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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Vydáno v:	Energies (Basel) Ročník 7; číslo 5; s. 2938 - 2960
Hlavní autoři:	Bennett, Christopher, Stewart, Rodney, Lu, Junwei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 2014
Témata:	Accuracy ARIMA with exogenous variables (ARIMAX) autoregressive integrated moving average (ARIMA) Capital expenditures Control algorithms Customers Demand Electricity electricity demand Energy management Energy storage forecast Load Low voltage Mathematical models Networks neural network (NN) Neural networks Relative humidity Residential Scheduling Time series Variables Queensland Australia Australia
ISSN:	1996-1073, 1996-1073
On-line přístup:	Získat plný text
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