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Multiple distribution networks hosting capacity assessment using a stochastic approach
Luleå tekniska universitet, Energivetenskap.ORCID iD: 0000-0002-3449-1579
Luleå tekniska universitet, Energivetenskap.ORCID iD: 0000-0003-0749-7366
2023 (English)In: Sustainable Energy, Grids and Networks, E-ISSN 2352-4677, Vol. 36, article id 101170Article in journal (Refereed) Published
Abstract [en]

About 15 000-customers are connected to the individual secondary distribution networks supplied through 48-medium voltage 10 kV radial feeders. The hosting capacity assessment uses the end-customer voltage magnitude rise and transformer thermal overload. The hosting capacity is estimated by applying the “stochastic mixed aleatory-epistemic method” to determine the voltage magnitude rise and load flow with solar PV. The minimum power consumption is compared with the solar PV power infeed through the individual transformers. The hosting capacity estimation is done for three-phase connected solar PV sizes from 3 to 18 kW. At moderate PV penetration (25%–50%), the results showed that overvoltage would limit the hosting capacity more often than overload, but it becomes an issue only for LV networks studied with more than 8-customers. Considering all LV networks, most of the customers could install 6 kWp. Even when installing PV systems of 18 kWp (about twice the average size today and about the maximum area of a typical residential roof), two-thirds of houses would not need an upgrade to withstand SS-EN 50160 voltage limits. The latter customers can connect solar PV units with 18 kWp size without overvoltage or overload issues.

Place, publisher, year, edition, pages
Elsevier , 2023. Vol. 36, article id 101170
Keywords [en]
Aleatory, Distribution network, Epistemic, Hosting capacity, Photovoltaic power systems, Uncertainty
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hig:diva-45761DOI: 10.1016/j.segan.2023.101170ISI: 001089060400001Scopus ID: 2-s2.0-85173485151OAI: oai:DiVA.org:hig-45761DiVA, id: diva2:1903133
Available from: 2024-10-03 Created: 2024-10-03 Last updated: 2025-10-02Bibliographically approved

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Mulenga, EnockEtherden, Nicholas

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