 Net load disaggregation at secondary substation levelMateo Toro-Cárdenas, Inês Moreira, Hugo Morais, Pedro M.S. Carvalho and Luis A.F.M. Ferreira Renewable Energy, 2023, vol. 207, issue C, 765-771 Abstract: With more and more micro-generation being connected to the low-voltage network, it becomes increasingly difficult for operators to anticipate the loading condition of their networks. Several facts concur with such difficulty, one being the frequent lack of knowledge about the generation component of the measured net load. The generation component is typically more volatile than the natural load and is impossible to predict without reliable information on the grid’s renewable installed capacity. In this context, the objective of this paper is to propose a non-intrusive methodology to estimate distributed generation’ installed capacity. Relying upon net-load historical data obtained at the secondary substation level and on historical meteorological data, the paper presents algorithms that proved effective in determining an approximation of the renewable embedded capacity. The accuracy and effectiveness of the proposed algorithms are illustrated in the paper with real data, for real use cases in the distribution systems. Keywords: Distribution network; Forecast; Net load disaggregation; Photovoltaic generation; Secondary substation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:207:y:2023:i:c:p:765-771 DOI: 10.1016/j.renene.2022.11.034 Access Statistics for this article Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides More articles in Renewable Energy from Elsevier |
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