SCD based IEC 61850 traffic estimation for substation automation networks

In Substation Automation System(SAS), communication network plays a critical role in the real time operation of the substation. IEC 61850 is a communication standard for SAS for the data transmission within and between station level, bay level and process level. The standard defines both the information model and the services used for communication between Intelligent Electronic Devices (IEDs) in a substation. The information model can be mapped to application protocols like MMS, GOOSE, SV of which GOOSE and SV messages are time critical and use Layer 2 of Open Systems Interconnection (OSI) model. IEC 61850 also defines substation configuration description (SCD), which embodies the substation model, the IED equipment model and the communication network model. With the increase in size and complexity of SAS network, it is desirable to properly segment multicast flows in order to avoid overloading at IEDs with unsubscribed messages. Knowledge of data flows and traffic patterns allow detecting network bottlenecks and aid in systematic network segmentation, filtering and segregation of the traffic. Hence there is a need to optimize the traffic segmentation and generate appropriate traffic filters which will be configured in network switch. Furthermore, by analyzing the application data and logical dataflow information present in the SCD file, it is possible to estimate the network bandwidth and flow latency. This would validate the network configuration for the fulfillment of the performance requirements based on the dataflow information in SCD file. So, there is a need to develop models that will estimate the GOOSE/SV traffic from the SCD file data. This paper proposes a method to optimally segment the Layer 2 network traffic and also a model to estimate GOOSE/SV traffic in SAS Network based on the information extracted from SCD file. This estimation would aid in analyzing the required network performance during the deployment and also better planning of SAS networks.