Evidence map›Paper›PMID 40000648›Full record

ArticleScientific reports2025

Developing a dynamic combined power quality index for assessing the performance of a nuclear facility.

Asmaa M Elsotohy, Mohammed Hamouda Ali, Ahmed S Adail, Ayman A Eisa, El-Said A Othman

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Asmaa M ElsotohyDepartment of Nuclear Safety and Radiological Emergencies, NCRRT, Egyptian Atomic Energy Authority, Cairo, Egypt. Asmaa.sotohy@eaea.org.eg.
Mohammed Hamouda AliDepartment of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo, Egypt.
Ahmed S AdailDepartment of Fuel Technology, Hot Laboratory Centre, Egyptian Atomic Energy Authority, Cairo, Egypt.
Ayman A EisaDepartment of Nuclear Safety and Radiological Emergencies, NCRRT, Egyptian Atomic Energy Authority, Cairo, Egypt.
El-Said A OthmanDepartment of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studying and evaluating the power quality (PQ) of an electrical network for nuclear installation is an important issue and a hot research topic for guaranteeing reliable and safe operation of sensitive electrical loads during this type of installation. As several PQ phenomena determine the overall PQ performance, analyzing PQ signals for evaluating the overall PQ is one of the major challenges for researchers in this field. Technically, voltage imbalance, current imbalance, voltage harmonic distortion, current harmonic distortion, and the power factor are five important PQ phenomena that judge the overall PQ performance of an electrical system. Multicriteria decision-making (MCDM) is used here as a methodology to identify a weighting for each PQ phenomenon. This paper proposes a power quality evaluation method for a nuclear research reactor (NRR) electrical network based on two MCDM. Methods the analytic hierarchy process (AHP) and criterion importance through inter-criteria correlation (CRITIC). A MATLAB/Simulink model for the NRR electrical system is presented, and then its validity and credibility are verified via measurements. In this study, different abnormal conditions are simulated in the NRR network to generate power quality disturbances, including a three-phase nonlinear load to simulate harmonics, an unbalanced load to simulate unbalance, and an inductive load to simulate the change in the power factor. The effectiveness and robustness of the proposed methodology are demonstrated through these different case studies. The results show that the obtained CPQI based on the dynamic weight approach allows for more accurate evaluations by adjusting the importance of various PQ phenomena depending on operational conditions and priorities. The main contribution of this paper is that a single compound power quality index (CPQI) was developed based on both the dynamic weights obtained from AHP-CRITIC methods and the results of the five PQ phenomena obtained under different abnormal conditions, considering the threshold level for each of these PQ phenomena. The analysis of the obtained results shows that this method accurately evaluates the overall PQ performance.

Indexed as

Compound power quality indexMCDMNuclear research reactorPower quality

Identifiers

PMID40000648
PMCPMC11861320

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.