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Stochastic Hosting Capacity in LV Distribution Networks

Deakin, M., Crozier, C., Apostolopoulou, D. ORCID: 0000-0002-9012-9910 , Morstyn, T. & McCulloch, M. (2020). Stochastic Hosting Capacity in LV Distribution Networks. In: 2019 IEEE Power & Energy Society General Meeting (PESGM). 2019 IEEE PES General Meeting, 04 - 08 Aug 2019, Atlanta, GA, USA. doi: 10.1109/PESGM40551.2019.8973688


Hosting capacity is defined as the level of penetration that a particular technology can connect to a distribution network without causing power quality problems. In this work, we study the impact of solar photovoltaics (PV) on voltage rise. In most cases, the locations and sizes of the PV are not known in advance, so hosting capacity must be considered as a random variable. Most hosting capacity methods study the problem considering a large number of scenarios, many of which provide little additional information. We overcome this problem by studying only cases where voltage constraints are active, with results illustrating a reduction in the number of scenarios required by an order of magnitude. A linear power flow model is utilised for this task, showing excellent performance. The hosting capacity is finally studied as a function of the number of generators connected, demonstrating that assumptions about the penetration level will have a large impact on the conclusions drawn for a given network.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Publisher Keywords: Hosting Capacity, Distributed Power Generation, Distribution System Planning
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Departments: School of Science & Technology
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