Grant: Collaborative Research and Development Grants
University of Western Ontario
$60,000.00
Big data analytics for energy management
FY 2015-16
Summary
As part of the Green Button initiative, utilities in Canada and the United States are making attempts to make smart meter data more accessible to customers by enabling them to download their energy usage data securely and share it with third parties. These Big Data presents opportunities to analyze energy consumption patterns, identify savings opportunities, and conserve energy.
The main objective of this research project is to devise a comprehensive software framework for monitoring energy consumption and analyzing data provided by smart meters along with the development of energy-related software applications. To achieve these goals, this project will explore and advance Big Data analytics in the context of energy management. The framework will be based on Service-Oriented Architecture and will provide data analytics capabilities as services. Moreover, because traditional data analytics methods are facing challenges in addressing Big Data requirements, traditional machine learning and data mining approaches will be adapted for work with Big Data in distributed and/or cloud environments.
The results from this project will directly benefit the industrial partner London Hydro by providing a generic, flexible, and expandable framework for energy management. The outcome of this project will provide energy consumers with the ability to understand their energy consumption better, identify opportunities for energy and cost savings, and estimate their future energy consumption and cost.
It is also expected that this project will contribute to advancements in Big Data analytics research which can benefit other domains. Furthermore, the HQP involved in this project will gain valuable experience in working with Big Data in the smart environment sector, which will make them valuable to any Internet of Things or Big Data job-related market.
Program
Collaborative Research and Development Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
477530-2014
Name nom
Capretz, Miriam
Department département
Electrical and Computer Engineering
Organization id
36
Institution établissement
University of Western Ontario
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2015
Competition year année de concours
2014
Award amount
60000
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
801
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer software
Area of application fr
Logiciel
Research subject code
2706
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Software engineering
Research subject fr
Génie logiciel
Partie
1
Nb partie
2
Application title
Big data analytics for energy management
Keyword
NSERC
Application summary
As part of the Green Button initiative, utilities in Canada and the United States are making attempts to make smart meter data more accessible to customers by enabling them to download their energy usage data securely and share it with third parties. These Big Data presents opportunities to analyze energy consumption patterns, identify savings opportunities, and conserve energy.
The main objective of this research project is to devise a comprehensive software framework for monitoring energy consumption and analyzing data provided by smart meters along with the development of energy-related software applications. To achieve these goals, this project will explore and advance Big Data analytics in the context of energy management. The framework will be based on Service-Oriented Architecture and will provide data analytics capabilities as services. Moreover, because traditional data analytics methods are facing challenges in addressing Big Data requirements, traditional machine learning and data mining approaches will be adapted for work with Big Data in distributed and/or cloud environments.
The results from this project will directly benefit the industrial partner London Hydro by providing a generic, flexible, and expandable framework for energy management. The outcome of this project will provide energy consumers with the ability to understand their energy consumption better, identify opportunities for energy and cost savings, and estimate their future energy consumption and cost.
It is also expected that this project will contribute to advancements in Big Data analytics research which can benefit other domains. Furthermore, the HQP involved in this project will gain valuable experience in working with Big Data in the smart environment sector, which will make them valuable to any Internet of Things or Big Data job-related market.