Machine Learning in Energy Forecasts with an Application to High Frequency Electricity Consumption Data

Machine Learning in Energy Forecasts with an Application to High Frequency Electricity Consumption Data

Forecasting plays an essential role in energy economics. With new challenges and use cases in the energy system, forecasts have to meet more complex requirements, such as increasing temporal and spatial resolution of data. The concept of machine learning can meet these requirements by providing diff...

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I publikationen:MAGKS - Joint Discussion Paper Series in Economics (Band 35-2021)
Huvudupphovsmän: Heilmann, Erik, Henze, Janosch, Wetzel, Heike
Materialtyp: Artikel
Språk:engelska
Publicerad: Philipps-Universität Marburg 2021
Ämnen:
time series forecast
arti�cial neural network
electricity consumption forecast
machine learning
Wirtschaft
Economics
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MAGKS - Joint Discussion Paper Series in Economics

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