Development of an algebraic model that predicts the maximum power output of solar modules including their degradation
Nochang Park,
Ju-Hee Kim,
Hyun-A. Kim and
Jin-Chel Moon
Renewable Energy, 2017, vol. 113, issue C, 141-147
Abstract:
This study is focused on the development of a predicting model of maximum power output, which contains the algorithms of photovoltaic (PV) module degradation. These algorithms enable the model to calculate the power decrease as time goes by. PV plants are expected to operate for over 20 years. This results in the decrease of power output for the operation. By incorporating a number of accelerated tests, the degradation rate of mono–crystalline silicon PV modules was determined. These included: five temperature–humidity tests and three thermal cyclic tests. The results of temperature–humidity test illustrate that degradation rate depends on the thermal activation energy as well as the humidity parameter. Similarly, the results of thermal cyclic test demonstrate that decrease in power output is affected by thermal activation energy; however, it was also influenced by the temperature difference between maximum and minimum. In order to verify the accuracy of developed model, PV modules have been exposed to outdoor conditions (Dec 2014–Nov 2016). The final results proved that the developed model with the algorithms of PV module degradation was more accurate than that of predicted model without degradation algorithms in predicting the power output for long-term operation.
Keywords: Solar photovoltaic; Maximum power output; Sustainable; Reliability; Degradation (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:113:y:2017:i:c:p:141-147
DOI: 10.1016/j.renene.2017.05.073
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