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Research Papers

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

[+] Author and Article Information
Sofiane Haddad

Electronic Department,
Faculty of Sciences and Technology,
University of Jijel,
BP 157 Taher,
Jijel 18002, Algeria
e-mail: sof_had@yahoo.fr

Adel Mellit

Renewable Energy Laboratory,
Faculty of Sciences and Technology,
University of Jijel,
BP 98 Ouled Issa,
Jijel 18000, Algeria
e-mail: adelmellit2013@gmail.com

Mohamed Benghanem

Physics Department,
Faculty of Science,
Taibah University,
P.O. Box 344,
Madinah 274, Saudi Arabia
e-mail: benghanem_mohamed@yahoo.fr

Khalid Osman Daffallah

Physics Department,
Faculty of Science,
Taibah University,
P.O. Box 344,
Madinah 274, Saudi Arabia
e-mail: khalid_71@hotmail.com

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received May 21, 2015; final manuscript received October 12, 2015; published online November 25, 2015. Assoc. Editor: M. Keith Sharp.

J. Sol. Energy Eng 138(1), 011004 (Nov 25, 2015) (6 pages) Paper No: SOL-15-1152; doi: 10.1115/1.4031970 History: Received May 21, 2015; Revised October 12, 2015

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.

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References

Figures

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Fig. 1

Photograph of the real PVWPS

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Fig. 2

Measured solar irradiation from 1st June to 12th July (42 days)

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Fig. 3

Measured air temperature from 1st June to 12th July (42days)

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Fig. 4

Measured HWFR from 1st June to 12th July (42 days)

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Fig. 5

Flowchart of the proposed methodology for forecasting the WFR multihours ahead of a PVWP system

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Fig. 6

Real and forecasted HWFR, next-day 12-hrs ahead (12th July)

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Fig. 7

Real versus forecast from 1 hr to 12 hrs ahead

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