A Multifactorial Framework for Short-Term Load Forecasting System as Well as the Jinan’s Case Study

A Multifactorial Framework for Short-Term Load Forecasting System as Well as the Jinan’s Case Study

Accurate and reliable short-term electric load forecasting (STLF) plays a critical role in power system to enhance its routine management efficiency and reduce operational costs. However, most of the existing STLF methods suffer from lack of appropriate feature selection procedure. In this paper, a...

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Bibliographic Details
Main Authors: Ya Gao, Yong Fang, Huanhe Dong, Yuan Kong
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Short-term load forecasting
feature selection
partial mutual information
artificial neural network
Online Access:https://ieeexplore.ieee.org/document/9252094/

Internet

https://ieeexplore.ieee.org/document/9252094/

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