Abstract

Control of power systems relies on the availability and quality of sensor measurements. However, measurements are inevitably subjected to faults caused by sensor failure, broken or bad connections, bad communication, or malfunction of some hardware or software. These faults, in turn, may cause the failure of power system controllers and consequently, severe contingencies in the power system. to avoid such contingencies, this paper presents a sensor evaluation and (missing sensor) restoration scheme (SERS) by using auto-associative neural networks (auto encoders) and particle swarm optimization. based on the SERS, a missing-sensor-fault-tolerant control is developed for controlling a static synchronous series compensator (SSSC) connected to a power network. This missing-sensor fault-tolerant control (MSFTC) improves the reliability, maintainability, and survivability of the SSSC and the power network. the effectiveness of the MSFTC is demonstrated by a real-time implementation of an SSSC connected to the IEEE 10-machine 39-bus system on a Real Time Digital Simulator and TMS320C6701 digital signal processor platform. the proposed fault-tolerant control can be readily applied to many existing controllers in power systems. © 2009 IEEE.

Department(s)

Electrical and Computer Engineering

Comments

National Science Foundation, Grant ECS # 0524183

Keywords and Phrases

Auto-associative neural network; Fault-tolerant control; Flexible ac transmission system (FACTS) device; Missing sensor restoration; Particle swarm optimization (PSO); Real-time implementation; Static synchronous series compensator (SSSC)

International Standard Serial Number (ISSN)

0885-8977

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

23 Mar 2009

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