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Comparative analysis of optimal power flow in renewable energy sources based microgrids

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 13 No. 2 (2023)

DOI
10.11591/ijece.v13i2.pp1241-1259
ISSN
2722-2578, 2088-8708
Published
2023-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Adaptation of renewable energy is inevitable. The idea of microgrid offers integration of renewable energy sources with conventional power generation sources. In this research, an operative approach was proposed for microgrids comprising of four different power generation sources. The microgrid is a way that mixes energy locally and empowers the end-users to add useful power to the network. IEEE-14 bus system-based microgrid was developed in MATLAB/Simulink to demonstrate the optimal power flow. Two cases of battery charging and discharging were also simulated to evaluate its realization. The solution of power flow analysis was obtained from the Newton–Raphson method and particle swarm optimization method. A comparison was drawn between these methods for the proposed model of the microgrid on the basis of transmission line losses and voltage profile. Transmission line losses are reduced to about 17% in the case of battery charging and 19 to 20% in the case of battery discharging when system was analyzed with the particle swarm optimization. Particle swarm optimization was found more promising for the deliverance of optimal power flow in the renewable energy sources-based microgrid.

Collaboration network of the authors

9 authors · 21 co-authorship links · 5 across different organisations

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  • University of Lahore
  • University of Skövde
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Rabia ArshadUniversity of Lahore1
Saba MehmoodUniversity of Lahore1
Danista KhanUniversity of Lahore1

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 27 Okt 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>Comparative analysis of optimal power flow in renewable energy sources based microgrids</dc:title><dc:creator>Muzzammel, Raheel</dc:creator><dc:creator>Arshad, Rabia</dc:creator><dc:creator>Bashir, Sobia</dc:creator><dc:creator>Mushtaq, Uzma</dc:creator><dc:creator>Durrani, Fariha</dc:creator><dc:creator>Noshin, Sadaf</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span lang="EN-US"&amp;gt;Adaptation of renewable energy is inevitable. The idea of microgrid offers integration of renewable energy sources with conventional power generation sources. In this research, an operative approach was proposed for microgrids comprising of four different power generation sources. The microgrid is a way that mixes energy locally and empowers the end-users to add useful power to the network. IEEE-14 bus system-based microgrid was developed in MATLAB/Simulink to demonstrate the optimal power flow. Two cases of battery charging and discharging were also simulated to evaluate its realization. The solution of power flow analysis was obtained from the Newton–Raphson method and particle swarm optimization method. A comparison was drawn between these methods for the proposed model of the microgrid on the basis of transmission line losses and voltage profile. Transmission line losses are reduced to about 17% in the case of battery charging and 19 to 20% in the case of battery discharging when system was analyzed with the particle swarm optimization. Particle swarm optimization was found more promising for the deliverance of optimal power flow in the renewable energy sources-based microgrid.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2023-04-01</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.v13i2.pp1241-1259</dc:identifier><dc:identifier>10.11591/ijece.v13i2.pp1241-1259</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 13 No 2 (2023); 1241</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/25864/16324</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>