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Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 9 No. 1 (2019)

DOI
10.11591/ijece.v9i1.pp55-65
ISSN
2088-8708, 2088-8708
Published
2019-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

This paper presents a voltage sensitivity analysis with respect to the real power injected with renewable energies to determine the optimal integration of distributed generation (DG) in distribution systems (DS). The best nodes where the power injections improve voltages magnitudes complying with the constraints are determined. As it is a combinatorial problem, p article swarm optimization (PSO) and simulated annealing (SA) were used to change injections from 10% to 60% of the total power load using solar and wind generators and find the candidate nodes for installing power sources. The method was tested using the 33-node, 69-node and 118-node radial distribution networks. The results showed that the best nodes for injecting real power with renewable energies were selected for the distribution network by using the voltage sensitivity analysis. Algorithms found the best nodes for the three radial distribution networks with similar values in the maximum injection of real power, suggesting that this value maintains for all the power system cases. The injections applied to the different nodes showed that voltage magnitudes increase significantly, especially when exceeding the maximum penetration of DG. The test showed that some nodes support injections up to the limits, but the voltages increase considerably on all nodes.

Collaboration network of the authors

4 authors · 6 co-authorship links · 2 across different organisations

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  • Universidad de la Costa
  • Universidad del Norte
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 1 Nov 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems</dc:title><dc:creator>Cabana, Katherine</dc:creator><dc:creator>Candelo, John</dc:creator><dc:creator>Castillo, Rafael</dc:creator><dc:creator>Franco, Emiro De la Hoz</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span&amp;gt;This paper presents a&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt; voltage &amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;sensitivity analysis &amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt;with respect to the real power injected &amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;with&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt; renewable energies&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt; to determine the optimal integration of distributed generation (DG) in distribution systems (DS).&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt; &amp;lt;span lang="EN-US"&amp;gt;The best nodes where the power injections improve voltages magnitudes complying with the constraints are determined.&amp;lt;/span&amp;gt;&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt; As it is a combinatorial problem, p&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt;article swarm optimization (PSO) and simulated annealing (SA) were used to change injections from 10% to 60% of the total power load using solar and wind generators and find the candidate nodes for installing &amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;power &amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt;sources. The method was tested using the 33-node, 69-node and 118-node radial distribution networks. The results showed that the best nodes for injecting real power with renewable energies were selected for the distribution network&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt; by using the voltage sensitivity analysis&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt;. Algorithms found the best nodes for the three radial distribution &amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;networks&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt; with similar&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt; values in the maximum injection of real&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt; power&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;, suggesting that this value maintains for all the power system cases&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt;. The injections applied to the different nodes showed that voltage magnitudes increase significantly, especially when exceeding the maximum penetration of DG. The test showed that some nodes support injections up to the limits, but the voltages increase considerably on all nodes.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2019-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v9i1.pp55-65</dc:identifier><dc:identifier>10.11591/ijece.v9i1.pp55-65</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 9 No 1 (2019); 55</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/11246/11013</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>