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Encompassing Monte Carlo Estimator with fair division method in determination of best suited methods in photovoltaic systems under partial shading condition [articol]

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dc.contributor.author Soundarrajan, Helen Catherine
dc.date.accessioned 2024-10-09T06:46:05Z
dc.date.available 2024-10-09T06:46:05Z
dc.date.issued 2019
dc.identifier.citation Soundarrajan, Helen Catherine. Encompassing Monte Carlo Estimator with fair division method in determination of best suited methods in photovoltaic systems under partial shading condition. Timişoara: Editura Politehnica, 2019. en_US
dc.identifier.issn 1582-4594
dc.identifier.uri https://dspace.upt.ro/xmlui/handle/123456789/6735
dc.description.abstract Solar photovoltaic system is an emerging technology for renewable power source, but some natural and undesirable changes like shadows of tower, trees, buildings, passing clouds, brings major losses in power. In order to overcome this issue, two different interconnection schemes are studied and compared between each other. Minimum distance Average (MDA) is a method based on clustering algorithm used to improve the power loss for different shading conditions. Fair Division Method (FDM) is yet another method which is found to be efficient in partially shaded conditions. These two methods are examined under four shaded patterns, Short narrow (SN), Short wide (SW), Long narrow (LN), Long wide (LW). The performances of each method are studied and compared using Monte Carlo Estimator (MCE) and the results are presented based on the working of proposed methods. en_US
dc.language.iso en en_US
dc.publisher Timișoara : Editura Politehnica en_US
dc.relation.ispartofseries Journal of Electrical Engineering;Vol 19 No 5
dc.subject Photovoltaic (PV) en_US
dc.subject Fair division method (FDM) en_US
dc.subject Minimum distance average method (MDA) en_US
dc.title Encompassing Monte Carlo Estimator with fair division method in determination of best suited methods in photovoltaic systems under partial shading condition [articol] en_US
dc.type Article en_US


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