Power quality techniques research worldwide: A review

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.

[1]  M. M. Morcos,et al.  Artificial Intelligence and Advanced Mathematical Tools for Power Quality Applications: A Survey , 2001, IEEE Power Engineering Review.

[2]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[3]  Angelo Baggini,et al.  Handbook of Power Quality , 2008 .

[4]  Paulo F. Ribeiro,et al.  Trends, Challenges and Opportunities in Power Quality Research , 2010 .

[5]  Andrew Kusiak,et al.  Optimization of wind turbine energy and power factor with an evolutionary computation algorithm , 2010 .

[6]  Michel Meunier,et al.  Detection and measurement of power quality disturbances using wavelet transform , 2000 .

[7]  Joao P. S. Catalao,et al.  Comparative study of power converter topologies and control strategies for the harmonic performance of variable-speed wind turbine generator systems , 2011 .

[8]  Math Bollen What is power quality , 2003 .

[9]  Consolación Gil,et al.  Wind turbine selection for wind farm layout using multi-objective evolutionary algorithms , 2014, Expert Syst. Appl..

[10]  Consolación Gil,et al.  Scientific production of renewable energies worldwide: An overview , 2013 .

[11]  Lutz Bornmann,et al.  Does the h-index for ranking of scientists really work? , 2005, Scientometrics.

[12]  J. Burnham Scopus database: a review , 2006, Biomedical digital libraries.

[13]  Huan Yang,et al.  Topologies and control strategies of multi-functional grid-connected inverters for power quality enhancement: A comprehensive review , 2013 .

[14]  Mario Oleskovicz,et al.  Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks , 2009 .

[15]  Consolación Gil,et al.  Optimization methods applied to renewable and sustainable energy: A review , 2011 .

[16]  Francisco G. Montoya,et al.  The research on energy in spain: A scientometric approach , 2014 .

[17]  José A. Aguado,et al.  Rule-based classification of power quality disturbances using S-transform , 2012 .

[18]  Qian Qing-quan,et al.  Study of a new method for power system transients classification based on wavelet entropy and neural network , 2011 .

[19]  Wing-Hong Lau,et al.  Real-Time Power-Quality Monitoring With Hybrid Sinusoidal and Lifting Wavelet Compression Algorithm , 2012, IEEE Transactions on Power Delivery.

[20]  Jong-Beom Lee,et al.  A fuzzy-expert system for classifying power quality disturbances , 2004 .

[21]  Panagiotis G. Ipeirotis,et al.  Duplicate Record Detection: A Survey , 2007 .

[22]  Yuh-Shan Ho,et al.  A bibliometric and citation analysis of stroke-related research in Taiwan , 2007, Scientometrics.

[23]  Consolación Gil,et al.  Genetic algorithm for S-transform optimisation in the analysis and classification of electrical signal perturbations , 2013, Expert Syst. Appl..

[24]  O. Arikan,et al.  Power quality assessment of grid-connected wind farms considering regulations in turkey , 2009 .

[25]  Quetzalcoatl Hernandez-Escobedo,et al.  Is the wind a periodical phenomenon? The case of Mexico , 2011 .

[26]  Jan T. Bialasiewicz,et al.  Power-Electronic Systems for the Grid Integration of Renewable Energy Sources: A Survey , 2006, IEEE Transactions on Industrial Electronics.

[27]  Yuh-Shan Ho,et al.  Global stem cell research trend: Bibliometric analysis as a tool for mapping of trends from 1991 to 2006 , 2009, Scientometrics.

[28]  V G Kinhal,et al.  Performance Investigation of Neural-Network-Based Unified Power-Quality Conditioner , 2011, IEEE Transactions on Power Delivery.

[29]  M.M.A. Salama,et al.  Effect of new deregulation policy on power quality monitoring and mitigation techniques , 2001, 2001 IEEE/PES Transmission and Distribution Conference and Exposition. Developing New Perspectives (Cat. No.01CH37294).

[30]  Irene Yu-Hua Gu,et al.  Signal processing of power quality disturbances , 2006 .

[31]  Whei-Min Lin,et al.  Detection and Classification of Multiple Power-Quality Disturbances With Wavelet Multiclass SVM , 2008, IEEE Transactions on Power Delivery.

[32]  G. Panda,et al.  Power Quality Analysis Using S-Transform , 2002, IEEE Power Engineering Review.

[33]  Consolación Gil,et al.  Minimization of voltage deviation and power losses in power networks using Pareto optimization methods , 2010, Eng. Appl. Artif. Intell..

[34]  Rene de Jesus Romero-Troncoso,et al.  Techniques and methodologies for power quality analysis and disturbances classification in power systems: a review , 2011 .

[35]  Jinho Choi,et al.  Analysis of keyword networks in MIS research and implications for predicting knowledge evolution , 2011, Inf. Manag..

[36]  Walid G. Morsi,et al.  Power quality evaluation in smart grids considering modern distortion in electric power systems , 2011 .

[37]  Rajiv Kapoor,et al.  Classification of power quality events – A review , 2012 .

[38]  Julio Barros,et al.  Applications of wavelets in electric power quality: Voltage events , 2012 .

[39]  J. E. Hirsch,et al.  An index to quantify an individual's scientific research output , 2005, Proc. Natl. Acad. Sci. USA.

[40]  Q. Hernández-Escobedo,et al.  Wind energy resource in Northern Mexico , 2014 .

[41]  Maria Dolores Gil Montoya,et al.  Comparative analysis of power variables in high performance embedded and x86 architectures using GNU/Linux , 2011, Comput. Electr. Eng..

[42]  Thomas F. Wenisch,et al.  Power management of online data-intensive services , 2011, 2011 38th Annual International Symposium on Computer Architecture (ISCA).

[43]  Francisco G. Montoya,et al.  TÉCNICAS DE INVESTIGACIÓN EN CALIDAD ELÉCTRICA: VENTAJAS E INCONVENIENTES , 2012 .

[45]  Eduardo Cabal-Yepez,et al.  A Real-Time Smart Sensor for High-Resolution Frequency Estimation in Power Systems , 2009, Sensors.

[46]  Bijaya K. Panigrahi,et al.  Power Quality Disturbance Classification Using Fuzzy C-Means Algorithm and Adaptive Particle Swarm Optimization , 2009, IEEE Transactions on Industrial Electronics.

[47]  Meng-Hui Wang,et al.  A novel analytic method of power quality using extension genetic algorithm and wavelet transform , 2011, Expert Syst. Appl..

[48]  Zaida Chinchilla-Rodríguez,et al.  Coverage analysis of Scopus: A journal metric approach , 2007, Scientometrics.

[49]  Francisco G. Montoya,et al.  The research of water use in Spain , 2016 .