Evaluation of the Accuracy of Different PV Estimation Models and the Effect of Dust Cleaning: Case Study a 103 MW PV Plant in Jordan

Loiy Al-Ghussain, Moath Abu Subaih and Andres Annuk
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Loiy Al-Ghussain: Mechanical Engineering Department, University of Kentucky, Lexington, KY 40506, USA
Moath Abu Subaih: Planning Operation Section, SAMRA Electric Power Company (SEPCO), Amman 11821, Jordan
Andres Annuk: Energy Application Engineering, Estonian University of Life Sciences, 51006 Tartu, Estonia

Sustainability, 2022, vol. 14, issue 2, 1-15

Abstract: The estimation of PV production has been widely investigated previously, where many empirical models have been proposed to account for wind and soiling effects for specific locations. However, the performance of these models varies among the investigated sites. Hence, it is vital to assess and evaluate the performance of these models and benchmark them against the common PV estimation model that accounts only for the ambient temperature. Therefore, this study aims to evaluate the accuracy and performance of four empirical wind models considering the soiling effect, and compare them to the standard model for a 103 MW PV plant in Jordan. Moreover, the study investigates the effect of cleaning frequency on the annual energy production and the plant’s levelized cost of electricity ( LCOE ). The results indicate almost identical performance for the adopted models when comparing the actual energy production with R 2 and RMSE (root mean square error) ranges of 0.93–0.98 and 0.93–1.56 MWh for both sub-plants, with a slight superiority of the models that incorporate wind effect. Finally, it is recommended in this study to clean the PV panels every two weeks instead of every three months, which would increase annual energy production by 4%, and decrease the LCOE by 5% of the two PV sub-plants.

Keywords: PV energy estimation models; large-scale PV plants; wind effect; soiling effect; cleaning frequency (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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