Environmental and Efficiency Analysis of the Solar-Based Water Heating System Using an Integration Multi-objective Evolutionary Optimization and Decision-Making Framework

Solar energy is known as one of the best available, clean, and renewable energy sources. Solar energy-based technologies can play an important role in the reduction of greenhouse gas emissions and use of the fossil fuel in Iran. This paper presents the numerical modeling-based optimization of the indirect-expansion solar based (IX-SHP) water heating system. After the verification of the proposed IX-SHP system, the system performance is examined in the temperate climate of Iran. The coefficient of performance (COP) and the collector efficiency (CE) are considered as two indexes for the system performance. The sensitivity analysis (SA) is carried out using the one-way analysis of variance (ANOVA) method to define how the system performance is affected by the changes in input design parameters. Then, the optimization process is carried out via the single objective and bi-objective Ant Colony Optimization (ACO) algorithm to maximize the system performance. Next, to achieve the optimum configuration of the system, Shannon’s entropy decision-making method is integrated with the ACO algorithm by programming under the MatLab environment. The optimization results demonstrate that while the CE of the maximized IX-SHP decreases from 61 to 46.5