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Abstract
This paper evaluates deterministic and probabilistic approaches for assessing hosting capacity (HC) of distribution networks for wind-based distributed generation (DG). The presented methodology considers variations of demands and DG power outputs, as well as dynamic thermal ratings (DTR) of network components. Deterministic approaches are based on a limited number of scenarios with minimum and maximum demands and DTR limits, while probabilistic approaches use simultaneous hourly values of all input parameters. The presented methodology has three stages. First, locational HC (LHC) of individual buses is calculated assuming connection of a single DG unit in the considered network. Afterwards, the LHC results are used to calculate network HC (NHC), assuming that DG units are connected at all network buses. Finally, busto-bus LHC-sensitivity factors are used to determine LHC and NHC for any number of DG units connected at arbitrary network buses.
Original language | English |
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Title of host publication | 2020 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2020 - Proceedings |
Subtitle of host publication | PMAPS |
Publisher | IEEE |
Pages | 1-6 |
Number of pages | 6 |
ISBN (Electronic) | 9781728128221 |
DOIs | |
Publication status | Published - 1 Sept 2020 |
Publication series
Name | 2020 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2020 - Proceedings |
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Bibliographical note
Publisher Copyright:© 2020 IEEE.
Keywords
- Deterministic and scenario-based analysis
- distributed generation
- dynamic thermal rating
- firm and non-firm capacity
- hosting capacity
- probabilistic analysis
- renewables
- wind energy
ASJC Scopus subject areas
- Computer Networks and Communications
- Statistics, Probability and Uncertainty
- Energy Engineering and Power Technology
- Safety, Risk, Reliability and Quality
- Statistics and Probability
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Dive into the research topics of 'Deterministic and Probabilistic Assessment of Distribution Network Hosting Capacity for Wind-Based Renewable Generation'. Together they form a unique fingerprint.Projects
- 1 Finished
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High Energy and Power Density (HEAPD) Solutions to Large Energy Deficits
Li, F. (PI), Redfern, M. (CoI) & Walker, I. (CoI)
Engineering and Physical Sciences Research Council
30/06/14 → 29/12/17
Project: Research council