IEEE PES T&D Conference & Exposition 2022 - 57

Panelists:
J. Fu, DOE EERE WETO
L. He, University of Illinois Chicago
E. Starschich, Siemens Energy, Germany
PN29
Latest Trends in T&D Planning and Operations
1:00pm - 3:00pm
Session Chairs:
Sharma Kolluri, EntergySession
Marianna Vaiman, V&R Energy
As the electric grid is undergoing major changes, the
challenges of maintaining secure, reliable, stable and resilient
operation of transmission and distribution systems
are growing. In order to address these challenges, electric
utilities are evaluating and deploying innovative solutions,
exploring new technologies and tools, and implementing
advanced processes.
The panel will cover the best industry practices that utilities
are implementing in order to maintain reliable and
resilient behavior of transmission and distribution grids.
It will discuss the impact of the recent changes (such
as renewable energy sources, microgrids, and PMUs)
on maintaining grid stability, reliability and resilience.
Industry experts will share their experiences and plans on
testing and deploying innovative approaches and tools for
planning transmission and distribution grids, real-time
microgrid monitoring and analysis, advanced analysis of
transmission and distribution systems. The panel will
address cutting edge emerging methodologies and techniques
that will help utilities to better implement their
decarbonization strategies.
Panelists:
K. Lawlor, San Diego Gas & Electric Company
R. Manuguid, San Diego Gas & Electric Company
P. Etingov, PNNL
S. Kolluri, Entergy
C. Abbey, Quanta Technology
S. Pandey, ComEd
PN28
Advanced Deep Neural Network Techniques for Smart Grid
1:00pm - 3:00pm
Session Chair:
Hiroyuki Mori, Meiji University
April 2022 Show Issue
This panel provides new Deep Neural Network (DNN)
methods for Smart Grid operation and planning. The goal
of this panel is to understand different DNN models from
a standpoint of theoretical background and the applications
in Smart Grid. Now, the third trend on Artificial
Intelligence (AI) has continued since the proposal of Deep
Learning in 2006. The use of DNN has been spread in
the fields of engineering because of better performance
than Artificial Neural Network (ANN) in terms of the
model accuracy. On the surface, DNN might look similar
to ANN, but in practice, DNN is often different from
it. It has been originally developed in the field of image
processing so that it is not necessarily straightforward
to apply DNN to smart grid operation and planning. In
other words, we need to think out the new applications
by having enough knowledge about DNNs in different
case studies. In this panel, the effectiveness of different
DNNs such as Deep Boltzmann Machine (DBM), Deep
Reinforcement Learning (DRL), Convolutional Neural
Network (CNN), etc. is demonstrated to make a comparison
with the conventional methods.
Panelists:
H. Mori, Meiji University
S. Takayama, Osaka Prefecture University
A. Saber, ETAP R&D
M. Hori, Kyushyu University
PN21
Technology Innovation for Humanitarian Needs and Disaster Response
1:00pm - 3:00pm
Session Chairs:
Ruomei Li, IEEE
Alexander Anderson, PNNL
This forum will discuss how to avoid or reduce the
impact of various natural and non-natural disasters on
humans through power technology and policy innovation.
Non-natural disasters include injuries to people caused
by equipment failures and human operating errors in
generation, transmission, and distribution facilities. Solving
these challenges will require not only new technology,
but also information transparency, government policies,
and updated regulations. In any case, the invention of
electricity originated from people for people, and meeting
people's needs is always a priority. The content of the
panel will cover both technical descriptions and industry
survey results. Speakers come from engineering and academia,
covering several continents. The panel discussion
will serve as a forum for information exchange to build a
consensus on the development of humanitarian technology
to improve disaster response and operational safety.
ieee power & energy magazine
57
IEEE PES T&D Conference & Exposition 2022

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