4.7 Article

A fast and simplified method using non-linear translation of operating points for PV modules energy output and daily pumped water to predict the performance of a stand-alone photovoltaic pumping system at different heads

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RENEWABLE ENERGY
卷 133, 期 -, 页码 248-260

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2018.10.004

关键词

PV pumping (E-pv,Q(d)) operating points; Head; Non-linear translation; Array energy output; Daily water pumped

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Predicting stand-alone photovoltaic (PV) pumping system performances at different heads is a key issue for designers and installers. The previous studies show that the head of well has a big effect on the performance of PV pumping system (PVPS). In this paper, a new practical model is proposed, in order to predict the daily pumped water quantity (Q(d)) and motor-pump efficiency for a given daily PV array energy output (E-pv) and any head (H). This model based on the no-linear translation of operating points for PV array energy output and daily pumped water quantity. This makes practical translation procedure much easier; only four E-pv-Q(d) operating points measured at any E-pv and H can be used as the reference E-pv-Q(d) operating points. For the validation, the test and measurement campaign carried out on the PVPS (model PS150) installed in the city of Adrar in the south of Algeria (Latitude 27 degrees 53' N, Longitude 0 degrees 17' W) has provided the necessary experimental data. The calculation of Q(d) over a wide range of E-pv and H well agree with experimental results of PVPS. This model can be used to investigate the reliability of the system to supply water in desert areas or isolated sites where no electricity supply is available depending on the required water demand. It is found that the optimum value of motor-pump efficiency can be obtained from PVPS fed by array PV with a nominal 300 Wp and installed in a well of 13.5 m head. We indicate that the translation of the E-pv-Q(d) operating points based on this method is effective for estimating the performance of the PVPS installed at any head and/or in any region. (C) 2018 Elsevier Ltd. All rights reserved.

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