Multihousehold Load Forecasting Based on a Convolutional Neural Network Using Moment Information and Data Augmentation

Multihousehold Load Forecasting Based on a Convolutional Neural Network Using Moment Information and Data Augmentation

Deep learning (DL) networks are a popular choice for short-term load forecasting (STLF) in the residential sector. Hybrid DL methodologies based on convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) have a higher forecasting accuracy than conventional statistical STLF t...

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Bibliographic Details
Main Authors: Shree Krishna Acharya, Hwanuk Yu, Young-Min Wi, Jaehee Lee
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Energies
Subjects:
multihousehold load forecasting
collective moment measure (CMM)
convolutional neural network (CNN)
data augmentation
shifting variance
Online Access:https://www.mdpi.com/1996-1073/17/4/902

Internet

https://www.mdpi.com/1996-1073/17/4/902

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