News models for Electrical energy evaluation and water flow rate prediction of the photovoltaic water pumping systems in Cameroon

Kodji Deli, Etienne Tchoffo Houdji, Albert Ayang, Dieudonne Kidmo Kaoga, Noel Djongyang

energy evaluation, water flow rate prediction, models, PVWPS.

Energy yield of tree photovoltaic water pumping (PVWP) systems have been studied in order to predict real time water flow rate of a PV water pumping systems in the Sahelian regions of Cameroon. Four semi-experimental models have been developed for the purpose. Models are validated by measured data of water flow rate based on selected statistical parameters such as mean bias error (MBE), mean absolute bias error (MABE), root mean square error (RMSE) and determination coefficient (). To know if the performance parameters perform data adequately, comparison are made among different models or model can be compared itself through ideal and recommended values of these parameters. It appears that for stations 1 and 2, the model 4 performed data better than other models since performance parameters are within the recommended values. Indeed, the MBE (%), MABE (%), RMSE (%) and (R²), are respectively (-6.4), (8.83), (13.82) and (0.95), for station 1 and (-7.04), (9.83), (17.42), (0.97) for station 2. These performance parameters are within the rigorous criterion of the evaluation of models for these two stations. However, for the station 3, model 4 is recommended for the evaluation of water flow rate during the cloudiest day since Model 2 is recommended for the sunniest day. Indeed, for the cloudy day, the MBE (%), MABE (%), RMSE (%) and (R²) are respectively (-6.49), (6.63), (8.72), (0.97) for cloudy day and (8.36), (14.52), (36.78), (0.705) for sunny day. Regarding these data the model 4 can be used to evaluate the water flow rate for any locations and for cloudy and sunny days.

https://dx.doi.org/10.31873/IJEAS.11.05.14