Optimal Placement and Sizing of Photovoltaics to Supply Water Pumping Stations

This paper presents a stochastic optimization-based algorithm to perceive the location and size of multiple solar photovoltaic (PV) generations in a distribution network optimally, focusing on supplying water system loads. The presented algorithm accounts for the uncertainty of PV production and load power demand. The solar irradiance real data for three years is used to extract representative solar irradiance profiles on different days and seasons using the k-means clustering algorithm. An IEEE 33-bus radial distribution test network has been implemented for the case study, and water stations are located within this grid. The load demand of water transmission stations is predicted based on historical data, and the uncertainty is modeled employing the normal probability distribution function. The outcomes demonstrated that the proposed stochastic planning model effectively addresses the PV generation uncertainty and optimally identifies the placement and capacity of PV units.