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The Digital Utility – From AI, AR, MR to Blockchain platforms to support P2P

Monday, September 21, 2020 @ 6:00 PM - Thursday, September 24, 2020 @ 9:00 PM

This event has been cancelled.

Certificate for Course THE DIGITAL UTILITY, Signed by the Instructor. 15 PDUs per course for 5 day course. Discounts available for students and for companies who register more than 5 people for the event. Email dustin.dunwell@ieee.org for details.

Course Timetable:
Start time: 6:00 pm ET
End time: 9:00 pm ET

On each of the following dates:

  • Monday, September 21, 2020
  • Wednesday, September 23, 2020
  • Thursday, September 24, 2020
  • Monday, September 28, 2020
  • Thursday, October 1, 2020

Speakers: Puica Nitu, Afiny Akdemir

Location: Virtual – Zoom
Full meeting details, including passwords to join the meetings, will be sent out to registrants before the event.

Organizer: IEEE Toronto

Contact: Satish Saini, Dustin Dunwell

Register: https://meetings.vtools.ieee.org/m/238130

Course Fees:

  • Non-IEEE Members: $250 CAD
  • Active Members: $220 CAD
  • Student Members: $50 CAD
  • Discounts available for students and for companies who register more than 5 people for the event.

Course Content: The Digital utility encompasses technological end-to-end digitization with emphasis on the consumer, on the flexibility and integration of renewable technologies while offering an increased portfolio of market services. This is the first course of 4 e-learning courses. Each course runs 5 evenings, for 3 hours each.

The first course presents the integration of new technologies in light of regulatory changes. The course explores the penetration of renewable energy resources facilitated by the operating flexibility brought by power electronics. Interoperability aspects and industry standards are discussed, with focus on the consumer centric paradigm of Transactive Energy.

This course defines AI followed by VR, AR and MR as they apply to power systems. Practical examples illustrate each methodology. Special attention is given to advanced AI applications with Machine Learning for load and solar energy forecasts. The White House call-to-action of a decade ago allows utilities today to utilize energy platforms and APIs to standardize reporting, optimize consumption and leverage the much needed open exchange of solar data.

The course introduces the Blockchain as a new line of defense against cyber threats and its increasing application to Peer-to-Peer transactions to stimulate green energy trading and also trading Renewable Certificates or Credits.

The course provides industry examples from utilities and agencies from Canada, US, EU and Southeast Asia.

Course Outline:

  1. Introduction: Historical Evolution of the inverter-based technologies
  2. Performance Requirements: Power System Controls Regulatory Agreements NERC, EU ENTSO
    The Role of the ISO
  3. Demonstration of Essential Reliability Services – Control algorithms
  4. Power System Stability in an Inverter dominated Grid
  6. P2P Energy Trading
  7. Collaboration between Market Entities and Government Agencies Cloud Services for Utilities – NAESB Green Button, Orange Button
  8. ARTIFICIAL INTELLIGENCE -AI and Artificial Neural Networks- ANN
    AI and ANN Applications in Power Systems: Machine Learning
    Training the algorithm for Short Term Load Forecast and Solar Energy Forecasts
  9. IOT – Internet of Things; A brief look into Interoperability INTERNET OF THINGS WORLD FORUM REFERENCE MODEL
  12. MR- MIXED REALITY and AR-Augmented Reality
  13. IEDs- Intelligent Electronic Devices and SENSORS IEDs – Examples and Functionality
  14. BLOCKCHAIN Security Certification ; Vulnerability Blockchain Applications in the Power Industry- P2P Trading
    Trading Renewable Certificates
    Emission Credits
  15. Class Test 45 min and Discussions for Course Certification

The target audience for this course includes practitioners at all levels in the organization in companies in the power industry, LDCs, regulatory agencies and students in engineering and economics. The course would benefit law firms supporting renewable investments, and CleanTech groups.


Puica Nitu, M.Sc. P.Eng., SM IEEE, CIGRE

Puica Nitu is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex utility projects in operations (EMS, energy derivatives, reliability studies and policy) and conducted long term planning studies to support planning and operational reliability standards.

Specializing in Smart Grids, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. Most recently, Puica was the Operations Expert for a regulatory assessment of the Oman Control Centre.

With over 25 years with Ontario Hydro and its successor company Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, NSERC (Natural Sciences and Engineering Research Council of Canada), Senior Member IEEE and Elsevier since 1990.

Puica Nitu chaired international conferences, lectured on 4 continents, published a book on Reliability and Security of Nuclear Power Plants, papers in IEEE, PICA, CIGRE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars to OPG, seminars organized by the Power Engineering Society, IEEE and seminars to power companies worldwide, including Thailand, Saudi Arabia, Oman, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana.
Puica Nitu is a registered member of the Professional Engineers of Ontario, Canada.

Afiny Akdemir

Afiny Akdemir is the co-founder and Director of Research at Xesto Inc.  Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as “Toronto’s Best Tech Startup 2019” and was named one of the top 10 “Canadian AI Startups to Watch” as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership.

Afiny Akdemir specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications.

At Xesto, Afiny leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology.

In addition, Afiny is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. His ongoing projects examine the results of the regularity of the equation that governs optimal matching between two arbitrary sets in different dimensions. He is developing algorithmic applications of these results, as well as studying these applications in the context of big data and statistical estimation where the parameter space is much larger than the number of observations. Afiny earned a Bachelor’s and MSc in Mathematics, both at the University of Toronto.

Having presented at research seminars as well as instructing engineers on various levels, Afiny has the ability to distill advanced theoretical concept to diverse audiences on all levels.

In addition to research, Afiny is also an avid traveller and plays the violin.


Monday, September 21, 2020 @ 6:00 PM
Thursday, September 24, 2020 @ 9:00 PM