Improved Power System State Estimation by Selected Node Technique

Udupa, H. and Kamath, H. (2015) Improved Power System State Estimation by Selected Node Technique. British Journal of Mathematics & Computer Science, 5 (4). pp. 525-537. ISSN 22310851

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Abstract

The state estimator is integral part of any Energy Management System. First and foremost the state estimation must be executed followed by system control, tie-line control, economic dispatch, security analysis etc. Most importantly the system voltage controls and the tie-line power controls must be handled within milliseconds to a few seconds. Obviously, in order to meet the requirements, state estimator should be able to process the results very fast. Due to the kind of complexity associated with the power system it’s very difficult to carry out the estimation in very short time. The author, H.N. Udupa & Dr. H.R. Kamath [1,2] had suggested a new innovative method to solve this complex problem in desired time without compromising on the results accuracy. In the said new approach, State Estimations are computed at each Node level.
This paper presents a unique technique to carried-out the State Estimation at selected Node Areas instead of every Node Area. As the network is interconnected, by selecting suitable Node Area it is possible to estimate all the state variables of the system. The method of selecting the Node Area is detailed in this paper. A node/bus along with its connected nodes/buses is called “Node Area”. By computing the SE only at Selected Nodes reduces the complexity of the system and also results in huge cost saving. The Node Area level of state estimation technique is suitable for smart grid application. This paper presents the Node Area selection technique along with its computational time and comparison with the conventional Integrated State Estimation (ISE) and Node Level State estimation.`

Item Type: Article
Subjects: OA STM Library > Mathematical Science
Depositing User: Unnamed user with email support@oastmlibrary.com
Date Deposited: 09 Jun 2023 08:01
Last Modified: 05 Jun 2024 10:14
URI: http://geographical.openscholararchive.com/id/eprint/1046

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