Canada Spends Logo

Explorez notre analyse du budget 2026

Grant: Discovery Grants Program - Individual

Memorial University of Newfoundland

$28,000.00

Dynamic Modeling and Control of Hybrid Power Systems

EF 2021-22

Résumé
Power systems that include conventional generation and renewable energy sources are called hybrid power systems. Canada has hundreds of remote isolated diesel-powered communities and many people live off-grid. Each remote community and isolated home can potentially use a more effective hybrid power system to supply power needs. The optimal sizing of a hybrid power system depends on the configuration of system components and cost analysis. The analysis and design of hybrid power systems is complex because of the nonlinear power characteristics of the components, e.g., wind turbine, PV system, energy storage, backup generator, and the load. Hybrid power systems also require optimal dynamic and supervisory controllers and may involve AC as well as a DC bus. The objectives of the proposed research program are to develop new predictive models and optimal control systems and components for small hybrid power systems. This research will integrate subsystem level models of small wind turbines, photovoltaic solar cells, batteries, and generators to develop new dynamic models of hybrid power systems. System controllers will be designed with the simulation results of hybrid power system models. More specifically, the research program will develop and identify: (1) new methods to determine a reduced order dynamic model of hybrid power systems that could be simulated more quickly than existing models; (2) intelligent control methods including supervisory controllers and ultra-low power data loggers; (3) a new linear parameter varying controller and a fuzzy supervisory controller for hybrid power systems and determine the best operational strategy; and (4) a low voltage nano-grid to power remote houses with distributed battery storage and renewable sources including a dynamic and supervisory controller for optimal operation. The research will develop a method to eliminate circulating currents between converters in hybrid power systems when such converters are working in synchronous and asynchronous switching modes. Also, it aims to develop a new method for reliability analysis of small remote hybrid power systems. The reduced order modeling and design of new ultra-low power controllers and data loggers are innovative since they will positively impact simulation techniques and phantom losses in hybrid power systems. The proposed research on a nano-grid will design a new supervisory controller and resolve its associated converters issues. The proposed research program will lead to new knowledge on hybrid power systems, their design, control, instrumentation, data logging, and reliability analysis. The research will enhance the adoption of renewable energy in Canada thereby helping to meet its commitment to reduce emissions and improves the lives of people living in remote northern communities. This research will also train ten graduate students on hybrid renewable power systems, hence developing the needed HQP for the renewable energy industry in Canada.
Programme
Discovery Grants Program - Individual
Emplacement
Newfoundland and Labrador, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2019-04126
Name nom
Iqbal, Mohammad
Department département
ECE
Organization id
89
Institution établissement
Memorial University of Newfoundland
Province en
Newfoundland and Labrador
Province fr
Terre-Neuve-et-Labrador
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2021
Competition year année de concours
2019
Award amount
28000
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
2516
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Energy conversion and distribution
Research subject fr
Conversion et distribution de l'énergie
Installment
inst:3
Partie
1
Nb partie
5
Application title
Dynamic Modeling and Control of Hybrid Power Systems
Keyword
NSERC
Application summary
Power systems that include conventional generation and renewable energy sources are called hybrid power systems. Canada has hundreds of remote isolated diesel-powered communities and many people live off-grid. Each remote community and isolated home can potentially use a more effective hybrid power system to supply power needs. The optimal sizing of a hybrid power system depends on the configuration of system components and cost analysis. The analysis and design of hybrid power systems is complex because of the nonlinear power characteristics of the components, e.g., wind turbine, PV system, energy storage, backup generator, and the load. Hybrid power systems also require optimal dynamic and supervisory controllers and may involve AC as well as a DC bus. The objectives of the proposed research program are to develop new predictive models and optimal control systems and components for small hybrid power systems. This research will integrate subsystem level models of small wind turbines, photovoltaic solar cells, batteries, and generators to develop new dynamic models of hybrid power systems. System controllers will be designed with the simulation results of hybrid power system models. More specifically, the research program will develop and identify: (1) new methods to determine a reduced order dynamic model of hybrid power systems that could be simulated more quickly than existing models; (2) intelligent control methods including supervisory controllers and ultra-low power data loggers; (3) a new linear parameter varying controller and a fuzzy supervisory controller for hybrid power systems and determine the best operational strategy; and (4) a low voltage nano-grid to power remote houses with distributed battery storage and renewable sources including a dynamic and supervisory controller for optimal operation. The research will develop a method to eliminate circulating currents between converters in hybrid power systems when such converters are working in synchronous and asynchronous switching modes. Also, it aims to develop a new method for reliability analysis of small remote hybrid power systems. The reduced order modeling and design of new ultra-low power controllers and data loggers are innovative since they will positively impact simulation techniques and phantom losses in hybrid power systems. The proposed research on a nano-grid will design a new supervisory controller and resolve its associated converters issues. The proposed research program will lead to new knowledge on hybrid power systems, their design, control, instrumentation, data logging, and reliability analysis. The research will enhance the adoption of renewable energy in Canada thereby helping to meet its commitment to reduce emissions and improves the lives of people living in remote northern communities. This research will also train ten graduate students on hybrid renewable power systems, hence developing the needed HQP for the renewable energy industry in Canada.