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Probabilistic methodology for calculating PV hosting capacity in LV networks using actual building roof data
ID Grabner, Miha (Author), ID Souvent, Andrej (Author), ID Suljanović, Nermin (Author), ID Košir, Andrej (Author), ID Blažič, Boštjan (Author)

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Abstract
There has been an increasing trend of integrating photovoltaic power plants (PVs). One of the important challenges for distribution system operators is to evaluate the total installed power of a PV that a particular network can host (or PV hosting capacity) while keeping voltage and element constraints within required limits. The major drawback of the existing methods for calculating PV hosting capacity is that they use the same installed power of the PV systems for all simulated PVs, as these methods do not use external data sources about building roofs. As a consequence, this has a significant impact on the final accuracy of the results. This paper presents a probabilistic methodology for calculating the PV hosting capacity in low voltage (LV) networks. The main contribution of this paper is the improved modeling of PV generation using actual building roof data when calculating the PV hosting capacity, as every building is treated according to its actual solar potential. Monte Carlo simulations with incorporated stochastic consumption and PV generation models are utilized for load flow calculations of the actual LV network. The simulation results presented in this paper prove that the proposed methodology increases the accuracy of the final PV hosting capacity calculations.

Language:English
Keywords:LV networks, hosting capacity, Monte Carlo, PV
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FE - Faculty of Electrical Engineering
Publication status:Published
Publication version:Version of Record
Year:2019
Number of pages:15 str.
Numbering:Vol. 12, iss. 21, art. 4086
PID:20.500.12556/RUL-132770 This link opens in a new window
UDC:621.3
ISSN on article:1996-1073
DOI:10.3390/en12214086 This link opens in a new window
COBISS.SI-ID:40299525 This link opens in a new window
Publication date in RUL:03.11.2021
Views:1197
Downloads:138
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Record is a part of a journal

Title:Energies
Shortened title:Energies
Publisher:Molecular Diversity Preservation International
ISSN:1996-1073
COBISS.SI-ID:518046745 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:01.11.2019

Secondary language

Language:Slovenian
Keywords:elektrotehnika, fotovoltaične elektrarne, nizkonapetostna omrežja, Monte Carlo

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