Reliability evaluation and dynamic update method for secondary system of smart substation based on Bayesian network
The real-time and accurate acquisition of reliability parameters for substation equipment is of great significance for the safe and stable operation of substations and power systems.To address the challenges of the complex secondary topology structure of smart substations and the difficulty in automatically assessing reliability,we establish a real-time reliability calculation model based on Bayesian networks,which realizes the accurate evaluation of the reliability of secondary equipment and systems.Firstly,based on the GOOSE network and physical network topology described in the SCD file,we build a Bayesian network that represents the information-physical system of the substation secondary circuit,depicting the coupling influence mechanism between the communication network and the GOOSE network.Then,through semantic analysis of alarm information,we propose a node state update mechanism based on equipment alarms.Finally,utilizing the bidirectional reasoning characteristics of Bayesian networks,we develop a comprehensive reliability dynamic update calculation method by considering posterior probabilities and reliability changes due to equipment aging.Case study shows that the proposed method can calculate the dynamic functional reliability of the system's information-physical coupling functions,correctly identify the impact scope of system maintenance and equipment failures,and realize the dynamic update of reliability parameters based on system alarm information.The proposed method is suitable for long-term reliability assessment.
reliabilityBayesian networkdynamic updatesmart substationcyber-physical system
万方数据
维普
