Thermo-economic and environmental optimization of solar assisted heat pump by using multi-objective particle swam algorithm

In this paper, a solar assisted heat pump is modelled and optimized. Solar panel surface areas, evaporator pressure, condenser pressure, capacity of heat storage tank as well as the value of superheating/subcooling in evaporator/condenser are selected as design parameters. MOPSO (Multi-objective Particle Swarm Optimization) algorithm is used to find the optimum value of design parameters where TAC (total annual cost) and COP (coefficient of performance) taken as two objective functions. TAC is included with sum of investment, operation and environmental costs. The optimization is separately performed for five working fluids including R123, R134a, R245fa, R407C and R22. The optimization results showed that the best studied working fluid is R245fa in both thermo-economical and environmental view point with 1746.1 $/year as TAC, 3.76 for COP and annual environmental cost of 81.825. The optimum results of R245fa as working fluid, showed 15.22%, 21.28%, 22.31% and 44.66% improvement in TAC compared with R134a, R123, R22 and R407C, respectively. Furthermore, COP improvement for R245fa was obtained 26.77%, 30.92%, 34.31% and 48.12% compared with R134a, R123, R22 and R407C, respectively.