Modeling and analysis of a solar minichannel flat plate collector system and optimization of operating conditions using particle swarms

Solar minichannel flat plate collector (MFPC) has shown appreciable results in the recent past. Compared to the conventional flat plate collector (CFPC), MFPC is simple in construction and provides better output. However, optimization studies on MFPC have not been well attended. In this paper, a simulation of MFPC is carried out using a novel mathematical model. The objectives of this study are to validate the mathematical model using experimental results; identify the major factors that highly influence the collector performance, and optimize the performance using an evolutionary algorithm. Collector performance, namely collector efficiency and water outlet temperature are bound to be affected by many factors like solar irradiation, water inlet temperature, mass flow rate, and channel width. A new technique of simulating MFPC is demonstrated for which equations are developed based on the energy balance principle and fin analysis at steady state. The model is validated by corroborating with experimental results. When compared with CFPC, MFPC is 10–12% more efficient. A design of experiments is used to determine the set of trials followed by MANOVA and regression analyses. Multi-objective particle swarm optimization (MOPSO) is adopted to maximize the collector performance. Regression equations for collector efficiency and water outlet temperatures serve as objective functions. The results revealed that solar radiation, water inlet temperature, flow rate, and channel width are highly significant factors. From the MOPSO analysis, a mass flow rate ranging between 0.01 and 0.015 kg/s is found to be optimal for the MFPC system.