CIGRE Academy Webinars

October 14, 2020 | 12:00PM–2:00PM ET | Register Here

Joint Working Group C2/C4.41

Impacts of High Share of Inverter-Based Resources on System Inertia and Frequency Control

Attendees of this webinar will receive a certificate for .2 CEU credits.

Speakers
[Moderator] Dr. Julia Matevosyan, ERCOT
Dr. Diptargha Chakravorty, TNEI
Dr. Papiya Dattaray, EPRI

Description
As a result of environmental incentives and policies as well as rapid technological development, power systems around the world are experiencing an increased number of inverter-based resources (IBRs), such as wind, solar and battery storage, being built. One of the challenges is that IBRs do not contribute to synchronous inertial response, while on the other hand, due to low/zero operating costs, displacing synchronous generation that provides inertial response in the unit commitment. Inertial response provides inherent resistance to change in system frequency after large generation trip events. If system inertia is low, the rate of change of frequency will be higher for the same size of generation loss. This leaves less time for any existing frequency control measures to respond and arrest system frequency before it triggers Under-frequency Load Shedding (UFLS). System operators, researchers, manufacturers and developers in countries that are experiencing rapid growth of IBRs have developed methods and technologies to address these issues.

This webinar will cover fundamentals of frequency control and impacts from high share of IBRs on overall frequency performance, and mitigation measures and technologies to address some of the challenges.

The presenters are members of CIGRE Joint Working Group (JWG) C2/C4.41 – Impact of High Penetration of Inverter-Based Generation on System Inertia of Networks. The group started three years ago with the objective to summarize and formulate methods for system operation in low inertia conditions in order to prepare for the ongoing energy transition. The JWG’s work will conclude in the first quarter of 2021 with the Technical Brochure and the group will host a Tutorial in December 2020.

The webinar will cover the following topics:

Fundamentals of Frequency Control and Impacts from High Share of IBRs
(15 mins)
Dr. Julia Matevosyan, ERCOT

Inertia Monitoring around the World
(15 mins)
Dr. Papiya Dattaray, EPRI

Inertia and Frequency Control by Generation Technologies
(10 mins)
Dr. Julia Matevosyan, ERCOT

Inertia and Frequency Control by Load Resources
(10 mins)
Dr. Diptargha Chakravorty, TNEI

Procurement of Inertial Products, Example of Great Britain and Ireland
(15 mins)
Dr. Diptargha Chakravorty, TNEI

Fast Frequency Response around the World
(15 mins)
Dr. Papiya Dattaray, EPRI

Methodology to Determine Amounts of Frequency Containment Reserve, Example of ERCOT
(15 mins)
Dr. Julia Matevosyan, ERCOT

Closing Remarks
(5 mins)
Dr. Julia Matevosyan, ERCOT

Q&A using slido.com
(15-20 mins)
Dr. Julia Matevosyan, ERCOT

October 21 & 28, 2020 | 12:00PM–2:00PM ET | Register Here

Virtual Tutorial

Accelerating AI on the Grid: PMU Fundamentals & Intro to AI

Attendees of this webinar will receive a certificate for .4 CEU credits.

Instructors
Alexandra “Sascha” von Meier, University of California, Berkeley
Kevin Jones, Dominion Energy
Sean Murphy, PingThings
Laurel Dunn, University of California, Berkeley
Mohini Bariya, University of California, Berkeley
Miles Rusch, University of California, Berkeley

Abstract
This two-part virtual tutorial is geared at training practitioners on how to use AI to analyze PMU (synchrophasor) data. The first session (PMU fundamentals) will provide a foundation for understanding and interpreting PMU measurement data and applications to practitioners at electric utilities. The second session (Intro to AI) will provide an introduction to Artificial Intelligence (AI), and will give attendees hands-on experience using AI to analyze PMU data in Python. The course will discuss opportunities for PMU data analytics to change best-practices in the industry, and participants will become practiced at using tools that can streamline workflows for digesting and visualizing time series data at scale.

Day 1 | October 21, 2020 | PMU Fundamentals
Day 1 will teach fundamental concepts from power systems engineering related to interpreting and analyzing PMU measurement data. This tutorial will both educate newcomers, and will serve as a useful refresher for seasoned experts. The course will go on to describe how PMU data are being applied in utility operations. Panelists will include Kevin Jones who has been instrumental in launching the PMU analytics program at Dominion. Their approach has been to connect analysts across the company with the training and tools they need to easily access PMU data; the program has unlocked unexpected opportunities for decision-makers to act on data in a more timely and more effective manner.

Day 2 | October 28, 2020 | Intro to AI
Day 2 will provide an introductory training for practitioners to start using AI in their own work. The course will begin by covering fundamental concepts related to AI and big data, and will motivate the need for practitioners in energy to become well-versed in AI tools. The course will step through interactive coding exercises using the National Infrastructure for AI on the Grid (NI4AI) Python API to access publicly hosted PMU data. NI4AI is built on PingThings’ PredictiveGridTM platform, a state-of-the-art tool optimized to support big data visualization and analysis workflows. Participants are requested to come prepared with a login to ni4ai.org and with Python installed (both are free). Exercises will assume some familiarity with Python, though participants with no programming experience will benefit from exposure to the concepts and tools presented.

PMU Fundamentals (Day 1)

1. Understanding PMU data
(Alexandra von Meier, 45 min)
1.1. Introduction to phasors and
PMU measurements
>1.2. PMU data and the grid: what
are we looking at, and why?

2. Applications for PMU data
(Kevin Jones, 45 min)
2.1. Applications for PMU data
2.2. How PMU data is changing the
way utilities operate

3. Introduction to NI4AI
(Sean Murphy, 30 min)
3.1. NI4AI data and content
3.2. Navigating the PredictiveGridTM
platform
3.3. NI4AI resources

Intro to AI (Day 2)

1. Big data analytics and prediction
(Sean Murphy, 20 min)

2. Interfacing with PMU data in Python
(Laurel Dunn, 25 min)
2.1. Accessing the NI4AI API
2.2. Phasor visualization
2.3. “Unwrapping” phase angle

3. Use cases for PMU data
3.1. Detecting voltage sags
(Mohini Bariya, 30 min)
3.2. Analyzing frequency
(Miles Rusch, 30 min)

4. Closing remarks and outlook for AI on the grid
(Sean Murphy, 15 min)

November 5 & 12, 2020 | 12:00PM–2:00PM ET | Register Here

Virtual Tutorial

Enabling Distributed Intelligence with the Open Field Message Bus (OpenFMB) Framework

Attendees of this webinar will receive a certificate for .4 CEU credits.

Instructors
John Camilleri, PSC
Dr. Stuart Laval, Duke Energy
Larry Lackey, Open Energy Solutions Inc. (OES)

Description
The OpenFMB Interoperability Framework standard was ratified in 2016 by the North American Energy Standards Board (NAESB). Today, the Utility Communications Architecture International Users Group (UCAIug) maintains the user’s group and is the Interoperability Testing Certification Authority. These two hour sessions provide both an overview of the standard and industry participation, as well as technical application.

Session 1 | OpenFMB 101: Introduction of the Standard, Business Drivers, and Industry Landscape
The OpenFMB Interoperability Framework has numerous benefits when federating operational grid-edge data in the field and enables new ways of addressing present and future challenges at utilities. This interactive session introduces the fundamental details of the OpenFMB standard, evolving grid-edge business drivers, and the key ecosystem players. Attendees will hear from utilities, vendors, and other active OpenFMB users group members on their experience.

Attendees of this session will learn about the:

  • Fundamentals of OpenFMB Standard and Architecture
  • Business drivers for Distributed Intelligence and Data Federation at the Grid-Edge
  • OpenFMB Adoption and Industry Landscape
  • Relevance of Open-Source

Session 2 | OpenFMB Implementation Approach: Current Developments and Technology Stack
During the session, attendees will review use cases, platform independent data models, and adapters. There will be discussions on lessons learned, best practices and limitations. In addition, we will review the concepts of system management and cyber security controls.

Attendees of this session will learn about the:

  • Key Enabling Technologies for OpenFMB
  • Messaging and data model extensibility of the framework
  • Use-cases that leverage Distributed Intelligence
  • Cybersecurity enhancements inherent to OpenFMB
  • Roadmap of Distributed Applications

 

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