Special Issue “Analysis for Power Quality Monitoring”

Juan-José González de-la-Rosa and Manuel Pérez-Donsión
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Juan-José González de-la-Rosa: Research Group PAIDI-TIC-168 in Computational Instrumentation and Industrial Electronics (ICEI), Higher Polytechnic School, University of Cádiz, Ramón Puyol Av., E-11202 Algeciras, Spain
Manuel Pérez-Donsión: Department of Electrical Engineering, ETSII, Campus de Lagoas-Marcosende, University of Vigo, E-36310 Vigo, Spain

Energies, 2020, vol. 13, issue 3, 1-6

Abstract: We are immersed in the so-called digital energy network, continuously introducing new technological advances for a better way of life. As a consequence, numerous emerging words are relevant to this point: Internet of Things (IoT), big data, smart cities, smart grid, industry 4.0, etc. To achieve this formidable goal, systems should work more efficiently, a fact that inevitably leads to power quality (PQ) assurance. Apart from its economic losses, a bad PQ implies serious risks for machines and, consequently, for people. Many researchers are endeavouring to develop new analysis techniques, instruments, measurement methods, and new indices and norms that match and fulfil the requirements regarding the current operation of the electrical network. This book, and its associated Special Issue, offer a compilation of some of the recent advances in this field. The chapters range from computing to technological implementation, going through event detection strategies and new indices and measurement methods that contribute significantly to the advance of PQ analysis and regulation. Experiments have been developed within the frameworks of research units and projects and deal with real data from industry practice and public buildings. Human beings have an unavoidable commitment to sustainability, which implies adapting PQ monitoring techniques to our dynamic world, defining a digital and smart concept of quality for electricity.

Keywords: power quality (PQ); PQ indices and thresholds; reliability; sensors and instruments for PQ; big data; machine learning; soft computing; statistical signal processing; data scalability; data compression (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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