{"title":"Hybrid algorithm for directly detecting and classification of multiple power quality disturbances","authors":"Cagri Altintasi","doi":"10.1016/j.epsr.2025.111428","DOIUrl":null,"url":null,"abstract":"<div><div>Detecting potential power quality (PQ) events that may occur in the network is an important issue to provide safe electricity to customers. In this study, a new hybrid algorithm named adaptive fitness distance balance hybrid artificial hummingbird algorithm-artificial rabbit optimization (AFDB-AHAARO) algorithm is introduced for the detection and classification of PQ events. A hybrid algorithm is developed to improve the early convergence of the AHA algorithm by expanding the search to avoid local minima. The proposed method, unlike the optimization algorithms used in the literature, is directly applied to the detection and classification of PQ events. The performance of the proposed algorithm is investigated by 6000 different single and multiple PQ events in the Matlab in noisy and noiseless environments, considering the IEEE-1159 standards. The obtained results are compared with the AHA algorithm and the methods proposed in the literature, and it is shown that the proposed method outperforms in noisy environments. It also provides information about the time interval of PQ events. The validity of the proposed algorithm in real systems is demonstrated by testing it on the voltage signal with flicker disturbance obtained from the electrical network and on experimentally generated sag and swell events.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"242 ","pages":"Article 111428"},"PeriodicalIF":3.3000,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electric Power Systems Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378779625000215","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Detecting potential power quality (PQ) events that may occur in the network is an important issue to provide safe electricity to customers. In this study, a new hybrid algorithm named adaptive fitness distance balance hybrid artificial hummingbird algorithm-artificial rabbit optimization (AFDB-AHAARO) algorithm is introduced for the detection and classification of PQ events. A hybrid algorithm is developed to improve the early convergence of the AHA algorithm by expanding the search to avoid local minima. The proposed method, unlike the optimization algorithms used in the literature, is directly applied to the detection and classification of PQ events. The performance of the proposed algorithm is investigated by 6000 different single and multiple PQ events in the Matlab in noisy and noiseless environments, considering the IEEE-1159 standards. The obtained results are compared with the AHA algorithm and the methods proposed in the literature, and it is shown that the proposed method outperforms in noisy environments. It also provides information about the time interval of PQ events. The validity of the proposed algorithm in real systems is demonstrated by testing it on the voltage signal with flicker disturbance obtained from the electrical network and on experimentally generated sag and swell events.
期刊介绍:
Electric Power Systems Research is an international medium for the publication of original papers concerned with the generation, transmission, distribution and utilization of electrical energy. The journal aims at presenting important results of work in this field, whether in the form of applied research, development of new procedures or components, orginal application of existing knowledge or new designapproaches. The scope of Electric Power Systems Research is broad, encompassing all aspects of electric power systems. The following list of topics is not intended to be exhaustive, but rather to indicate topics that fall within the journal purview.
• Generation techniques ranging from advances in conventional electromechanical methods, through nuclear power generation, to renewable energy generation.
• Transmission, spanning the broad area from UHV (ac and dc) to network operation and protection, line routing and design.
• Substation work: equipment design, protection and control systems.
• Distribution techniques, equipment development, and smart grids.
• The utilization area from energy efficiency to distributed load levelling techniques.
• Systems studies including control techniques, planning, optimization methods, stability, security assessment and insulation coordination.