SIZING ALGORITHM OF SOLAR-POWERED WATER PUMPING SYSTEM FOR DOMESTIC APPLICATION USING PARTICLE SWARM OPTIMIZATION

Abstract

Due to some issues faced in rural areas such as increasing water demand, the limited reach of electricity, as well as the scarcity of fossil fuel and its negative impact on the environment, renewable energy water pumping systems emerges as an excellent solution to solve those problems. In this case, the components in the renewable energy water pumping system ought to be optimized to improve the effectiveness of the system. This study was aimed at developing and analyzing an optimization model for the sizing of solar-powered water pumping systems for domestic applications. The sizing algorithm was developed using Particle Swarm Optimization (PSO) in MATLAB software. As a result of optimization, a summary of the main findings was provided, which include the optimal values for the number of solar panels, water tank capacity, and water pump power that minimize system costs and fulfill the water demand simultaneously. To investigate the performance of the proposed algorithm, several case studies have been evaluated by varying the total dynamic head (TDH) and water demands. In summary, TDH value primarily affects the number of PV panels and pump power, leaving the water tank capacity unchanged. However, the variations in water demand can impact all three parameters: the number of PV panels, water tank capacity, and water pump power. Overall, by applying the PSO method in the sizing algorithm of a solar-powered water pumping system, the cost could be minimized, and it would be able to cover the cost of water storage that supports the water demand of a certain application.