Autors: Antonov, S. I., Swati Gade., Rahul Agrawal., Dipak Patil. Title: Optimal utilization of UPQC at different operating condition using TLBO Keywords: optimization; optimum VA loading; Power Quality; reactive po References Issue
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Цитирания (Citation/s):
1. Gade, S. and Agrawal, R., 2023. Optimal utilization of unified power quality conditioner using the JAYA optimization algorithm. Engineering Optimization, 55(1), pp.1-18, https://doi.org/10.1080/0305215X.2021.1978440 - 2023 - в издания, индексирани в Scopus или Web of Science
2. Gade, S., Agrawal, R. (2022). Optimal VA Loading of UPQC Using Rao-1 Algorithm. In: Mahajan, V., Chowdhury, A., Padhy, N.P., Lezama, F. (eds) Sustainable Technology and Advanced Computing in Electrical Engineering . Lecture Notes in Electrical Engineering, vol 939. Springer, Singapore. https://doi.org/10.1007/978-981-19-4364-5_73 - 2022 - в издания, индексирани в Scopus или Web of Science
3. Gade, S., & Agrawal, R. (2023). VA Loading Optimization of a Converter Using the Rao Algorithm for Maximum Utilization of the Unified Power Quality Conditioner. ECTI Transactions on Electrical Engineering, Electronics, and Communications, 21(1), 248573. https://doi.org/10.37936/ecti-eec.2023211.248573 - 2023 - в издания, индексирани в Scopus или Web of Science
4. S. Gade, R. Agrawal, R. Jha and D. Patil, "Optimal utilization of UPQC using Rao-2 Algorithm," 2023 World Conference on Communication & Computing (WCONF), RAIPUR, India, 2023, pp. 1-6, doi: 10.1109/WCONF58270.2023.10235231. - 2023 - в издания, индексирани в Scopus или Web of Science
5. Gade, S. and Agrawal, R., 2024. An Elitism-Based SAMP-JAYA Algorithm for Optimal VA Loading of Unified Power Quality Conditioner. In Artificial Intelligence Techniques in Power Systems Operations and Analysis (pp. 101-124). Auerbach Publications, ISBN: 9781003301820 - 2023 - в издания, индексирани в Scopus или Web of Science
6. Singh A.R., Dashtdar M., Bajaj M., Garmsiri R., Blazek V., Prokop L., Misak S., AI-enhanced power quality management in distribution systems: implementing a dual-phase UPQC control with adaptive neural networks and optimized PI controllers, ARTIFICIAL INTELLIGENCE REVIEW, ISSN: 0269-2821, SPRINGER, vol. 57, issue: 11, DOI: 10.1007/s10462-024-10959-0 - 2024 - в издания, индексирани в Scopus или Web of Science
Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus