Please use this identifier to cite or link to this item:
Title: Expert system application for reactive power compensation in isolated electric power systems
Authors: Kirgizov, A. K.
Dmitriev, S. A.
Safaraliev, M. Kh.
Pavlyuchenko, D. A.
Ghulomzoda, A. H.
Ahyoev, J. S.
Issue Date: 2021
Publisher: Institute of Advanced Engineering and Science
Citation: Expert system application for reactive power compensation in isolated electric power systems / A. K. Kirgizov, S. A. Dmitriev, M. Kh. Safaraliev, et al. — DOI 10.11591/ijece.v11i5.pp3682-3691 // International Journal of Electrical and Computer Engineering. — 2021. — Vol. 11. — Iss. 5. — P. 3682-3691.
Abstract: Effective electricity use can be an option which enables to achieve significant economy while generating and transmitting of electricity. One of the most important things is to improve the electricity quality through reactive power correction up to optimum values. The current article presents the solution to compensate the reactive power in the distribution networks, in Gorno-Badakhshan Autonomous Oblast (GBAO) with the use of the advanced technologies based on the data collection within real time. The article describes the methodology of fuzzy logic application and bio-heuristic algorithms for the suggested solution effectiveness to be determined. Fuzzy logic application to specify the node priority for compensating devices based on the linguistic matrix power loss and voltage gives the possibility to the expert to take appropriate solutions for compensating devices installation location to be determined. The appropriate (correct) determination of the compensating devices installation location in the electric power system ensures the effective regulation of the reactive power with the least economic costs. Optimization problems related to the active power loss minimization are solved as well as the cost minimization with compensating devices to ensure the values tan(f) not exceeding 0.35 through reducing multi-objective problem to the single-objective one using linear convolution. © 2021 Institute of Advanced Engineering and Science. All rights reserved.
Keywords: EXPERTS
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85107269624
PURE ID: 22097635
ISSN: 20888708
DOI: 10.11591/ijece.v11i5.pp3682-3691
metadata.dc.description.sponsorship: The reported study was funded by RFBR, project number 19-38-90204.
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

Files in This Item:
File Description SizeFormat 
2-s2.0-85107269624.pdf923,88 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.