Abstract
Solar thermal systems have been widely used to increase energy efficiency in the building sector, since the use of renewable energy sources became one of the top priorities to meet environmental targets. The main objective of this study is the thermo-economic optimization of solar thermal systems for residential building applications, considering a multi-objective approach. The simulations were performed through a MatLab code by implementing an elitist variant of Non-dominated Sorting Genetic Algorithm-II (NASGA-II). The solar collection area and the linear loss coefficient as well as the tank storage volume were defined as decision variables. A two-dimensional Pareto front was obtained, considering as objective functions the minimization of the annualized investment cost and the maximization of the solar collection efficiency. Based on the best trade-off between both objectives and considering that the solar thermal systems can operate for a period of at least 15 years, the Pareto analysis led to the conclusion that a system with an annualized investment cost between 270 and 280 €/year allows reaching a collection efficiency of 60%. After the analysis of the optimal solution points, a configuration was selected to estimate the system total purchasing cost: a panel with a solar area of 4.17 m2 and with a linear coefficient loss of 3.684 W/m2.K; a storage volume of 0.275 m3; and a pump flow rate of 0.1364 m3/h. For this configuration, we estimated a total purchasing cost of 2545.0 €, whereas the solar collector and the storage tank are the most expensive components, representing a share of 42% and 43%, respectively. These results represent a specific cost of 610.3 €/m2 per solar collection area.