Modular Predictor for Day-Ahead Load Forecasting and Feature Selection for Different Hours
To improve the accuracy of the day-ahead load forecasting predictions of a single model, a novel modular parallel forecasting model with feature selection was proposed. First, load features were extracted from a historic load with a horizon from the previous 24 h to the previous 168 h considering th...
Main Authors: | Lin Lin, Lin Xue, Zhiqiang Hu, Nantian Huang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-07-01
|
Series: | Energies |
Subjects: | |
Online Access: | http://www.mdpi.com/1996-1073/11/7/1899 |
Similar Items
-
Day-Ahead Load Forecasting Using Exponential Smoothing
by: R. Bindiu, et al.
Published: (2009-12-01) -
Day-Ahead Forecast of Electrical Load Based on EMD-MLP Combination Model
by: Luyao LIU, et al.
Published: (2024-01-01) -
Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting
by: Zhengjie Li, et al.
Published: (2021-04-01) -
Adequacy of neural networks for wide-scale day-ahead load forecasts on buildings and distribution systems using smart meter data
by: Oleg Valgaev, et al.
Published: (2020-11-01) -
Day-Ahead Forecast of Photovoltaic Power Based on a Novel Stacking Ensemble Method
by: Luyao Liu, et al.
Published: (2023-01-01)