Ultra-Short-Term Load Forecasting for Customer-Level Integrated Energy Systems Based on Composite VTDS Models

A method is proposed to address the challenging issue of load prediction in user-level integrated energy systems (IESs) using a composite VTDS model. Firstly, an IES multi-dimensional load time series is decomposed into multiple intrinsic mode functions (IMFs) using variational mode decomposition (V...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Processes 2023-08, Vol.11 (8), p.2461
Hauptverfasser:	Lu, Tong, Hou, Sizu, Xu, Yan
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithms Analysis Artificial neural networks Carbon Case studies Clustering Comparative analysis Correlation analysis Data compression Decomposition Embedding Emissions Feature selection Forecasting Integrated energy systems Long short-term memory Methods Missing data Neural networks Noise reduction Optimization Particle swarm optimization Regression models Support vector machines Time series
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!