Short-Term Forecasting of Electric Loads Using Nonlinear Autoregressive Artificial Neural Networks with Exogenous Vector Inputs

Short-Term Forecasting of Electric Loads Using Nonlinear Autoregressive Artificial Neural Networks with Exogenous Vector Inputs

Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing...

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Bibliographic Details
Main Authors: Jaime Buitrago, Shihab Asfour
Format: Article
Language:English
Published: MDPI AG 2017-01-01
Series:Energies
Subjects:
short-term load forecasting
nonlinear autoregressive exogenous input
artificial neural networks
closed-loop forecasting
Online Access:http://www.mdpi.com/1996-1073/10/1/40

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