Temporary Variables for Predicting Electricity Consumption Through Data Mining
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Authors
Silva, JesúsSenior Naveda, Alexa
Hernández Palma, Hugo
Niebles Núẽz, William
Niebles Núẽz, Leonardo
Issue Date
2020-01-07Keywords
Data miningElectric power transmission networks
Electric power utilization
Forecasting
Electricity grids
Electricity-consumption
Intelligent distribution networks
Prediction systems
Real-time collection
Short term
Smart grid
Time variable
Metadata
Show full item recordPublisher
Institute of Physics PublishingJournal
Journal of Physics: Conference SeriesDOI
10.1088/1742-6596/1432/1/012033Abstract
In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids allows real-time collection of data on the operating status of the electricity grid. Based on this availability of data, it is feasible and convenient to predict consumption in the short term, from a few hours to a week. The hypothesis of the study is that the method used to present time variables to a prediction system of electricity consumption affects the results.Type
info:eu-repo/semantics/articleRights
info:eu-repo/semantics/openAccessAttribution-NonCommercial-ShareAlike 4.0 International
Language
engISSN
17426588EISSN
17426596ae974a485f413a2113503eed53cd6c53
10.1088/1742-6596/1432/1/012033
Scopus Count
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The following license files are associated with this item:
- Creative Commons
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