DEVELOPMENT OF A CASE-BASED TRAINING SIMULATOR FOR POWER SYSTEM RESTORATION
Date
1999
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
ORCID
Type
Degree Level
Masters
Abstract
Due to the continued improvement of the reliability of power system components, electric power blackout has become a rare phenomenon in a modern power system. However, major faults and catastrophic events may lead to the collapse of an entire system. A power company would face huge financial and consequential losses as a result of a power blackout. It is essential to have a speedy restoration to minimize such losses. System operators gain little or no experience on restoration from their daily operation. System operators, therefore, should be trained to handle the complex operations involved in system restoration.
A case-based expert system has been developed to train and familiarize system operators with various steps involved in a restoration process.
A user friendly and straightforward case-based reasoning algorithm has been proposed to solve the problems of conventional rule-based algorithms. This expert system has been applied to restore a part of the Saskatchewan Power network from simulated blackout events. A user accessible, knowledge database has been developed based on previous experiences. Various mathematical analyses have been used to verify the risk of a proposed solution. A case adaptation process has been developed based on the system symmetry and its configuration. An object-oriented graphical user interface has been developed to communicate with the expert system. Various Windows° resources have been utilized to make the expert system user friendly. With this graphical user interface, a user can simulate a blackout event and the expert system then proposes a solution after consultation with the knowledge database. In its way to propose a solution the graphical user interface explains ongoing reasoning activities and creates an interactive environment. With a user accessible knowledge database, a user can apply his/her own knowledge and can ensure better participation in training sessions.
Description
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Citation
Degree
Master of Science (M.Sc.)
Department
Electrical and Computer Engineering
Program
Electrical Engineering