IEEE Power & Energy Magazine - Grid Edge 2023 - 13

* 23GET0109, Network of Microgrids: Opportunities and
Challenges
K. SKEEN, Clemson University
G. VENAYAGAMOORTHY, Clemson University
* 23GET0110, Federated Learning vs Edge Learning for
Hot Water Demand Forecasting in Distributed Electric
Water Heaters for Demand Side Flexibility Aggregation
S. PANDIYAN, NTNU
J. RAJASEKHARAN, NTNU
* 23GET0112, Optimal Defense Strategy Against Load
Redistribution Attacks under Attacker’s Resource
Uncertainty: A Trilevel Optimization Approach
J. SU, George Washington University
C. XIE, George Washington University
P. DEHGHANIAN, George Washington University
S. MEHRANI, Florida Atlantic University
* 23GET0114, Steady State Voltage Regulation Requirements
for Grid-Forming Inverter based Power Plant in
Microgrid Applications
W. WANG, Electric Power Research Institute
A. HUQUE, Electric Power Research Institute
* 23GET0118, Training A Deep Reinforcement Learning
Agent for Microgrid Control using PSCAD
Environment
A. FAROKHI SOOFI, University of California
San Diego
R. BAYANI, University of California San Diego
M. YAZDANIBIOUKI, San Diego State University
S. D. MANSHADI, San Diego State University
PANEL SESSIONS
Be sure to visit the conference web page as additional panel
sessions and panel session details will be available soon.
Application of Real-Time Simulation in Bulk Power
System Studies with Renewables (Panel Session)
Session Chair: Aboutaleb Haddadi, Electric Power Research
Institute
Real-time (RT) simulation provides a high-fidelity simulation
capability that also enables assessing the performance
of an actual hardware in a close-to-real environment
through Hardware-In-the-Loop (HIL) simulation. This
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April 2023 Show Issue
ieee power & energy magazine
13
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IEEE Power & Energy Magazine - Grid Edge 2023

Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - Grid Edge 2023

Contents
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IEEE Power & Energy Magazine - Grid Edge 2023 - Cover2
IEEE Power & Energy Magazine - Grid Edge 2023 - Contents
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