Determining the Optimal Location and Number of Voltage Dip Monitoring Devices Using the Binary Bat Algorithm
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- Adarsh, B.R. & Raghunathan, T. & Jayabarathi, T. & Yang, Xin-She, 2016. "Economic dispatch using chaotic bat algorithm," Energy, Elsevier, vol. 96(C), pages 666-675.
- Haoyuan Sha & Fei Mei & Chenyu Zhang & Yi Pan & Jianyong Zheng, 2019. "Identification Method for Voltage Sags Based on K-means-Singular Value Decomposition and Least Squares Support Vector Machine," Energies, MDPI, vol. 12(6), pages 1-15, March.
- Ngo Minh Khoa & Le Van Dai, 2020. "Detection and Classification of Power Quality Disturbances in Power System Using Modified-Combination between the Stockwell Transform and Decision Tree Methods," Energies, MDPI, vol. 13(14), pages 1-30, July.
- Ferhat Ucar & Jose Cordova & Omer F. Alcin & Besir Dandil & Fikret Ata & Reza Arghandeh, 2019. "Bundle Extreme Learning Machine for Power Quality Analysis in Transmission Networks," Energies, MDPI, vol. 12(8), pages 1-26, April.
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- Michele Zanoni & Riccardo Chiumeo & Liliana Tenti & Massimo Volta, 2023. "What Else Do the Deep Learning Techniques Tell Us about Voltage Dips Validity? Regional-Level Assessments with the New QuEEN System Based on Real Network Configurations," Energies, MDPI, vol. 16(3), pages 1-24, January.
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Keywords
voltage dip; PQ monitor; monitor reach area matrix; binary bat algorithm;All these keywords.
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