https://orcid.org/0000-0001-8657-3800
![Sample our Engineering & Technology journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5933/TOC-Subject-Sample-2021-Engineering-Tech.jpg"})
ABSTRACT
Clustering of electrical load curves is an important resource used in the analysis of Electric Power Systems, as it extracts characteristics from the behavior of the load. Real data of load curve presents outliers and acquisition problems that are not suitable for clustering. This research proposes a hybrid algorithm for load curve filtering and clustering. An iterative process using the Hampel filter and the Wavelet Transform was applied to filter the data from the load curve. Then, the dimensionality of the load curves was reduced, using the Wavelet Transform, followed by clustering performed with the k-means algorithm. The result of the filtering step demonstrated the effectiveness in correcting abnormalities present in the load curves, thus excluding the load curves with a predominance of abnormalities indicating failures in the measurement system. The clusters resulting from the dimensionality reduction method followed by clustering, originated load curves with well-defined typologies, as well as typical days and periods of the year, in addition to a reduced processing time. The entire methodology was applied using real data from a total of 2588 load curves discretized every 5 minutes.
Acknowledgments
The authors would like to acknowledge the Federal University of Piauí (Brazil) for the research facilities and the São Francisco Hydroelectric Company for the data provided to conduct this project. This research did not receive any specific grants from public, private or non-profit funding agencies.
This work is partially funded by FCT/MCTES through national funds and when applicable co-funded EU funds under the Project UIDB/50008/2020; and by Brazilian National Council for Scientific and Technological Development - CNPq, via Grant No. 313036/2020-9.
Disclosure statement
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Additional information
Funding
Notes on contributors
Juan A. Gonçalves
Juan de Aguiar Gonçalves is Graduated in Electrical Engineering from Universidade Estadual do Piauí (UESPI), Specialization in Electrical Engineering with Emphasis in Systems from Universidade Cândido Mendes and Master in Electrical Engineering from Universidade Federal do Piauí (UFPI). He is currently a professor at the State University of Piauí (UESPI), Coordinator of the Center for Training and Research in Renewable Energies of Piauí (NUFPERPI) and Leader of the Interdisciplinary Research Group on Renewable Energy and Social Technologies at UESPI (GIPERTS). He has experience in the area of Transmission, Power Generation and Analysis of Electrical Systems. His main interests involve Renewable Energies, Telecommunications, Energy Efficiency, Power Systems Analysis, Energy Planning, Protection of Electrical Systems and Computational Intelligence Applications in Electrical Systems.
André L. S. Pessoa
André Luis da Silva Pessoa has a degree in Electrical Engineering from the State University of Piauí (2015) and a master’s degree in Electrical Engineering from the University of São Paulo (2017). He has experience in the field of Electrical Engineering, with an emphasis on Electrical Power Systems, working mainly on the following topics: meta-heuristic optimization algorithms, machine learning algorithms, electrical power quality, fault location in distribution systems, electrical networks smart and micro-networks.
Ênio R. Viana
Ênio Rodrigues Viana is Bachelor of Computer Science. He has a specialization in Computer Forensic Expertise, is a specialist in Mobile Development with an emphasis on the Android platform. He holds a master’s degree in Electrical Engineering from the Federal University of Piauí. He has extensive experience as an IT Support Analyst. He acts as a full-stack web developer in freelance and freelance work. Expertises: C++, Artificial Intelligence, Genetic Algorithms, Multiobjective Optimization, PHP, CSS3, HTML5, Laravel Framework.
Hermes M. G. C. Branco
Hermes Manoel Galvão Castelo Branco is Professor at the Technology Center of the Federal University of Piauí, Teresina, Brazil. He received the B.Sc. degrees in Computer Science from the UFPI B.Sc. degrees in Electrical Engineering from the UNICEP, the M.Sc and the Ph.D. degree in Electrical Engineering from the University of São Paulo, São Paulo, in 2013. He has experience in application of computational intelligence in electrical power systems.
Joel J. P. C. Rodrigues
Joel J. P. C. Rodrigues [Fellow, IEEE] is a professor at the Federal University of Piauí, Brazil; and senior researcher at the Instituto de Telecomunicações, Portugal. Prof. Rodrigues is the leader of the Next-Generation Networks and Applications (NetGNA) research group (CNPq), an IEEE Distinguished Lecturer, Member Representative of the IEEE Communications Society on the IEEE Biometrics Council, and the President of the scientific council at ParkUrbis – Covilhã Science and Technology Park. He was Director for Conference Development - IEEE ComSoc Board of Governors, Technical Activities Committee Chair of the IEEE ComSoc Latin America Region Board, a Past-Chair of the IEEE ComSoc Technical Committee (TC) on eHealth and the TC on Communications Software, a Steering Committee member of the IEEE Life Sciences Technical Community and Publications cochair. He is the editor-in-chief of the International Journal of E-Health and Medical Communications and editorial board member of several high-reputed journals (mainly, from IEEE). He has been general chair and TPC Chair of many international conferences, including IEEE ICC, IEEE GLOBECOM, IEEE HEALTHCOM, and IEEE LatinCom. He has authored or coauthored about 1000 papers in refereed international journals and conferences, 3 books, 2 patents, and 1 ITU-T Recommendation. He had been awarded several Outstanding Leadership and Outstanding Service Awards by IEEE Communications Society and several best papers awards. Prof. Rodrigues is a member of the Internet Society, a senior member ACM, and Fellow of IEEE.
Ricardo de A. L. Rabêlo
Ricardo de Andrade Lira Rabelo is a Professor at the Federal University of Piauí, Teresina, Brazil. He received the B.Sc. degrees in Computer Science from the UFPI and the Ph.D. degree in Electrical Engineering from the University of São Paulo, São Paulo, in 2010. He has experience in the application of computational intelligence in Internet of Things and electrical power systems.