Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/72514
Title: Centralized control of load-tap-changing transforms using neural networks
Authors: Huang, J.S.
Negnevitsky, M.
Chang, C.S. 
Liew, A.C. 
Issue Date: 2000
Source: Huang, J.S.,Negnevitsky, M.,Chang, C.S.,Liew, A.C. (2000). Centralized control of load-tap-changing transforms using neural networks. Proceedings of the World Congress on Intelligent Control and Automation (WCICA) 2 : 925-930. ScholarBank@NUS Repository.
Abstract: The paper presents a neural network based centralized control scheme for load tap-changing transformers. To implement the coordinated tap adjustment, the developed scheme employs successive linearization techniques to evaluate the interactions among different trnasformers represmted by a sensitivity matrix. Through updating the matrix using neural network methods, only the local information associated with the participating transformers is desired to perform the centralized tap control. The developed scheme has been verified to be superior to conventional decentralized methods in terms of avoiding unnecessary dynamics and enhancing voltage stability of power systems.
Source Title: Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
URI: http://scholarbank.nus.edu.sg/handle/10635/72514
Appears in Collections:Staff Publications

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