Visualization and Animation of State Estimation Performance

Visualization and Animation of State Estimation Performance...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
1 Visualization and Animation of State Estimation Performance A. P. Sakis Meliopoulos, George J. Cokkinides Georgia Institute of Technology Mike Ingram, Sandra Bell, Sherica Mathews Tennessee Valley Authority Abstract Reliable real time system “visibility” depends on a reliable and accurate state estimator. Present experience with state estimators indicates that its reliability is below expectations (an average of 5% non-convergent cases). The causes of this poor performance have been identified in earlier work by the authors and alternative robust state estimators have been proposed. For any state estimator, it is important to develop techniques for monitoring the performance of the state estimator and identification of potential problems such as bad sensors, consistent errors, modeling errors, etc. The paper presents visualization and animation methods that assist this process. It is demonstrated that bad data many times can be detected via visualization methods. The methodologies are demonstrated with a hybrid three-phase state estimator which addresses the issue of systematic errors from modeling and imbalance errors. This estimator is enhanced by visualization and animation methods that provide valuable information to users and system operators “at a glance”. The procedure and the visualization techniques are demonstrated on TVA’s 500 kV transmission system. 1. Introduction A reliable and accurate real time model of a power system is of paramount important for effective control and operation of the system. The real time visibility of the system is achieved with the use of the SCADA system and processing of the SCADA data via state estimators. The end result of this process is expected to be a reliable and accurate real time model of the system. The importance of this process has become abundantly clear during the August 14, 2003 blackout. Historically, the importance of this issue was recognized immediately after the 1965 blackout. Following the 1965 blackout, power system state estimators were implemented in the late 60s to achieve this objective. The initial implementation was based on single phase measurements and a power system model that is assumed to operate under single frequency, balanced conditions and symmetric system model. These assumptions are still prevalent today. The single frequency, balanced and symmetric system assumptions have simplified the implementation but have generated a disconnect between the model and the real time data, i.e. the model utilized generates biases. These biases have resulted in poor performance and several other practical problems [7]. The experience is that the State Estimation problem does not have 100% performance, i.e. there are cases and time periods that the SE algorithm will not converge. The state estimator can be drastically improved with GPS synchronized measurements. Specifically, recent technology of disturbance recorders introduced synchronized measurements. Synchronization is achieved
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 2
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 01/29/2011 for the course ENGR 52 taught by Professor Mcmillan during the Spring '10 term at Baylor Med.

Page1 / 8

Visualization and Animation of State Estimation Performance...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online