Automated Detection of Electric Energy Consumption Load Profile Patterns
Load profiles of energy consumption from smart meters are becoming more and more available, and the amount of data to analyse is huge. In order to automate this analysis, the application of state-of-the-art data mining techniques for time series analysis is reviewed. In particular, the use of dynami...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/15/6/2176 |
| _version_ | 1797446698003333120 |
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| author | Ignacio Benítez José-Luis Díez |
| author_facet | Ignacio Benítez José-Luis Díez |
| author_sort | Ignacio Benítez |
| collection | DOAJ |
| description | Load profiles of energy consumption from smart meters are becoming more and more available, and the amount of data to analyse is huge. In order to automate this analysis, the application of state-of-the-art data mining techniques for time series analysis is reviewed. In particular, the use of dynamic clustering techniques to obtain and visualise temporal patterns characterising the users of electrical energy is deeply studied. The performed review can be used as a guide for those interested in the automatic analysis and groups of behaviour detection within load profile databases. Additionally, a selection of dynamic clustering algorithms have been implemented and the performances compared using an available electric energy consumption load profile database. The results allow experts to easily evaluate how users consume energy, to assess trends and to predict future scenarios. |
| first_indexed | 2024-03-09T13:45:19Z |
| format | Article |
| id | doaj.art-86da6f3dc96e496b8d9b39b81544552c |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T13:45:19Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-86da6f3dc96e496b8d9b39b81544552c2023-11-30T21:02:02ZengMDPI AGEnergies1996-10732022-03-01156217610.3390/en15062176Automated Detection of Electric Energy Consumption Load Profile PatternsIgnacio Benítez0José-Luis Díez1Sustainability and Energy Efficiency Area, Fundación Valenciaport, Building III, Avda. Muelle del Túria s/n, 46023 Valencia, SpainInstituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, Camino de Vera s/n, 46023 Valencia, SpainLoad profiles of energy consumption from smart meters are becoming more and more available, and the amount of data to analyse is huge. In order to automate this analysis, the application of state-of-the-art data mining techniques for time series analysis is reviewed. In particular, the use of dynamic clustering techniques to obtain and visualise temporal patterns characterising the users of electrical energy is deeply studied. The performed review can be used as a guide for those interested in the automatic analysis and groups of behaviour detection within load profile databases. Additionally, a selection of dynamic clustering algorithms have been implemented and the performances compared using an available electric energy consumption load profile database. The results allow experts to easily evaluate how users consume energy, to assess trends and to predict future scenarios.https://www.mdpi.com/1996-1073/15/6/2176time series analysisdynamic clusteringuser load profiles |
| spellingShingle | Ignacio Benítez José-Luis Díez Automated Detection of Electric Energy Consumption Load Profile Patterns Energies time series analysis dynamic clustering user load profiles |
| title | Automated Detection of Electric Energy Consumption Load Profile Patterns |
| title_full | Automated Detection of Electric Energy Consumption Load Profile Patterns |
| title_fullStr | Automated Detection of Electric Energy Consumption Load Profile Patterns |
| title_full_unstemmed | Automated Detection of Electric Energy Consumption Load Profile Patterns |
| title_short | Automated Detection of Electric Energy Consumption Load Profile Patterns |
| title_sort | automated detection of electric energy consumption load profile patterns |
| topic | time series analysis dynamic clustering user load profiles |
| url | https://www.mdpi.com/1996-1073/15/6/2176 |
| work_keys_str_mv | AT ignaciobenitez automateddetectionofelectricenergyconsumptionloadprofilepatterns AT joseluisdiez automateddetectionofelectricenergyconsumptionloadprofilepatterns |