Synchro-Waveforms (also known as time-synchronized waveform measurements) are a powerful new technology for monitoring and situational awareness of power systems. Synchro-Waveforms are obtained from a new class of smart grid sensors called Waveform Measurement Units (WMUs). WMUs provide precise time-synchronized voltage waveform and current waveform measurements in time-domain. They show the wave-shape of the voltage and current at very high resolutions. WMUs operate at very high reporting rates, such as at 256 samples per cycle, i.e., 15,360 recordings per second. This is much higher than the sampling rate of practically every other smart grid sensor, such as phasor measurement units. At such a high reporting rate, a WMU reports 7,962,624,000 data points per day. This is an overwhelming amount of data that requires high-performance computing to analyze. Further, WMUs use a global positioning system (GPS) clock to precisely synchronize the sampling of waveforms across different WMUs, enabling precise time synchronization of the reported synchro-waveforms. The availability of synchro-waveform measurements can significantly enhance our understanding and awareness about the status of the power electric grid than traditional measurements. Therefore, synchro-waveforms introduce a new era of power systems monitoring and situational awareness. Synchro-waveforms offer groundbreaking applications in 1) event detection and classification, 2) event location identification, 3) topology identification, 4) network parameter estimation 5) asset monitoring, 6) incipient faults detection, and more importantly 7) wildfire monitoring.
A novel way to study synchro-waveforms is through the new graphical concept, called synchronized Lissajous curve. The synchronized Lissajous curve is obtained by plotting the difference of two synchronized voltage waveforms versus the difference of two synchronized current waveforms. The synchronized Lissajous curve carries valuable and complementary information about the waveforms that are captured by WMUs during events and disturbances. As an example, consider the power distribution feeder in Figure 1. Suppose two WMUs are installed on this feeder, where WMU 1 is installed at the beginning of the feeder and WMU 2 is installed at the end of the feeder. Figure 2 shows the synchronized voltage waveform measurements and the current waveform measurements from WMU 1 and WMU 2 as well as the corresponding synchronized Lissajous curve during both the normal operating condition (blue) and also the event condition (red). Under normal operating conditions, the synchronized Lissajous curve is an ellipse shape; however, once the event occurs in the feeder, the Lissajous curve takes a very different shape, making the impact of the event clearly visible. Therefore, the changes in the shape of the synchronized Lissajous curve carries information about the type of the event, the location of the event, and other dynamics characteristics of the event.
- The Synchro-Waveforms Repository:
- Main contact: Dr. Milad Izadi,
- URL: https://www.synchrowaveforms.com
- Milad Izadi and Hamed Mohsenian-Rad, “Event Detection, Classification, and Location Identification with Synchro-Waveforms,” in Microgrids Optimal Operation of Independent Storage Systems in Energy and Reserve, Wiley, 2023 (The first book chapter on the topic of Synchro-Waveforms).
URL: https://ieeexplore.ieee.org/document/10477722 - Milad Izadi and Hamed Mohsenian-Rad,”A Synchronized Lissajous-based Method to Detect and Classify Events in Synchro-waveform Measurements in Power Distribution Networks,” in IEEE Trans. on Smart Grid, vol. 13, no. 3, pp. 2170-2184, May 2022.
URL: https://ieeexplore.ieee.org/document/9702755 - Zong-Jhen Ye, Milad Izadi, Mohammad Farajollahi, and Hamed Mohsenian-Rad, “A Remedy to Losing Time Synchronization at D-PMUs, H-PMUs, and WMUs in Event Location Identification in Power Distribution Systems,” in IEEE Trans. on Smart Grid, accepted for publication, May 2023.
URL: https://ieeexplore.ieee.org/document/10130079 - Xu, Z. Huang, X. Xie, and C. Li, “Synchronized waveforms– a frontier of data-based power system and apparatus monitoring, protection, and control,” IEEE Trans. on Power Delivery, vol. 37, no. 1, pp. 3–17, 2022.
URL: https://ieeexplore.ieee.org/document/9403991 - Milad Izadi and Hamed Mohsenian-Rad,”Characterizing Synchronized Lissajous Curves to Scrutinize Power Distribution Synchro-waveform Measurements,” in IEEE Trans. on Power Systems, vol. 36, no. 5, pp. 4880-4883, September 2021.
URL: https://ieeexplore.ieee.org/document/9442909 - Milad Izadi and Hamed Mohsenian-Rad, “Synchronous Waveform Measurements to Locate Transient Events and Incipient Faults in Power Distribution Networks,” in IEEE Trans. on Smart Grid, vol. 12, no. 5, pp. 4295-4307, September 2021 (The first journal paper on the topic of Synchro-Waveforms).
URL: https://ieeexplore.ieee.org/document/9432388
- IEEE SGSMA 2024 Panel, Washington DC, May 20-23, 2024
- Milad Izadi, Mirrasoul J. Mousavi, Jong Min Lim, and Hamed Mohsenian-Rad,”Data-Driven Event Location Identification Without Knowing Network Parameters Using Synchronized Electric-Field and Current Waveform Data,” in Proc. of the IEEE PES General Meeting, Denver, CO, July 2022.
URL: https://ieeexplore.ieee.org/document/9917233 - Blair and J. Costello, “Slipstream: High-Performance Lossless Compression for Streaming Synchronized Waveform Monitoring Data,” 2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA), Split, Croatia, 2022.
URL: https://ieeexplore.ieee.org/document/9805997 - Milad Izadi and Hamed Mohsenian-Rad, “A Synchronized Lissajous-based Approach to Achieve Situational Awareness Using Synchronized Waveform Measurements,” in Proc. of the IEEE PES General Meeting, Washington, DC, July 2021.
URL: https://ieeexplore.ieee.org/document/9637952 - Alvaro Furlani Bastos, S. Santoso, W. Freitas, and W. Xu, “SynchroWaveform measurement units and applications, ” in Proc. of the IEEE PES General Meeting, Atlanta, GA, Jul. 2019.
URL: https://ieeexplore.ieee.org/document/8973736 - Milad Izadi and Hamed Mohsenian-Rad, “Event Location Identification in Distribution Networks Using Waveform Measurement Units,” in Proc. of the IEEE PES Innovative Smart Grid Technologies Conference – Europe, The Hague, The Netherlands, October 2020.
URL: https://ieeexplore.ieee.org/document/9248804