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Grant: Engage Plus Grants Program

Université du Québec à Montréal

$12,500.00

Data Mining for Energy Analysis

FY 2017-18

Summary
The advent of information technology and electronic have facilitated the recording process of energyconsumption of costumers using smart meters. The recorded information can be explored to figure out relevantinsights. However, digging into this data pose a serious problem in the sense we have tremendous amount ofcostumers, which present various behaviour at different time point. Motivated by the need of effective softwarefor analyzing energy-related big data, SAP Canada Inc. (""SAP""), is developing SAP Energy Analysis, a newgeneration of real time business intelligence software for energy-related issues. SAP Energy Analysis offers aset of tools to run the data collected from smart meters and any other monitoring systems into actionableinsights. Specifically, SAP Energy Analysis provides tools to manage the cost effectiveness of energyproduction and consumption in the form of interactive dashboard, personalized report, real time businessactivity monitoring, prescriptive analysis, and more. By effectively analysing customers' consumption datausing SAP Energy Analysis, it becomes possible to monitor the energy production and consumption and, thus,allow better load balance, load matching and load scheduling through improving energy efficiencies andmanagement practices. To this end, the company wants to increase SAP Energy Analysis software capabilitiesto fully harness the potential of the collected data. To achieve this goal, the proposed project aims to investigateadvanced data mining algorithms in order to extract, from the collected data, useful patterns of actions thatoffer insight to track customers' consumption over different time stamps and develop an automatic tool toinstantly aggregate and analyze customers' energy consumption profiles by any dimension or level ofgranularity as well as predicting future consumption trends which in turn permits efficient energy use.
Program
Engage Plus Grants Program
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
508360-2017
Name nom
Bouguessa, Mohamed
Department département
Informatique
Organization id
57
Institution établissement
Université du Québec à Montréal
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2017
Competition year année de concours
2017
Award amount
12500
Program id
EGP2
Program name en
Engage Plus Grants Program
Program name fr
Programme de subvention d'engagement partenarial Plus
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1552
Committee name en
Quebec Internal Decision Committee
Committee name fr
Comité de décision interne pour le Québec
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
2800
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Artificial intelligence (computer vision, use2603)
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Partie
1
Nb partie
1
Application title
Data Mining for Energy Analysis
Keyword
NSERC
Application summary
The advent of information technology and electronic have facilitated the recording process of energyconsumption of costumers using smart meters. The recorded information can be explored to figure out relevantinsights. However, digging into this data pose a serious problem in the sense we have tremendous amount ofcostumers, which present various behaviour at different time point. Motivated by the need of effective softwarefor analyzing energy-related big data, SAP Canada Inc. (""SAP""), is developing SAP Energy Analysis, a newgeneration of real time business intelligence software for energy-related issues. SAP Energy Analysis offers aset of tools to run the data collected from smart meters and any other monitoring systems into actionableinsights. Specifically, SAP Energy Analysis provides tools to manage the cost effectiveness of energyproduction and consumption in the form of interactive dashboard, personalized report, real time businessactivity monitoring, prescriptive analysis, and more. By effectively analysing customers' consumption datausing SAP Energy Analysis, it becomes possible to monitor the energy production and consumption and, thus,allow better load balance, load matching and load scheduling through improving energy efficiencies andmanagement practices. To this end, the company wants to increase SAP Energy Analysis software capabilitiesto fully harness the potential of the collected data. To achieve this goal, the proposed project aims to investigateadvanced data mining algorithms in order to extract, from the collected data, useful patterns of actions thatoffer insight to track customers' consumption over different time stamps and develop an automatic tool toinstantly aggregate and analyze customers' energy consumption profiles by any dimension or level ofgranularity as well as predicting future consumption trends which in turn permits efficient energy use.