Together with the developing nanotechnology, nanofluids and nanoparticles are used as working fluid in energy applications. It is foreseen that nanoparticles have high heat conduction coefficient and it will increase system performance by using as a working fluid in energy systems. Many studies in the literature show that nanofluids increase the heat transfer rate by improving heat transfer. In this study, a performance analysis of an absorption cooling system using solar energy was performed as numerically. LiBr-Al2O3-water nanofluid has been used in the cooling system as working fluid. The thermodynamic values and calculations used in the analyses were performed with Engineering Equation Solver program. Heat load necessary for the generator is provided with a flat plate solar collector. For different operation condition, the variation of COP values was determined depend on Al2O3-water nanoparticle concentration ratio. When the Al2O3-water nanoparticle concentrations are changed as 0%, 0.5% and 0.1%, it was determined that the COP values increased. Nanoparticles added to the refrigerant at certain concentration values affects the COP values positively of cooling systems. Maximum COP value is 0.86 for 85 oC generator temperature and 0.1% Al2O3-water nanoparticle concentration. The lowest COP value was obtained for the 75 oC generator temperature. When the Al2O3-water nanoparticle concentration was increased together with the generator temperature, COP values also increased. When the nanoparticle concentration of the working fluid increases, the viscosity of the nanofluid can be increases. Due to, increased viscosity increases the pressure drop in the flow channel and the pump power required for the flow. Thus, minimum viscosity with maximum thermal conductivity optimisation in applications is very important.

Two-stage compression operation prevents excessive compressor outlet pressure and temperature and this operation provides more efficient working condition in low-temperature refrigeration applications. Vapor compression refrigeration system with two-stage and intercooler is very good solution for low-temperature refrigeration applications. In this study, refrigeration system with two-stage and intercooler were optimized using fuzzy logic and genetic algorithm. The necessary thermodynamic characteristics for optimization were estimated with Fuzzy Logic and liquid phase enthalpy, vapour phase enthalpy, liquid phase entropy, vapour phase entropy values were compared with actual values. As a result, optimum working condition of system was estimated by the Genetic Algorithm as -6.0449 o C for evaporator temperature, 25.0115 o C for condenser temperature and 5.9666 for COP. Morever, irreversibility values of the refrigeration system are calculated.