Assessment of Malaysia's Large‐Scale Solar Projects: Power System Analysis for Solar PV Grid Integration
Abstract: Malaysia targets to become the second‐largest producer of solar photovoltaic (PV) in the world by increasing the current output from 12% to 20% in 2020. The government also expects to achieve 45% reduction of greenhouse gas emission by 2030 through renewable energy mainly by solar PV. Large‐scale solar (LSS) aims to produce 2.5 GW, which contributes to 10% of the nation's electricity demands. The LSS system is held back by the grid‐scale integration, transmission, and distribution infrastructure. Thus, power system analysis is crucial to achieve optimization in LSS to power grid integration. This paper investigates various power system analysis models and recommends an optimized configuration based on Malaysia's LSS scenario. In stage 1, an optimal PV sizing is carried out based on real data of LSS installation in different locations. In stage 2, power analysis is carried out using to analyze the potential difference variation when connected to a nine‐bus power system. The potential variation at each bus of the system is assessed and hence provides a feasibility statement on the most effective configurations for LSS–grid integration. This paper serves as the reference model for LSS–grid integration in Malaysia and is expected to be replicated in the other countries with similar conditions.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Assessment of Malaysia's Large‐Scale Solar Projects: Power System Analysis for Solar PV Grid Integration ; volume:4 ; number:2 ; year:2020 ; extent:17
Global challenges ; 4, Heft 2 (2020) (gesamt 17)
- Creator
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Khan, Rehan
Go, Yun Ii
- DOI
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10.1002/gch2.201900060
- URN
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urn:nbn:de:101:1-2022070508282479302096
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:32 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Khan, Rehan
- Go, Yun Ii