Fault-tolerant wide-area control for power oscillation damping
2012 IEEE Power and Energy Society General Meeting
In this paper, the effectiveness of using both local and remote (wide-area) feedback signals for power oscillation damping (POD) controllers is shown. However, the challenge is to guarantee a minimum level of dynamic performance with only the local signal following sudden loss of remote signals. A case study on the Nordic equivalent system is presented to show that the closed-loop response could deteriorate once the remote signals are lost. A fault-tolerant control (FTC) design methodology is
... esented to solve this problem and ensure an acceptable performance level even in case of loss of remote signals. The FTC design methodology is based on simultaneous pole-placement for normal and loss of (remote) signals conditions along with minimisation of control effort. The problem is solved non-iteratively using Linear Matrix Inequalities (LMIs). Under the normal condition (when both local and remote signals are present) the fault-tolerant controller (FTC) requires more control effort as compared to a conventional controller (CC) in order to achieve the same performance. However, case studies on the Nordic equivalent system confirm that the proposed FTC is able to produce acceptable performance in case of loss of the remote signals while the response with a CC is unacceptable. Index Terms-Power oscillation damping, fault-tolerant control, pole-placement, local and remote feedback Petr Korba received his MSc in electrical engineering from the Czech Technical University, Prague, Czech Republic, in 1995 and his PhD from the University of Duisburg, Germany, in 2000. He was an invited scientist at the Delft University of Technology, the Netherlands, and at the University of Manchester Institute of Science and Technology (UMIST) in 1998 and 1999, respectively. He became a member of staff at UMIST, Control Systems Centre, where he stayed until 2001. Since then he has been with ABB Switzerland Ltd. His interests include model identification techniques, robust and adaptive control theory and their industrial applications.