The Power of Big Data and Data Analytics for AMI Data: A Case Study
In recent years, there has been a transformation in the value chain of different industrial sectors, like the electricity networks, with the appearance of smart grids. Currently, the underlying knowledge in raw data coming from numerous devices can mark a significant competitive advantage for utilit...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/11/3289 |
| _version_ | 1797565694066294784 |
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| author | Jenniffer Sidney Guerrero-Prado Wilfredo Alfonso-Morales Eduardo Caicedo-Bravo Benjamín Zayas-Pérez Alfredo Espinosa-Reza |
| author_facet | Jenniffer Sidney Guerrero-Prado Wilfredo Alfonso-Morales Eduardo Caicedo-Bravo Benjamín Zayas-Pérez Alfredo Espinosa-Reza |
| author_sort | Jenniffer Sidney Guerrero-Prado |
| collection | DOAJ |
| description | In recent years, there has been a transformation in the value chain of different industrial sectors, like the electricity networks, with the appearance of smart grids. Currently, the underlying knowledge in raw data coming from numerous devices can mark a significant competitive advantage for utilities. It is the case of the Advanced Metering Infrastructure (AMI). Such technology gets user consumption characteristics at levels of detail that were previously not possible. In this context, the terms big data and data analytics become relevant, which are tools that allow using large volumes of information and the generation of valuable knowledge from raw data that can support data-driven decisions for operating on the grid. This paper presents the results of the big data implementation and data analytics techniques in a case study with smart metering data from the city of London. Implemented big data and data analytic techniques to show how to understand user consumption patterns on a broader horizon, the relationships with seasonal variables identify behaviors related to specific events and atypical consumptions. This knowledge helps support decision making about improving demand response programs and, in general, the planning and operation of the Smart Grid. |
| first_indexed | 2024-03-10T19:16:39Z |
| format | Article |
| id | doaj.art-12f56d224b4740a08421f8413fda9a0a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T19:16:39Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-12f56d224b4740a08421f8413fda9a0a2023-11-20T03:19:11ZengMDPI AGSensors1424-82202020-06-012011328910.3390/s20113289The Power of Big Data and Data Analytics for AMI Data: A Case StudyJenniffer Sidney Guerrero-Prado0Wilfredo Alfonso-Morales1Eduardo Caicedo-Bravo2Benjamín Zayas-Pérez3Alfredo Espinosa-Reza4School of Electrical and Electronics Engineering, Universidad del Valle, Cali PC 760031, ColombiaSchool of Electrical and Electronics Engineering, Universidad del Valle, Cali PC 760031, ColombiaSchool of Electrical and Electronics Engineering, Universidad del Valle, Cali PC 760031, ColombiaIntegral Processes Management Department, Instituto Nacional de Electricidad y Energías Limpias, Cuernavaca PC 62490, MexicoIntegral Processes Management Department, Instituto Nacional de Electricidad y Energías Limpias, Cuernavaca PC 62490, MexicoIn recent years, there has been a transformation in the value chain of different industrial sectors, like the electricity networks, with the appearance of smart grids. Currently, the underlying knowledge in raw data coming from numerous devices can mark a significant competitive advantage for utilities. It is the case of the Advanced Metering Infrastructure (AMI). Such technology gets user consumption characteristics at levels of detail that were previously not possible. In this context, the terms big data and data analytics become relevant, which are tools that allow using large volumes of information and the generation of valuable knowledge from raw data that can support data-driven decisions for operating on the grid. This paper presents the results of the big data implementation and data analytics techniques in a case study with smart metering data from the city of London. Implemented big data and data analytic techniques to show how to understand user consumption patterns on a broader horizon, the relationships with seasonal variables identify behaviors related to specific events and atypical consumptions. This knowledge helps support decision making about improving demand response programs and, in general, the planning and operation of the Smart Grid.https://www.mdpi.com/1424-8220/20/11/3289AMIbig dataclusteringdata analyticsdata-driven decisionsload forecasting |
| spellingShingle | Jenniffer Sidney Guerrero-Prado Wilfredo Alfonso-Morales Eduardo Caicedo-Bravo Benjamín Zayas-Pérez Alfredo Espinosa-Reza The Power of Big Data and Data Analytics for AMI Data: A Case Study Sensors AMI big data clustering data analytics data-driven decisions load forecasting |
| title | The Power of Big Data and Data Analytics for AMI Data: A Case Study |
| title_full | The Power of Big Data and Data Analytics for AMI Data: A Case Study |
| title_fullStr | The Power of Big Data and Data Analytics for AMI Data: A Case Study |
| title_full_unstemmed | The Power of Big Data and Data Analytics for AMI Data: A Case Study |
| title_short | The Power of Big Data and Data Analytics for AMI Data: A Case Study |
| title_sort | power of big data and data analytics for ami data a case study |
| topic | AMI big data clustering data analytics data-driven decisions load forecasting |
| url | https://www.mdpi.com/1424-8220/20/11/3289 |
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