Grant: Discovery Grants Program - Individual
University of Saskatchewan
$72,000.00
Advanced Dynamic Load Modeling for Modern Smart Grids
FY 2021-22
Summary
Analytical Method; Artificial Intelligent-Based Machine Learning; Artificial Neural Networks; Distributed Generation; Dynamic Load Modeling; Parameter Identification; Renewable Energy Sources; Smart Grid; Support Vector Machines; Synchrophasor Technology
Program
Discovery Grants Program - Individual
Recipient
Location
Saskatchewan, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
RGPIN-2016-04170
Name nom
Liang, Xiaodong
Department département
Electrical & Computer Engineering - Electrical & Computer Engineering
Organization id
16
Institution établissement
University of Saskatchewan
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2021
Competition year année de concours
2016
Award amount
72000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
304
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Electrical energy
Area of application fr
Énergie électrique
Research subject code
2501
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Power systems
Research subject fr
Réseaux électriques
Installment
inst:6; 7
Partie
2
Nb partie
7
Application title
Advanced Dynamic Load Modeling for Modern Smart Grids
Keyword
NSERC
Application summary
Analytical Method; Artificial Intelligent-Based Machine Learning; Artificial Neural Networks; Distributed Generation; Dynamic Load Modeling; Parameter Identification; Renewable Energy Sources; Smart Grid; Support Vector Machines; Synchrophasor Technology
