Autoregressive with Exogenous Variables and Neural Network Short-Term Load Forecast Models for Residential Low Voltage Distribution Networks

Autoregressive with Exogenous Variables and Neural Network Short-Term Load Forecast Models for Residential Low Voltage Distribution Networks

This paper set out to identify the significant variables which affect residential low voltage (LV) network demand and develop next day total energy use (NDTEU) and next day peak demand (NDPD) forecast models for each phase. The models were developed using both autoregressive integrated moving averag...

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Bibliographic Details
Main Authors: Christopher Bennett, Rodney A. Stewart, Junwei Lu
Format: Article
Language:English
Published: MDPI AG 2014-04-01
Series:Energies
Subjects:
forecast
electricity demand
residential
time series
autoregressive integrated moving average (ARIMA)
ARIMA with exogenous variables (ARIMAX)
neural network (NN)
Online Access:http://www.mdpi.com/1996-1073/7/5/2938

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