Quantifying Topological Flexibility of Active Distribution Networks Based on Community Detection Article Swipe
Active distribution networks (ADNs) provide a flexible platform to integrate various distributed generation sources, among which the intermittent renewable sources impose high operating uncertainty. Topological flexibility of ADNs should be exploited to counter the stochastic operating conditions by modifying the topologies of ADNs. Quantifying the topological flexibility is a vital step to utilize it, which is lacking in previous studies. A quantification method is proposed to measure the topological flexibility of ADNs in this paper. First, the community structures of ADNs are detected to achieve spatial partitions of the networks. Second, an improved spectral clustering algorithm is employed to significantly reduce the dimensionality of the partition space, in which the ADNs are further partitioned using the affinity propagation algorithm. Finally, a topological flexibility metric is defined based on the guiding role of sectionalizing and tie switches within and between communities. The proposed topological flexibility quantification method is a superb approach to the utilization of flexibility resources in distribution networks. Case study results of test ADNs demonstrate the effectiveness and efficiency of the proposed quantification method.
Related Topics
Concepts
Flexibility (engineering)
Topology (electrical circuits)
Metric (unit)
Computer science
Partition (number theory)
Curse of dimensionality
Cluster analysis
Network topology
Mathematical optimization
Distributed computing
Algorithm
Mathematics
Artificial intelligence
Engineering
Statistics
Computer network
Operations management
Combinatorics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/en13184786
- https://www.mdpi.com/1996-1073/13/18/4786/pdf?version=1600073951
- OA Status
- gold
- Cited By
- 3
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3086137543
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3086137543Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/en13184786Digital Object Identifier
- Title
-
Quantifying Topological Flexibility of Active Distribution Networks Based on Community DetectionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-09-14Full publication date if available
- Authors
-
Huizi Gu, Xiaodong ChuList of authors in order
- Landing page
-
https://doi.org/10.3390/en13184786Publisher landing page
- PDF URL
-
https://www.mdpi.com/1996-1073/13/18/4786/pdf?version=1600073951Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1996-1073/13/18/4786/pdf?version=1600073951Direct OA link when available
- Concepts
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Flexibility (engineering), Topology (electrical circuits), Metric (unit), Computer science, Partition (number theory), Curse of dimensionality, Cluster analysis, Network topology, Mathematical optimization, Distributed computing, Algorithm, Mathematics, Artificial intelligence, Engineering, Statistics, Computer network, Operations management, CombinatoricsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1, 2022: 2Per-year citation counts (last 5 years)
- References (count)
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43Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W1976245933, https://openalex.org/W2074606535, https://openalex.org/W2003965484, https://openalex.org/W4243994762, https://openalex.org/W2155297377, https://openalex.org/W1978813851, https://openalex.org/W2008193622, https://openalex.org/W2913033704, https://openalex.org/W2152753170, https://openalex.org/W2061949258, https://openalex.org/W2131579565, https://openalex.org/W2011735378, https://openalex.org/W2020206829, https://openalex.org/W6683429886, https://openalex.org/W2391531688, https://openalex.org/W2001711707, https://openalex.org/W1965180610, https://openalex.org/W2112090702, https://openalex.org/W2008620264, https://openalex.org/W2118608338, https://openalex.org/W373740153, https://openalex.org/W1968686485, https://openalex.org/W2392109819, https://openalex.org/W2147040528, https://openalex.org/W1985155531, https://openalex.org/W2164735154, https://openalex.org/W2127048411, https://openalex.org/W2121947440, https://openalex.org/W2126337883, https://openalex.org/W2132914434, https://openalex.org/W2095293504, https://openalex.org/W2030586864, https://openalex.org/W2161528141, https://openalex.org/W2019678018, https://openalex.org/W1975191997, https://openalex.org/W1978356399, https://openalex.org/W2160138905, https://openalex.org/W2113104174, https://openalex.org/W2030186864, https://openalex.org/W2762654164, https://openalex.org/W2764025117, https://openalex.org/W3102641634, https://openalex.org/W2160136197 |
| referenced_works_count | 43 |
| abstract_inverted_index.A | 60 |
| abstract_inverted_index.a | 5, 48, 120, 147 |
| abstract_inverted_index.an | 91 |
| abstract_inverted_index.be | 29 |
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| corresponding_author_ids | https://openalex.org/A5058548071 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I154099455 |
| citation_normalized_percentile.value | 0.57665873 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |