Abstract

Each year, hundreds of kilometers of medium voltage power lines across the country are repaired or
replaced. In order to reduce the effects of failures of these lines and improve service quality, while ensuring service continuity, the study of their behavior is found necessary. In addition, existing medium voltage electrical energy transmission systems are increasingly exposed to numerous risks (accidental breakage, failure of a transformer, and unavailability of operating devices). These situations of failure represent the major concern of the operators of these networks (Sonelgaz), and the authorities. In this context a prediction of the reliability of these electrical networks has been sought. The reliability of the electrical power network has been modeled using a static Bayesian network. This made it possible to qualitatively and quantitatively analyze the electricity availability in the electrical network. Dynamic Bayesian Networks (RBD) are also used to assess the reliability of switches that have a dynamic behavior. The dynamic modeling presented in this paper is a function of time, something that has allowed forecasting
management of the energy distribution. Finally, an application on a section of medium voltage network in the locality of Souk-Ahras has been shown in order to validate the Bayesian model experimentally on the one hand, and on the other hand to show the efficiency of these tools in real-world applications alongside real-time operating systems such as the SCADA used by Sonelgaz.

Information

Item Type:	Conference
Divisions:	» Faculty of Science and Technology
ePrint ID:	1733
Date Deposited:	2019-05-10
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/1733

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