Gene expression technique-based approach to improve the accuracy of estimating the total generated power by neighbouring photovoltaic systems
dc.contributor.author | Al-Hilfi, H.A.H. | |
dc.contributor.author | Shahnia, F. | |
dc.contributor.author | Abu-Siada, Ahmed | |
dc.date.accessioned | 2021-06-28T03:26:07Z | |
dc.date.available | 2021-06-28T03:26:07Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Al-Hilfi, H.A.H. and Shahnia, F. and Abu-Siada, A. 2020. Gene expression technique-based approach to improve the accuracy of estimating the total generated power by neighbouring photovoltaic systems. IET Renewable Power Generation. 14 (18): pp. 3715-3723. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/84226 | |
dc.identifier.doi | 10.1049/iet-rpg.2020.0279 | |
dc.description.abstract |
The penetration of photovoltaic systems (PVs) to existing power grids is increasing as they are considered attractive options for electricity generation in distribution networks. This paper focuses on estimating the total power generated by a group of neighbouring PVs, spread over a distribution network using a single pyranometer for measuring the solar irradiance. A new empirical-based model that employs the Gene Expression Programming (GEP) technique is proposed to correlate the distribution of the PVs and the irradiance measured by the pyranometer and estimate the total power generated by the PVs. The geographic variability reduction index has been considered in developing the proposed model that also employs a Wavelet Transform technique to enhance its accuracy. The effective performance of the proposed model is validated using real data collected by the Solar Project at the University of Queensland, Brisbane, Australia. Results reveal that the proposed technique yields more accurate results when compared with other existing approaches in the literature. | |
dc.title | Gene expression technique-based approach to improve the accuracy of estimating the total generated power by neighbouring photovoltaic systems | |
dc.type | Journal Article | |
dcterms.source.volume | 14 | |
dcterms.source.number | 18 | |
dcterms.source.startPage | 3715 | |
dcterms.source.endPage | 3723 | |
dcterms.source.issn | 1752-1416 | |
dcterms.source.title | IET Renewable Power Generation | |
dc.date.updated | 2021-06-28T03:26:06Z | |
curtin.department | School of Elec Eng, Comp and Math Sci (EECMS) | |
curtin.accessStatus | Open access via publisher | |
curtin.faculty | Faculty of Science and Engineering | |
curtin.contributor.orcid | Abu-Siada, Ahmed [0000-0002-2094-3036] [0000-0002-8560-3403] | |
curtin.contributor.researcherid | Abu-Siada, Ahmed [K-3809-2013] [O-7116-2019] | |
dcterms.source.eissn | 1752-1424 | |
curtin.contributor.scopusauthorid | Abu-Siada, Ahmed [24780681200] |
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