Power quality techniques research worldwide: A review
Francisco G. Montoya,
Amós García-Cruz,
Maria G. Montoya and
Francisco Manzano-Agugliaro
Renewable and Sustainable Energy Reviews, 2016, vol. 54, issue C, 846-856
Abstract:
In this study, a detailed analysis of research on the subject of power quality published during the period from 1970 to 2013 is presented; Elsevier׳s Scopus database was used as a reference, and bibliometric analysis techniques were employed. All materials reported in Scopus have been included. Different aspects of these publications have been studied, such as the publication type, subject, language, subcategories and journal type and the frequency with which the keywords were found. An analysis of the use of techniques such as heuristic optimisation, artificial intelligence and signal processing was also conducted within the framework of power quality. The keywords harmonics, active filter, voltage sag, distributed generation and wavelet transform were verified as the most commonly used terms other than the term power quality. The contributions were categorised geographically and by institution; China, USA and India were the main contributing countries, and the IEEE, the Indian Institute of Technology, and the North China Electric Power University were the main contributing research institutions. The most active categories in the fields of optimisation, artificial intelligence and signal processing were Genetic Algorithms and Particle Swarm Optimisation, Neural Network and Fuzzy Logic and Wavelet Transform and Fourier Analysis, respectively. This scientific publication analysis-based methodology presents new perspectives with respect to the research trends of the international scientific community.
Keywords: Bibliometric; Power quality; Scientometric; Computer science; Research trends (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (9)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:rensus:v:54:y:2016:i:c:p:846-856
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DOI: 10.1016/j.rser.2015.10.091
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