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http://hdl.handle.net/11189/9686| Title: | Methods and tools for PV and EV hosting capacity determination in low voltage distribution networks−a review | Authors: | Umoh, Vincent Davidson, Innocent Adebiyi, Abayomi Ekpe, Unwana |
Keywords: | Hosting capacity;solar PV;electric vehicle;distribution network;deterministic;stochasti;time series;streamlined;optimization | Issue Date: | 2023 | Publisher: | MDPI | Source: | Umoh, V. et al. 2023. Methods and tools for PV and EV hosting capacity determination in low voltage distribution networks−a review. Energies, 16(8):1-25. [https://doi.org/10.3390/en16083609] | Journal: | Energies | Abstract: | The increasing demand for electricity and the need for environmentally friendly transportation systems has resulted in the proliferation of solar photovoltaic (PV) generators and electric vehicle (EV) charging within the low voltage (LV) distribution network. This high penetration of PV and EV charging can cause power quality challenges, hence the need for hosting capacity (HC) studies to estimate the maximum allowable connections. Although studies and reviews are abundant on the HC of PV and EV charging available in the literature, there is a lack of reviews on HC studies that cover both PV and EVs together. This paper fills this research gap by providing a detailed review of five commonly used methods for quantifying HC including deterministic, time series, stochastic, optimization, and streamlined methods. This paper comprehensively reviews the HC concept, methods, and tools, covering both PV and EV charging based on a survey of state-of-the-art literature published within the last five years (2017−2022). Voltage magnitude, thermal limit, and loading of lines, cables, and transformers are the main performance indices considered in most HC studies. | URI: | http://hdl.handle.net/11189/9686 | ISSN: | 1996-1073 1996-1073 |
DOI: | https://doi.org/10.3390/en16083609 |
| Appears in Collections: | Eng - Journal articles (DHET subsidised) |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| Methods_Tools_for_PV_EV.pdf | 781.36 kB | Adobe PDF | View/Open |
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