Canada Spends Logo

Explore our Budget 2026 analysis

Grant: Collaborative Research and Development Grants

Lakehead University

$30,000.00

A data analytics system for adaptive demand response in smart grids

FY 2019-20

Summary
The load demand of the residential sector in Canada constitutes a third of the country's electricity consumption according to Natural Resources Canada. With thousands of houses being built every year, the growing demand has heightened the burden on electric grids. To address this concern, utility companies strive to find ways to engage consumers in demand response (DR) programs to reduce load demand. However, DR programs face multiple research challenges in the residential sector. First, existing DR programs do not explore the issue of reducing peak load while taking into account the consumer energy consumption behavior. Second, DR schemes require accurate prediction of energy spikes at the electric feeder level (e.g., neighborhood) to be effective. Third, targeting individual appliance/device at residential homes requires a prioritization and interruption cost mechanisms to ensure proper and fair monetary compensation for consumers. To address the above challenges, in this research project we propose to work with Synergy North, Thunder Bay, Canada, to study, design, and develop an intelligent adaptive data-driven DR system. Synergy North is the power distribution company responsible for delivering electricity to 56,000 homes and businesses in the cities of Thunder Bay and Kenora in Northwestern Ontario. The outcome of this research project can lead to breakthroughs in the design and development of next-generation energy DR for the residential sector. The project benefits Canada's economy and the environment in different aspects. Canadian residential consumers adopting the proposed DR solution will be able to save in their electricity bill by engaging in energy curtailment schemes and receive compensation. Canadian utilities will be able to reduce the cost of energy during peak hours and minimize their dependency on standby generators or fossil fuel plants; thus, helping Canada's environment by decreasing greenhouse gas emissions.
Program
Collaborative Research and Development Grants
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
543866-2019
Name nom
Yassine, Abdulsalam
Department département
Software Engineering, Dept. of
Organization id
25
Institution établissement
Lakehead University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2019
Competition year année de concours
2019
Award amount
30000
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
306
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Energy efficiency
Area of application fr
Efficacité énergétique
Research subject code
2705
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Software and development
Research subject fr
Logiciels et développement
Installment
inst:1 - 1
Partie
1
Nb partie
1
Application title
A data analytics system for adaptive demand response in smart grids
Keyword
NSERC
Application summary
The load demand of the residential sector in Canada constitutes a third of the country's electricity consumption according to Natural Resources Canada. With thousands of houses being built every year, the growing demand has heightened the burden on electric grids. To address this concern, utility companies strive to find ways to engage consumers in demand response (DR) programs to reduce load demand. However, DR programs face multiple research challenges in the residential sector. First, existing DR programs do not explore the issue of reducing peak load while taking into account the consumer energy consumption behavior. Second, DR schemes require accurate prediction of energy spikes at the electric feeder level (e.g., neighborhood) to be effective. Third, targeting individual appliance/device at residential homes requires a prioritization and interruption cost mechanisms to ensure proper and fair monetary compensation for consumers. To address the above challenges, in this research project we propose to work with Synergy North, Thunder Bay, Canada, to study, design, and develop an intelligent adaptive data-driven DR system. Synergy North is the power distribution company responsible for delivering electricity to 56,000 homes and businesses in the cities of Thunder Bay and Kenora in Northwestern Ontario. The outcome of this research project can lead to breakthroughs in the design and development of next-generation energy DR for the residential sector. The project benefits Canada's economy and the environment in different aspects. Canadian residential consumers adopting the proposed DR solution will be able to save in their electricity bill by engaging in energy curtailment schemes and receive compensation. Canadian utilities will be able to reduce the cost of energy during peak hours and minimize their dependency on standby generators or fossil fuel plants; thus, helping Canada's environment by decreasing greenhouse gas emissions.
Lakehead University - $30,000 Grant (2019-20) | Canada Spends