Multi-objective optimization of a solar-assisted heat pump for swimming pool heating using genetic algorithm

A proper assessment of heating systems for swimming pools should evaluate the compromise between comfort level and the willingness to pay for it. The present work presents a multi-objective optimization of indirect solar assisted heat pump systems for outdoor swimming pool heating. Four different configurations are reported; (airto-water heat pump and three solar assisted heat pumps, air-to-water, water-to-water and a dual-source); and evaluated in six different locations (three location in Chile: Antofagasta, Santiago, and Concepcion; and three locations in Brazil: Brazilia, Sao Paulo, and Florianopolis). The methodology approach configures two objectives optimization, the minimization of the Annualized Life Cycle Cost (ALCC) and the maximization of the comfort level offered by the swimming pool. The optimization scheme consists of using a combination of tools: the energy-savings potential of i-SAHP are evaluated using the TRNSYS software in combination with GenOpt; and the economic modeling and optimization are performed in the MATLAB environment, using an approximation model and variant of NSGA-II genetic algorithm for building the Pareto frontiers. The optimization results demonstrate that solar-assisted configurations present significant improvements in performance for almost all locations, reaching the same levels of comfort at lower ALCCs when compared with the ASHP configuration.