EDITORIAL
Published on 06 Jan 2025
Editorial: Data-driven approaches for efficient smart grid systems
doi 10.3389/fenrg.2024.1536459
- 287 views
- Frontiers in Energy Research
- Smart Grids
- Research Topics
- Data-Driven Approaches for Efficient Smart Grid Systems
Data-Driven Approaches for Efficient Smart Grid Systems
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Articles
ORIGINAL RESEARCH
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Photovoltaic output prediction based on VMD disturbance feature extraction and WaveNet
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- 236 views
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A multi-task learning based line parameter identification method for medium-voltage distribution network
doi 10.3389/fenrg.2024.1485369
- 346 views
ORIGINAL RESEARCH
Published on 16 Oct 2024
A study of short-term wind power segmentation forecasting method considering weather on ramp segments
doi 10.3389/fenrg.2024.1474969
- 345 views
METHODS
Published on 11 Oct 2024
Bad data identification method considering the on-load tap changer model
doi 10.3389/fenrg.2024.1478834
- 227 views
ORIGINAL RESEARCH
Accepted on 05 Sep 2024
Optimal scheduling of the active distribution network with microgrids considering multi-timescale source-load forecasting
doi 10.3389/fenrg.2024.1419898
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Published on 22 Jul 2024
Short-term wind power prediction and uncertainty analysis based on VDM-TCN and EM-GMM
doi 10.3389/fenrg.2024.1404165
- 497 views
ORIGINAL RESEARCH
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A physical virtual multi-graph convolutional coordinated prediction method for spatio-temporal electricity loads integrating multi-dimensional information
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- 416 views
ORIGINAL RESEARCH
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Intelligent substation virtual circuit verification method combining knowledge graph and deep learning
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ORIGINAL RESEARCH
Published on 12 Jun 2024
Evaluation of electrical load demand forecasting using various machine learning algorithms
doi 10.3389/fenrg.2024.1408119
- 1,867 views
- 2 citations
ORIGINAL RESEARCH
Published on 10 Jun 2024
Ultra-short-term prediction of microgrid source load power considering weather characteristics and multivariate correlation
doi 10.3389/fenrg.2024.1409957
- 452 views
- 1 citation
ORIGINAL RESEARCH
Published on 04 Apr 2024
Optimal placement of distributed generation in power distribution system and evaluating the losses and voltage using machine learning algorithms
doi 10.3389/fenrg.2024.1378242
- 1,567 views
- 1 citation
Published in
Frontiers in Energy Research
- Smart Grids
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- 14kTopic views
- 9,216Article views
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