2018;43(5):2631-2644. [
Link] [
DOI:10.1016/j.ijhydene.2017.12.073]
28. Rashidi H, Khorshidi J. Exergoeconomic analysis and optimization of a solar based multigeneration system using multiobjective differential evolution algorithm. Journal of Cleaner Production. 2018;170:978-990. [
Link] [
DOI:10.1016/j.jclepro.2017.09.201]
29. Ishaq H, Dincer I, Naterer G. Exergy-based thermal management of a steelmaking process linked with a multi-generation power and desalination system. Energy. 2018;159:1206-1217. [
Link] [
DOI:10.1016/j.energy.2018.06.213]
30. Ghasemi A, Heidarnejad P, Noorpoor A. A novel solar-biomass based multi-generation energy system including water desalination and liquefaction of natural gas system: Thermodynamic and thermoeconomic optimization. Journal of Cleaner Production. 2018;196:424-437. [
Link] [
DOI:10.1016/j.jclepro.2018.05.160]
31. Mohammadi A, Mehrpooya M. Exergy analysis and optimization of an integrated micro gas turbine, compressed air energy storage and solar dish collector process. Journal of Cleaner Production. 2016;139:372-383. [
Link] [
DOI:10.1016/j.jclepro.2016.08.057]
32. Soltani R, Dincer I, Rosen MA. Thermodynamic analysis of a novel multigeneration energy system based on heat recovery from a biomass CHP cycle. Applied Thermal Engineering. 2015;89:90-100. [
Link] [
DOI:10.1016/j.applthermaleng.2015.05.081]
33. Islam S, Dincer I, Yilbas BS. Development, analysis and assessment of solar energy-based multigeneration system with thermoelectric generator. Energy Conversion and Management. 2018;156:746-756. [
Link] [
DOI:10.1016/j.enconman.2017.09.039]
34. Ahmadi P, Dincer I, Rosen MA. Thermoeconomic multi-objective optimization of a novel biomass-based integrated energy system. Energy. 2014;68:958-970. [
Link] [
DOI:10.1016/j.energy.2014.01.085]
35. Moghimi M, Emadi M, Ahmadi P, Moghadasi H. 4E analysis and multi-objective optimization of a CCHP cycle based on gas turbine and ejector refrigeration. Applied Thermal Engineering. 2018;141:516-530. [
Link] [
DOI:10.1016/j.applthermaleng.2018.05.075]
36. Sahu RK, Panda S, Padhan S. A hybrid firefly algorithm and pattern search technique for automatic generation control of multi area power systems. International Journal of Electrical Power & Energy Systems. 2015;64:9-23. [
Link] [
DOI:10.1016/j.ijepes.2014.07.013]
37. Feshki Farahani H, Rashidi F. An improved teaching-learning-based optimization with differential evolution algorithm for optimal power flow considering HVDC system. Journal of Renewable and Sustainable Energy. 2017;9(3):035505. [
Link] [
DOI:10.1063/1.4989828]
38. Czerniak JM, Zarzycki H. Artificial acari optimization as a new strategy for global optimization of multimodal functions. Journal of Computational Science. 2017;22:209-227. [
Link] [
DOI:10.1016/j.jocs.2017.05.028]
39. Tripathi PK, Bandyopadhyay S, Pal SK. Multi-objective particle swarm optimization with time variant inertia and acceleration coefficients. Information Sciences. 2007;177(22):5033-5049. [
Link] [
DOI:10.1016/j.ins.2007.06.018]
40. Deb K, Pratap A, Agarwal S, Meyarivan T. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation. 2002;6(2):182-197. [
Link] [
DOI:10.1109/4235.996017]
41. Borhanazad H, Mekhilef S, Ganapathy VG, Modiri-Delshad M, Mirtaheri A. Optimization of micro-grid system using MOPSO. Renewable Energy. 2014;71:295-306. [
Link] [
DOI:10.1016/j.renene.2014.05.006]