Day Ahead Electric Load Forecast: A Comprehensive LSTM-EMD Methodology and Several Diverse Case Studies
Optimal behind-the-meter energy management often requires a day-ahead electric load forecast capable of learning non-linear and non-stationary patterns, due to the spatial disaggregation of loads and concept drift associated with time-varying physics and behavior. There are many promising machine le...
Main Authors: | Michael Wood, Emanuele Ogliari, Alfredo Nespoli, Travis Simpkins, Sonia Leva |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-03-01
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Series: | Forecasting |
Subjects: | |
Online Access: | https://www.mdpi.com/2571-9394/5/1/16 |
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