Symbolic Analysis Role in the Reliability and Availability of Power Systems

This article proposes a comprehensive prognostic procedure capable of preventing failures in electrical power systems based on the theory of parametric faults of analog circuits. In this sense, the integration of symbolic analysis software, programming platforms and graphical environments for dynamic analysis of multidomain systems plays a fundamental role. The most important steps to avoid catastrophic failures and organize maintenance operations are described, starting from the modeling of the system under test, passing through the Testability analysis, up to the development of classification algorithms. Therefore, the main objective is to propose a specific simulation procedure that exploits the interoperability of different tools to identify and classify the most important fault mechanisms on power lines and power transformers. Finally, the use of different classification algorithms is proposed to evaluate the effectiveness of the method. The obtained results show that the classification techniques based on machine learning algorithms allow results higher than 90% to be obtained in the case of power lines, while in the case of monitoring a power transformer the classification rate of 76% shows further possibilities of development.