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Development of automatic intelligent system for on-line voltage security control of power systems


Tomin, N and Zhukov, A and Kurbatsky, V and Sidorov, D and Negnevitsky, M, Development of automatic intelligent system for on-line voltage security control of power systems, Proceedings from the 2017 IEEE Manchester PowerTech, 18-22 June 2017, Manchester, United Kingdom, pp. 674-781. ISBN 9781509042388 (2017) [Refereed Conference Paper]


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DOI: doi:10.1109/PTC.2017.7980922


The majority of recent large-scale blackouts have been caused by voltage instability. A prompt on-line assessment of voltage stability for preventive corrective control of electric power systems is one of the key objectives for Control centers. The use of classical approximation methods alone is complicated. Therefore, several modified methods combined with machine learning algorithms enabling security assessment in real time have been proposed over the last years. The paper presents an automatic intelligent system for on-line voltage security control, which is based on the model of decision trees Proximity Driven Streaming Random Forest (PDSRF). In this case, the combination of original properties of PDSRF and capabilities of L-index as a target vector makes it possible to provide the functions of dispatcher warning, localization of critical nodes, and ensure direct interaction with the security automation systems. The efficiency of the proposed system was demonstrated using various test schemes of IEEE.

Item Details

Item Type:Refereed Conference Paper
Keywords:power system, voltage security, control, random forest, security assessment, L-index.
Research Division:Engineering
Research Group:Control engineering, mechatronics and robotics
Research Field:Field robotics
Objective Division:Manufacturing
Objective Group:Machinery and equipment
Objective Field:Machinery and equipment not elsewhere classified
UTAS Author:Negnevitsky, M (Professor Michael Negnevitsky)
ID Code:124538
Year Published:2017
Deposited By:Engineering
Deposited On:2018-02-23
Last Modified:2018-06-18
Downloads:141 View Download Statistics

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