Clustering Analysis for Active and Reactive Energy Consumption Data Based on AMI Measurements
Electrical data analysis based on smart grids has become a fundamental tool used by electrical grid stakeholders to understand the energy consumption patterns of users, although many proposals in this area do not consider reactive energy as another source of useful information regarding distribution...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/1/221 |
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| author | Oscar A. Bustos-Brinez Javier Rosero Garcia |
| author_facet | Oscar A. Bustos-Brinez Javier Rosero Garcia |
| author_sort | Oscar A. Bustos-Brinez |
| collection | DOAJ |
| description | Electrical data analysis based on smart grids has become a fundamental tool used by electrical grid stakeholders to understand the energy consumption patterns of users, although many proposals in this area do not consider reactive energy as another source of useful information regarding distribution costs and threats to the grid. In this regard, the analysis of reactive energy patterns can become an extremely useful addition to existing electrical data analysis frameworks. This work shows the application of a series of clustering techniques over measurements of both active and reactive energy consumption measured for end users from the Colombian electrical network, including an analysis of the efficiency of the network measured by calculating the ratio of active energy to total consumption (power factor) per user. This allows a detailed characterization of users to be compiled, based on the identification of different active and reactive energy consumption behaviors, which could help grid operators to improve overall grid management and to increase the efficiency of their reactive energy compensation strategies. |
| format | Article |
| id | doaj-art-9cd5d326d2a9416b985fd69e16488c36 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-9cd5d326d2a9416b985fd69e16488c362025-01-10T13:17:27ZengMDPI AGEnergies1996-10732025-01-0118122110.3390/en18010221Clustering Analysis for Active and Reactive Energy Consumption Data Based on AMI MeasurementsOscar A. Bustos-Brinez0Javier Rosero Garcia1EM&D Research Group, Electrical and Electronics Engineering Department, Faculty of Engineering, Universidad Nacional de Colombia, Bogota 111321, ColombiaEM&D Research Group, Electrical and Electronics Engineering Department, Faculty of Engineering, Universidad Nacional de Colombia, Bogota 111321, ColombiaElectrical data analysis based on smart grids has become a fundamental tool used by electrical grid stakeholders to understand the energy consumption patterns of users, although many proposals in this area do not consider reactive energy as another source of useful information regarding distribution costs and threats to the grid. In this regard, the analysis of reactive energy patterns can become an extremely useful addition to existing electrical data analysis frameworks. This work shows the application of a series of clustering techniques over measurements of both active and reactive energy consumption measured for end users from the Colombian electrical network, including an analysis of the efficiency of the network measured by calculating the ratio of active energy to total consumption (power factor) per user. This allows a detailed characterization of users to be compiled, based on the identification of different active and reactive energy consumption behaviors, which could help grid operators to improve overall grid management and to increase the efficiency of their reactive energy compensation strategies.https://www.mdpi.com/1996-1073/18/1/221energy analyticsdata analysiselectrical grid managementreactive energypower factor |
| spellingShingle | Oscar A. Bustos-Brinez Javier Rosero Garcia Clustering Analysis for Active and Reactive Energy Consumption Data Based on AMI Measurements Energies energy analytics data analysis electrical grid management reactive energy power factor |
| title | Clustering Analysis for Active and Reactive Energy Consumption Data Based on AMI Measurements |
| title_full | Clustering Analysis for Active and Reactive Energy Consumption Data Based on AMI Measurements |
| title_fullStr | Clustering Analysis for Active and Reactive Energy Consumption Data Based on AMI Measurements |
| title_full_unstemmed | Clustering Analysis for Active and Reactive Energy Consumption Data Based on AMI Measurements |
| title_short | Clustering Analysis for Active and Reactive Energy Consumption Data Based on AMI Measurements |
| title_sort | clustering analysis for active and reactive energy consumption data based on ami measurements |
| topic | energy analytics data analysis electrical grid management reactive energy power factor |
| url | https://www.mdpi.com/1996-1073/18/1/221 |
| work_keys_str_mv | AT oscarabustosbrinez clusteringanalysisforactiveandreactiveenergyconsumptiondatabasedonamimeasurements AT javierroserogarcia clusteringanalysisforactiveandreactiveenergyconsumptiondatabasedonamimeasurements |