Grid-connected photovoltaic system performance prediction using long-term weather data / Nor Zaini Zakaria … [et al.]

Zakaria, Nor Zaini and Zainuddin, Hedzlin and Shaari, Sulaiman and Omar, Ahmad Maliki and Sulaiman, Shahril Irwan (2020) Grid-connected photovoltaic system performance prediction using long-term weather data / Nor Zaini Zakaria … [et al.]. Scientific Research Journal, 17 (1). pp. 43-57. ISSN 2289-649X

Abstract

This aim of this paper is to evaluate the accuracy of long-term weather data models for performance prediction of grid-connected photovoltaic (GCPV) systems. The analyses were done for a 6-year old metal deck roof retrofitted GCPV system located in Shah Alam, Malaysia. The monthly and annual energy yield of the actual field data for three consecutive years were compared with the predicted yield using the long-term weather data models. These models were the Typical Meteorological Year (TMY), Model Year Climate (MYC), Microclimate data, and Long-Term statistical Mean for ground station data at Subang. The findings can be a reference for photovoltaic (PV) system designers on the range of accuracy when using the weather data models for performance predictions of GCPV system in Malaysia.

Metadata

Item Type: Article
Creators:
CreatorsID Num. / Email
Zakaria, Nor ZainiUNSPECIFIED
Zainuddin, Hedzlinzainuddinhedzlin@gmail.com
Shaari, SulaimanUNSPECIFIED
Omar, Ahmad MalikiUNSPECIFIED
Sulaiman, Shahril IrwanUNSPECIFIED
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Photovoltaic power systems
Divisions: Universiti Teknologi MARA, Shah Alam > Research Management Centre (RMC)
Journal or Publication Title: Scientific Research Journal
Journal: UiTM Journal > Scientific Research Journal
ISSN: 2289-649X
Volume: 17
Number: 1
Page Range: pp. 43-57
Item ID: 30093
Uncontrolled Keywords: GCPV system, Performance prediction,Llong-term weather data, Typical meteorological year, Model year climate
URI: http://ir.uitm.edu.my/id/eprint/30093

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