Contributions to Power Grid System Analysis Based on Clustering Techniques
The topic addressed in this article is part of the current concerns of modernizing power systems by promoting and implementing the concept of smart grid(s). The concepts of smart metering, a smart home, and an electric car are developing simultaneously with the idea of a smart city by developing hig...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/4/1895 |
| _version_ | 1797618298087538688 |
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| author | Gheorghe Grigoraș Maria Simona Raboaca Catalin Dumitrescu Daniela Lucia Manea Traian Candin Mihaltan Violeta-Carolina Niculescu Bogdan Constantin Neagu |
| author_facet | Gheorghe Grigoraș Maria Simona Raboaca Catalin Dumitrescu Daniela Lucia Manea Traian Candin Mihaltan Violeta-Carolina Niculescu Bogdan Constantin Neagu |
| author_sort | Gheorghe Grigoraș |
| collection | DOAJ |
| description | The topic addressed in this article is part of the current concerns of modernizing power systems by promoting and implementing the concept of smart grid(s). The concepts of smart metering, a smart home, and an electric car are developing simultaneously with the idea of a smart city by developing high-performance electrical equipment and systems, telecommunications technologies, and computing and infrastructure based on artificial intelligence algorithms. The article presents contributions regarding the modeling of consumer classification and load profiling in electrical power networks and the efficiency of clustering techniques in their profiling as well as the simulation of the load of medium-voltage/low-voltage network distribution transformers to electricity meters. |
| first_indexed | 2024-03-11T08:11:07Z |
| format | Article |
| id | doaj.art-b0fe4f1993564a49b69f8c0426a84190 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T08:11:07Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-b0fe4f1993564a49b69f8c0426a841902023-11-16T23:07:35ZengMDPI AGSensors1424-82202023-02-01234189510.3390/s23041895Contributions to Power Grid System Analysis Based on Clustering TechniquesGheorghe Grigoraș0Maria Simona Raboaca1Catalin Dumitrescu2Daniela Lucia Manea3Traian Candin Mihaltan4Violeta-Carolina Niculescu5Bogdan Constantin Neagu6Department of Power Engineering, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, RomaniaNational Research and Development Institute for Cryogenic and Isotopic Technologies—ICSI Rm. Vâlcea, Uzinei Street, No. 4, P.O. Box 7 Râureni, 240050 Ramnicu Valcea, RomaniaDepartment Telematics and Electronics for Transports, University “Politehnica” of Bucharest, 060042 Bucharest, RomaniaFaculty of Civil Engineering, Technical University of Cluj-Napoca, Constantin Daicoviciu Street, No. 15, 400020 Cluj-Napoca, RomaniaFaculty of Building Services Engineering, Technical University of Cluj—Napoca, Bd. 21 Decembrie 1989, No. 128-130, 400604 Cluj-Napoca, RomaniaNational Research and Development Institute for Cryogenic and Isotopic Technologies—ICSI Rm. Vâlcea, Uzinei Street, No. 4, P.O. Box 7 Râureni, 240050 Ramnicu Valcea, RomaniaDepartment of Power Engineering, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, RomaniaThe topic addressed in this article is part of the current concerns of modernizing power systems by promoting and implementing the concept of smart grid(s). The concepts of smart metering, a smart home, and an electric car are developing simultaneously with the idea of a smart city by developing high-performance electrical equipment and systems, telecommunications technologies, and computing and infrastructure based on artificial intelligence algorithms. The article presents contributions regarding the modeling of consumer classification and load profiling in electrical power networks and the efficiency of clustering techniques in their profiling as well as the simulation of the load of medium-voltage/low-voltage network distribution transformers to electricity meters.https://www.mdpi.com/1424-8220/23/4/1895smart gridclustering techniquespattern clusteringpower distribution planningregression algorithms |
| spellingShingle | Gheorghe Grigoraș Maria Simona Raboaca Catalin Dumitrescu Daniela Lucia Manea Traian Candin Mihaltan Violeta-Carolina Niculescu Bogdan Constantin Neagu Contributions to Power Grid System Analysis Based on Clustering Techniques Sensors smart grid clustering techniques pattern clustering power distribution planning regression algorithms |
| title | Contributions to Power Grid System Analysis Based on Clustering Techniques |
| title_full | Contributions to Power Grid System Analysis Based on Clustering Techniques |
| title_fullStr | Contributions to Power Grid System Analysis Based on Clustering Techniques |
| title_full_unstemmed | Contributions to Power Grid System Analysis Based on Clustering Techniques |
| title_short | Contributions to Power Grid System Analysis Based on Clustering Techniques |
| title_sort | contributions to power grid system analysis based on clustering techniques |
| topic | smart grid clustering techniques pattern clustering power distribution planning regression algorithms |
| url | https://www.mdpi.com/1424-8220/23/4/1895 |
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