A scoping review of deep neural networks for electric load forecasting
Abstract The increasing dependency on electricity and demand for renewable energy sources means that distributed system operators face new challenges in their grid. Accurate forecasts of electric load can solve these challenges. In recent years deep neural networks have become increasingly popular i...
Main Authors: | Nicolai Bo Vanting, Zheng Ma, Bo Nørregaard Jørgensen |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2021-09-01
|
Series: | Energy Informatics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s42162-021-00148-6 |
Similar Items
-
Electricity load forecasting using a deep neuralnetwork
by: Chawalit Jeenanunta
Published: (2019-03-01) -
The Application of Ontologies in Multi-Agent Systems in the Energy Sector: A Scoping Review
by: Zheng Ma, et al.
Published: (2019-08-01) -
Short-Term Load Forecasting of Natural Gas with Deep Neural Network Regression †
by: Gregory D. Merkel, et al.
Published: (2018-08-01) -
Multivariate Short-term Electricity Load Forecasting with Deep Learning and exogenous covariates
by: Oscar, Nordström
Published: (2021) -
Electric Vehicle Charging Load Forecasting: A Comparative Study of Deep Learning Approaches
by: Juncheng Zhu, et al.
Published: (2019-07-01)