NARX-Based Short-Term Forecasting of Water Flow Rate of a Photovoltaic Pumping System: A Case Study

作者：Haddad Sofiane; Mellit Adel; Benghanem Mohamed; Daffallah Khalid Osman

来源：Journal of Solar Energy Engineering-Transactions of the ASME, 2016, 138(1): 011004.

DOI：10.1115/1.4031970

<jats:p>Hourly water flow rate (HWFR) forecasting is very important to photovoltaic water pumping system (PVWPS) planning, operation, and control. In this paper, a nonlinear autoregressive with exogenous input-recurrent neural network (NARX-RNN) is investigated for the prediction of water flow rate (WFR) using experimental data collected from a PVWPS installed at Madinah site (Saudi Arabia). Results showed that the developed NARX-based model is able to reach acceptable accuracy for 1–12 hrs (next-day) ahead predictions. The developed methodology provides valuable information to PVWPS operators for controlling the production, storage, and delivery of water.</jats:p>

• 出版日期2016-2