Title Operational performance of megawatt-scale grid integrated rooftop solar PV system in tropical wet and dry climates of India /
Authors Sandhya, Thotakura ; Sri, Chandan Kondamudi ; J. Francis, Xavier ; Ma, Quanjin ; Guduru, Rama Krishna Reddy ; Pavan, Gangwar ; Sri, Lakshmi Davuluri
DOI 10.1016/j.csite.2020.100602
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Is Part of Case studies in thermal engineering.. Amsterdam : Elsevier. 2020, vol. 18, art. no. 100602, p. 1-11.. ISSN 2214-157X
Keywords [eng] solar PV plants ; PV performance ; PVGIS ; PV watts ; PV Syst ; simulation tools
Abstract [eng] This case study presents the performance of a megawatt-scale grid-connected rooftop solar photovoltaic (PV) plant installed on the building rooftops of an educational institute (GITAM Deemed to be University) located in coastal regions (longitude 83° 23' 6.54'' E and latitude 17° 48' 8.208'' N) of Andhra Pradesh. A framework is proposed to validate the existing simulation models that are used for PV project modeling. The validation is done by comparing the simulated performance with the real-time monitored performance. The studied PV plant consists of 3078 solar panels and 23 inverters. For the analysis, we recorded the PV plant operational data for 12 months from 1st October 2018 to 30th September 2019. Based on the monitored data and by following the proposed framework, performance analysis is carried out. The results include the estimated parameters like energy outputs, yield factor, capacity factor, performance ratio, and the error matrices. The solar PV plant supplied energy of 1325.42 MWh to the grid during the monitored period. The expected outcomes of the solar PV plant are assessed using PVGIS, PV Watts, and PV Syst simulation tools. We observed an average mean bias error (MBE) of 5.33% (PVGIS), 12.33% (PV Watts) and 30.64% (PV Syst) and average normalized mean bias error (NMBE) of 2.954% (PVGIS), 7.88% (PV watts) and 22.75% (PV Syst). Overall, it is observed that there is a deviation between the simulated and monitored energy performance.
Published Amsterdam : Elsevier
Type Journal article
Language English
Publication date 2020
CC license CC license description