A quasi oppositional forensic based investigation algorithm for optimizing distributed generation placement and sizing in power distribution systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10257761" target="_blank" >RIV/61989100:27240/25:10257761 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27730/25:10257761
Result on the web
<a href="https://www.nature.com/articles/s41598-025-01378-4" target="_blank" >https://www.nature.com/articles/s41598-025-01378-4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-025-01378-4" target="_blank" >10.1038/s41598-025-01378-4</a>
Alternative languages
Result language
angličtina
Original language name
A quasi oppositional forensic based investigation algorithm for optimizing distributed generation placement and sizing in power distribution systems
Original language description
The optimal siting and sizing of DGs are vital for the efficient operation of both radial and microgrid distribution systems. From an operational perspective, minimizing real power loss, reducing voltage deviation, and improving voltage stability index are the three primary objectives considered in this study. This manuscript addresses these issues by proposing a novel quasi-oppositional forensic-based investigation (QOFBI) algorithm, an evolutionary meta-optimization technique designed to optimize the location and sizing of DGs under various operating conditions, while adhering to system constraints. The approach introduces a weighting factor-based multiobjective formulation, where optimal weighting factors are computed dynamically. This ensures a balanced approach to minimizing power loss, voltage deviation, and enhancing voltage stability. Extensive simulations were conducted on the IEEE 33-bus and IEEE 69-bus standard distribution systems, evaluating the impact of DG placement with varying power factors under operational constraints. The results demonstrate the superiority of the proposed approach in terms of faster convergence, reduced complexity, and improved performance compared to existing optimization methods. The QOFBI algorithm achieves a 94.44% reduction in active power loss, highlighting its robust performance across different operational scenarios. These findings underscore the potential of QOFBI as a highly effective tool for DG optimization in modern distribution systems, offering both operational efficiency and system reliability.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
<a href="/en/project/TN02000025" target="_blank" >TN02000025: National Centre for Energy II</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Scientific Reports
ISSN
2045-2322
e-ISSN
2045-2322
Volume of the periodical
15
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
34
Pages from-to
1-34
UT code for WoS article
001486830600037
EID of the result in the Scopus database
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