Modeling of PV Water Pumping Performance using Multi-Parallel Pump Switching for an Optimal Hydraulic Power Point Tracking

Performance of photovoltaic water pumping systems (PVWPS) directly coupled to pressured irrigation systems is mainly affected by irradiance fluctuations during days and seasons. Considerable efforts have been done to improve the photovoltaic outputs using maximum power point tracking (MPPT) concept. However, the improvement on the hydraulic side of PVWPS kept limited. For optimizing the hydraulic performance, a new concept of hydraulic power point tracking (HPPT) was, previously implemented and tested for yielding energy at the hydraulic network using parallel switching of irrigated sectors. Otherwise, the hydraulic performance can be yielded using similar concept of switching parallel pumps. The present research work aims for developing the HPPT approach based on multi-parallel pumps switching to enhance the performance of PVWPS. After that, the dataset taken from this HPPT approach was used for modeling the performance trends using the Python (TM) and R interfaces in order to evaluate and predict the system's optimal hydraulic performance. Results showed that use of the HPPT concept by switching multi-parallel pumps can effectively improves PVWPS performance. It can potentially increase the daily hydraulic energy by up to 50% during low irradiance periods and up to 20% during the day. The modeling of the growth performance is used to predict the daily optimal performances. The predictions were compared with the experimentally results to show that the modeling of the HPPT concept is promising for use as decisional tool to manage hydraulic performance (RMSE < 08.37% and MAE < 06.93%).