Functional Failure Probability Analysis Method of Dispatching Automation Master Station System Based on Logistic Regression Model

The dispatching automation master station system (DAMSS) is an important component of power grid, responsible for real-time monitoring and control of the power grid’s status. Its stability and reliability directly affect the safe operation of the power grid. Once the DAMSS experiences functional failures, it can pose significant safety risks and lead to serious power grid accidents. To address this issue, this paper proposes a functional failure probability analysis method of DAMSS based on logistic regression model. This method thoroughly analyzes the risk factors that may cause functional failure and establishes a logistic regression model capable of analyzing the functional failure probability. The model can make full use of the data information retained during the operation of DAMSS, using the status of risk factors as evidence input to the logistic regression model, and obtain the functional failure probability. Finally, a case study is conducted on a specific DAMSS to validate the effectiveness of the proposed method.