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Energy forecasting tools and services
Author(s) -
González Ordiano Jorge Á.,
Waczowicz Simon,
Hagenmeyer Veit,
Mikut Ralf
Publication year - 2017
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.1235
Subject(s) - renewable energy , smart grid , computer science , categorization , service (business) , data science , grid , demand forecasting , energy (signal processing) , environmental economics , operations research , engineering , business , artificial intelligence , marketing , economics , geometry , mathematics , electrical engineering , statistics
The increasing complexity of the power grid and the continuous integration of volatile renewable energy systems on all aspects of it have made more precise forecasts of both energy supply and demand necessary for the future Smart Grid. Yet, the ever increasing volume of tools and services makes it difficult for users (e.g., energy utility companies) and researchers to obtain even a general sense of what each tool or service offers. The present contribution provides an overview and categorization of several energy‐related forecasting tools and services (specifically for load and volatile renewable power), as well as general information regarding principles of time series, load, and volatile renewable power forecasting. WIREs Data Mining Knowl Discov 2018, 8:e1235. doi: 10.1002/widm.1235 This article is categorized under: Application Areas > Business and Industry Application Areas > Data Mining Software Tools Technologies > Prediction