Multi-criteria optimization of a micro solar-geothermal CCHP system applying water/CuO nanofluid based on exergy, exergoeconomic and exergoenvironmental concepts

• Published in: Applied thermal engineering Vol. 112; pp. 660 - 675
• Main Authors: Boyaghchi, Fateme Ahmadi, Chavoshi, Mansoure
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 05.02.2017; Elsevier BV
• Subjects: Accumulators; Collectors; Concentration (composition); Cooling; Copper oxides; Cost engineering; Decentralization; Economic analysis; Ejector refrigeration; Environmental impact; Exergy; Flat plate collector; Genetic algorithms; Geothermal power; Multiple objective analysis; Nanofluids; Nanoparticles; NSGA-II; Optimization; Organic Rankine cycle; Solar generators; Studies; Thermodynamics; Water/CuO nanofluid; Working fluids; Turkey; Flat plate collector; Ejector refrigeration; NSGA-II; Water/CuO nanofluid; Environmental impact; Organic Rankine cycle
• ISSN: 1359-4311; 1873-5606
• DOI: 10.1016/j.applthermaleng.2016.10.139

•A solar-geothermal CCHP is modeled using exergoeconomic and exergoenvironmental concepts.•ηex, ĊP,tot and ḂP,tot are selected as objective functions with twelve decision variables.•The increment of nanoparticles volume fraction has a positive effect on all objective functions.•NSGA-II is applied individually for R134a, R423A, R1234ze and R134yf. The main objective of the present study is to perform the thermodynamic, economic and environmental analyses of a solar-geothermal driven combined cooling, heating and power (CCHP) cycle integrated with flat plat collectors containing water/copper oxide (CuO) nanofluid as the absorbing medium. Twelve main parameters are selected as the decision variables of the desired system while the daily exergetic efficiency, total product cost rate and total product environmental impact associated with exergy rate are chosen as the three main objective functions. NSGA-II (Non-dominated Sort Genetic Algorithm-II) is individually applied to obtain the final optimal solutions in the multi-objective optimization of the desired system for four working fluids including R134a, R423A, R1234ze and R134yf from the exergy, exergoeconomic and exergoenviromental points of view. Based on the multi-objective optimization outcomes, R1234ze is the best fluid with 36.82Pts/h total product environmental impact rate so that the maximum nanoparticles volume fraction and minimum collector tilt angle are required. Moreover, R423A with the minimum total product cost rate of 4496 $/year is the best fluid at which minimum collector area is needed. Furthermore, R134a is the best fluid with 4.194% daily exergetic efficiency so that the minimum nanoparticle volume fraction is required compared with other studied fluids.