Brief Review on Identification, Categorization and Elimination of Power Quality Issues in a Microgrid Using Artificial Intelligent Techniques
Power quality is the manifestation of a disruption in the supply voltage, current or frequency that damages the utility equipment and has become an important issue with the introduction of more sophisticated and sensitive devices. So, the supply power quality issue still remains a major challenge as...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Universidade do Porto
2023-09-01
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| Series: | U.Porto Journal of Engineering |
| Subjects: | |
| Online Access: | https://journalengineering.fe.up.pt/index.php/upjeng/article/view/1388 |
| _version_ | 1797676976657399808 |
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| author | Amrit Pattnaik Prakash Kumar Hota Meera Viswavandya |
| author_facet | Amrit Pattnaik Prakash Kumar Hota Meera Viswavandya |
| author_sort | Amrit Pattnaik |
| collection | DOAJ |
| description | Power quality is the manifestation of a disruption in the supply voltage, current or frequency that damages the utility equipment and has become an important issue with the introduction of more sophisticated and sensitive devices. So, the supply power quality issue still remains a major challenge as its degradation can cause huge destabilization of electrical networks. As renewable energy sources have irregular nature, a microgrid essentially needs energy storage system containing advanced power electronic converters which is the root cause of majority of power quality disturbances. Also, the integration of non-linear and unbalanced loads into the grid adds to its power quality problems. This article gives a compact overview on the identification, categorization and mitigation of these power quality events in a microgrid by using various Artificial Intelligence-based techniques like Optimization techniques, Adaptive Learning techniques, Signal Processing and Pattern Recognition, Neural Networks and Fuzzy Logic. |
| first_indexed | 2024-03-11T22:38:14Z |
| format | Article |
| id | doaj.art-c3c175f9b30c461d87ec2815219fb884 |
| institution | Directory Open Access Journal |
| issn | 2183-6493 |
| language | English |
| last_indexed | 2024-03-11T22:38:14Z |
| publishDate | 2023-09-01 |
| publisher | Universidade do Porto |
| record_format | Article |
| series | U.Porto Journal of Engineering |
| spelling | doaj.art-c3c175f9b30c461d87ec2815219fb8842023-09-22T11:41:07ZengUniversidade do PortoU.Porto Journal of Engineering2183-64932023-09-0194205010.24840/2183-6493_009-004_0013881559Brief Review on Identification, Categorization and Elimination of Power Quality Issues in a Microgrid Using Artificial Intelligent TechniquesAmrit Pattnaik0https://orcid.org/0000-0002-5195-6083Prakash Kumar Hota1Meera Viswavandya2 Odisha University of Technology and Research, Department of Electrical EngineeringOdisha University of Technology and Research, Department of Electrical EngineeringVeer Surendra Sai University of Technology, Department of Electrical EngineeringPower quality is the manifestation of a disruption in the supply voltage, current or frequency that damages the utility equipment and has become an important issue with the introduction of more sophisticated and sensitive devices. So, the supply power quality issue still remains a major challenge as its degradation can cause huge destabilization of electrical networks. As renewable energy sources have irregular nature, a microgrid essentially needs energy storage system containing advanced power electronic converters which is the root cause of majority of power quality disturbances. Also, the integration of non-linear and unbalanced loads into the grid adds to its power quality problems. This article gives a compact overview on the identification, categorization and mitigation of these power quality events in a microgrid by using various Artificial Intelligence-based techniques like Optimization techniques, Adaptive Learning techniques, Signal Processing and Pattern Recognition, Neural Networks and Fuzzy Logic.https://journalengineering.fe.up.pt/index.php/upjeng/article/view/1388power qualitymicrogridsartificial intelligenceidentification and categorizationrenewable energy sourcesenergy storage systempower electronic convertersdistributed generation |
| spellingShingle | Amrit Pattnaik Prakash Kumar Hota Meera Viswavandya Brief Review on Identification, Categorization and Elimination of Power Quality Issues in a Microgrid Using Artificial Intelligent Techniques U.Porto Journal of Engineering power quality microgrids artificial intelligence identification and categorization renewable energy sources energy storage system power electronic converters distributed generation |
| title | Brief Review on Identification, Categorization and Elimination of Power Quality Issues in a Microgrid Using Artificial Intelligent Techniques |
| title_full | Brief Review on Identification, Categorization and Elimination of Power Quality Issues in a Microgrid Using Artificial Intelligent Techniques |
| title_fullStr | Brief Review on Identification, Categorization and Elimination of Power Quality Issues in a Microgrid Using Artificial Intelligent Techniques |
| title_full_unstemmed | Brief Review on Identification, Categorization and Elimination of Power Quality Issues in a Microgrid Using Artificial Intelligent Techniques |
| title_short | Brief Review on Identification, Categorization and Elimination of Power Quality Issues in a Microgrid Using Artificial Intelligent Techniques |
| title_sort | brief review on identification categorization and elimination of power quality issues in a microgrid using artificial intelligent techniques |
| topic | power quality microgrids artificial intelligence identification and categorization renewable energy sources energy storage system power electronic converters distributed generation |
| url | https://journalengineering.fe.up.pt/index.php/upjeng/article/view/1388 |
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