A Combined Method for Short-Term Load Forecasting Considering the Characteristics of Components of Seasonal and Trend Decomposition Using Local Regression

In response to the complexity and high volatility of original load data affecting the accuracy of load forecasting, a combined method for short-term load forecasting considering the characteristics of components of seasonal and trend decomposition using local regression (STL) is proposed. The origin...

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Bibliografiske detaljer

Principais autores:	Sile Hu, Yuan Wang, Wenbin Cai, Yuan Yu, Chao Chen, Jiaqiang Yang, Yucan Zhao, Yuan Gao
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2024-03-01
Serier:	Applied Sciences
Fag:	short-term load forecasting seasonal and trend decomposition using local regression long and short-term memory network convolutional neural network Gaussian process regression
Online adgang:	https://www.mdpi.com/2076-3417/14/6/2286
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