Frequency is one of the most important measurements of a power system and is widely used in power system analysis, operation, and control. Since power system is operated in a steady state for most of the time, the median frequency is significant in power system analysis and monitoring, such as extreme frequency analysis and tripped amount estimation whenever an event happens. Well down sampled, continuous system median frequency will not only improve the bulk power system situation awareness but also require less network bandwidth or storage space. When a significant perturbation occurs in an electrical power system, the frequency varies in terms of time and space. The dynamic frequency measurements from different parts of the system with accurate UTC time stamp helps to reconstruct an event and gives the operators a full picture of the disturbance. Last but not the least, data visualization tools based on the system median frequency and the dynamic event data can demonstrate the state of the power system in a human friendly way and help operators and auditors to analyze and investigate the event.
While the North American Electric Reliability Corporation (NERC) is collecting data via OSIsoft PI system from power companies, the low-resolution data is yet not enough for event analysis and investigation. Also, the lack of visualization tools makes it difficult for engineers to quickly locate the event and acquire the event information. This project is to develop the data down sampling system, stream the data to the PI system at Center for Ultra-Wide-Area Resilient Electric Energy Transmission Networks (ORNL) and build up the data pipeline between the PI system at NERC and the PI system at ORNL to transmit and visualize the data.