A Hybrid Short-Term Load Forecasting Approach for Individual Residential Customer

This article proposes a hybrid method (HM) to improve the accuracy of short-term individual residential load forecasting. The HM includes an ensemble model (EM), deep ensemble model (DEM), and thermal dynamic model expressed by resistance-capacitance (RC). The EM consists of three predictors of supp...

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Vydané v:	IEEE transactions on power delivery Ročník 38; číslo 1; s. 26 - 37
Hlavní autori:	Lin, Xin, Zamora, Ramon, Baguley, Craig A., Srivastava, Anurag K.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.02.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Air conditioning Algorithms Artificial neural networks Atmospheric modeling Back propagation networks Bayesian algorithm Bi-LSTM BPNN Data models Distributed generation Dynamic models Electrical loads Forecasting genetic algorithm Genetic algorithms GRNN hybrid method Illuminance Lighting Load Load modeling Neural networks Optimization Predictive models short-term residential load forecasting Support vector machines SVM thermal dynamic model trimmed algorithm
ISSN:	0885-8977, 1937-4208
On-line prístup:	Získať plný text
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