CPOW Analysis: Data processing techniques for extracting insights from continuous point-on-wave measurements


Date: Monday, May 23                              Time: 3:00 pm – 6:00 pm (CEST)


Name of the organizer: Alexandra von Meier

Email: vonmeier@berkeley.edu

Short biography of the chair: Sascha von Meier is an Adjunct Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, and Director of the Electric Grid Research program at the California Institute for Energy and Environment. She is also a Faculty Scientist at the Lawrence Berkeley National Laboratory. Her research focuses on advanced measurements, data analytics and control strategies in electric grids to support resilience and the decarbonization of the energy sector.

Abstract: This online only workshop will introduce techniques and tools for analyzing continuous point-on-wave (CPOW) measurements from electric grid sensors, on the PredictiveGrid platform. After a general introduction to CPOW data, participants will have the opportunity to work hands-on in applying algorithms to CPOW data sets consisting of field measurements of primary and/or secondary distribution system voltages. Breakout rooms will focus on specific topic areas including oscillation detection, waveform/harmonic analysis, and multi-resolution data, allowing small groups to work together on coding challenges.


Part 1:

Name of the speakers: Sascha von Meier and Laurel Dunn

Short biography:

Sascha von Meier is an Adjunct Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, and Director of the Electric Grid Research program at the California Institute for Energy and Environment. She is also a Faculty Scientist at the Lawrence Berkeley National Laboratory. Her research focuses on advanced measurements, data analytics and control strategies in electric grids to support resilience and the decarbonization of the energy sector.

Laurel Dunn is a project manager leading PingThings ARPA-E project A National Infrastructure for AI on the Grid. She received her engineering PhD at the University of California, Berkeley where she specialized in data-driven decision analysis for utilities. She specializes in bridging interdisciplinary perspectives and areas of expertise to advance the use of big data and AI/ML tools for grid modernization.

Title of presentation: Introduction to continuous point-on-wave measurement (40 min)

Abstract: Much of the sensing instrumentation on the grid reports phasors or time-averaged values which are often derived from higher frequency measurements. These raw waveform data include information that is lost in aggregation. This portion of the tutorial will examine the information contents of CPOW data compared with other data streams, motivating the need for more widespread collection and analysis of CPOW data. We will also discuss computational challenges and requirements for processing this volume of data.


Part 2:

Name of the speakers: Mohini Bariya and Theo Laughner

Short biography:
Mohini Bariya leads the data & applications team at PingThings. Her work focuses on the use of novel, high-resolution measurements for improved situational awareness in the electric grid. She has worked extensively with real PMU datasets and has also taught science and engineering concepts to different audiences. She holds a PhD in electrical engineering and computer science from UC Berkeley.

Theo Laughner is the Director of Engineering at Lifescale Analytics.  Previously, Mr. Laughner spent 21 years at TVA where he was responsible for the Power Quality program at TVA.  He has a passion for helping utilities and their stakeholder maximize investment in data for the contemporary grid.  Cyber security and data analytics are at the center of this focus.  Mr. Laughner is a registered professional engineer in the state of Tennessee.

Title of presentation: Applications and data analysis techniques (60 min)

Abstract: This portion of the course will cover data processing techniques relevant to extracting different types of insights from CPOW data. Analytical methods focus on extracting features of the data (such as the power density, or fault analysis) to characterize dynamics that would not be evidenced by low-frequency sensor telemetry streams. These methods offer a foundation for data exploration and synthesis aimed at drawing attention to time-intervals where relevant dynamics are present, and provide a basis for targeting downstream workflows to diagnose and address possible issues.


Part 3:

Name of the speakers: Laurel Dunn

Short biography: Laurel Dunn is a project manager leading PingThings ARPA-E project A National Infrastructure for AI on the Grid. She received her engineering PhD at the University of California, Berkeley where she specialized in data-driven decision analysis for utilities. She specializes in bridging interdisciplinary perspectives and areas of expertise to advance the use of big data and AI/ML tools for grid modernization.

Title of presentation: : Coding challenge: Exploratory data analysis and visualization (60 min)

Abstract: This portion of the tutorial will include guided data analysis exercises designed to give attendees the experience of working with point-on-wave data. Presenters will disseminate data and code necessary to replicate analytics described earlier in the session. This portion of the tutorial will include a series of breakout room sessions targeted at building familiarity with point-on-wave workflows needed to develop exploratory data analysis workflows of their own.


Part 4:

Title of presentation: Conclusion, discuss interim results (20 min)

Abstract: The workshop will culminate with attendees and panelists re-grouping to discuss highlights and challenges associated with processing


 

Presenters:

Sascha von Meier is an Adjunct Professor in the Department of Electrical Engineering and
Computer Science at the University of California, Berkeley, and Director of the Electric Grid
Research program at the California Institute for Energy and Environment. She is also a Faculty
Scientist at the Lawrence Berkeley National Laboratory. Her research focuses on advanced
measurements, data analytics and control strategies in electric grids to support resilience and the
decarbonization of the energy sector.

Laurel Dunn is a project manager leading PingThings ARPA-E project A National
Infrastructure for AI on the Grid. She received her engineering PhD at the University of
California, Berkeley where she specialized in data-driven decision analysis for utilities. She
specializes in building bridges between stakeholders across the industry to advance the use of big
data and AI/ML tools for grid modernization.

Mohini Bariya is a data scientist at PingThings. Her work focuses on the use of novel,
high-resolution measurements for improved situational awareness in the electric grid. She has
worked extensively with real PMU datasets. She has experience teaching science and
engineering concepts to different audiences, including as a graduate student instructor for the
Electric Power Systems course at UC Berkeley.

Miles Rusch is a PhD student in Electrical Engineering at UC Berkeley. His research involves
high-resolution measurements using unsupervised learning algorithms to perform data analysis
on electric power systems.

Theo Laughner is the Director of Engineering at Life Scale Analytics and spent over two
decades at TVA rising to senior program manager of power quality. During his tenure at TVA, he
focused on integrating data from over 1700 power quality monitors, digital fault recorders,
revenue meters, and microprocessor relays into an enterprise database system. Since 2018, he
has been helping utilities and their stakeholders maximize investment in data for the
contemporary grid.