A dynamic multi-objective optimization procedure for water cooling of a photovoltaic module

Abstract

Dynamic multi-objective optimization (DMOO) is implemented on a water-based cooling system to enhance the performance of a 50 W polycrystalline-based solar photovoltaic (PV) module. The DMOO is conducted under the climatic conditions of Tehran, Iran, with the aim of maximizing the power output while minimizing the amount of cooling water consumed. The results of the DMOO are compared against those of a no-cooling condition (NCC) and a constant water flow (CWF) condition of 0.1 LPM. Compared with CWF, DMOO is found to produce a 64.73% increase in the annual energy production and a 41.98% decrease in water usage over an entire year. Furthermore, compared to NCC, DMOO is able to reduce the average and maximum temperatures of the PV module by 54.07% and 61.02%, respectively in a year; these figures are 16.63% and 17.37% better than those of CWF. Moreover, on an annual basis, DMOO is found to reduce the difference between the average and maximum PV temperatures by 79.79% and 54.53% relative to NCC and CWF, respectively. This study shows that the performance of a PV module can be improved significantly by applying DMOO to its water-based cooling system.