Design and application of a distributed generation  hosting capacity algorithm

M. A. Sam; D. T. O Oyedokun; K.O Akpeji

doi:10.17159/2413-3051/2021/v32i3a10364

Authors

M. A. Sam Department of Electrical Engineering, University of Cape Town, Cape Town, South Africa https://orcid.org/0000-0001-5828-274X
D. T. O Oyedokun Department of Electrical Engineering, University of Cape Town, Cape Town, South Africa https://orcid.org/0000-0002-8025-0143
K.O Akpeji University of Cape Town https://orcid.org/0000-0003-2762-9186

DOI:

https://doi.org/10.17159/2413-3051/2021/v32i3a10364

Abstract

Distribution networks in Southern Africa and elsewhere are witnessing an unprecedented growth of consumer-side distributed generation (DG) courtesy of governmental interventions to maximise the utilisation of renewable energy resources through low-carbon grid-edge technologies. To deal with the increasing adoption of consumer-side DG, distribution network operators need to conduct technical studies to foster an understanding of the benefits and impacts of DG and the hosting capacity (HC) of existing distribution networks. This will aid the implementation of measures to manage grid exports. Using a distribution network in Namibia as a case study, this paper presents an algorithm for assessing the HC of consumer-side DG in existing distribution networks that are situated in areas anticipating high and uniform uptake of DG. The algorithm is a hybrid of deterministic and probabilistic methods. The uniqueness of the algorithm is the concept of calculating monthly HC. The algorithm was tested on a real existing residential distribution network and the results confirmed that HC varies monthly. However, the practical implementation of monthly HC requires upgrades to existing inverter technology, which currently contains a single export limit functionality. This opens the possibility to drive innovation in the inverter technology to develop a date-based multiple export limit functionality.

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Design and application of a distributed generation hosting capacity algorithm

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