Works matching IS 17521416 AND DT 2024 AND VI 18 AND IP 4
Results: 10
A novel DC‐link voltage synchronous control with enhanced inertial capability for full‐scale power conversion wind turbine generators.
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- IET Renewable Power Generation (Wiley-Blackwell), 2024, v. 18, n. 4, p. 690, doi. 10.1049/rpg2.12936
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Optimal design and sizing of a hybrid energy system for water pumping applications.
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- IET Renewable Power Generation (Wiley-Blackwell), 2024, v. 18, n. 4, p. 706, doi. 10.1049/rpg2.12937
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Experimental validation of a low‐voltage regulator model—A case study of a Maltese low‐voltage feeder.
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- IET Renewable Power Generation (Wiley-Blackwell), 2024, v. 18, n. 4, p. 679, doi. 10.1049/rpg2.12933
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Multi‐agent protection scheme for microgrid using deep learning.
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- IET Renewable Power Generation (Wiley-Blackwell), 2024, v. 18, n. 4, p. 663, doi. 10.1049/rpg2.12929
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High step up DC–DC converter with low conduction losses and reduced switching losses.
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- IET Renewable Power Generation (Wiley-Blackwell), 2024, v. 18, n. 4, p. 654, doi. 10.1049/rpg2.12927
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Robust self‐adaptive fuzzy controller for load‐frequency control of islanded airport microgrids considering electric aircraft energy storage and demand response.
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- IET Renewable Power Generation (Wiley-Blackwell), 2024, v. 18, n. 4, p. 616, doi. 10.1049/rpg2.12926
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- Article
Multi‐timescale synergistic planning for flexible regulation of thermal power to support wind‐photovoltaic‐storage.
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- IET Renewable Power Generation (Wiley-Blackwell), 2024, v. 18, n. 4, p. 604, doi. 10.1049/rpg2.12925
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A comprehensive review on enhancing wind turbine applications with advanced SCADA data analytics and practical insights.
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- IET Renewable Power Generation (Wiley-Blackwell), 2024, v. 18, n. 4, p. 722, doi. 10.1049/rpg2.12920
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- Article
Stochastic unit commitment based on energy‐intensive loads participating in wind and solar power consumption.
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- IET Renewable Power Generation (Wiley-Blackwell), 2024, v. 18, n. 4, p. 589, doi. 10.1049/rpg2.12915
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A double‐layer neural network wind speed prediction framework based on training set segmentation and error correction.
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- IET Renewable Power Generation (Wiley-Blackwell), 2024, v. 18, n. 4, p. 571, doi. 10.1049/rpg2.12914
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- Article