Team Members
Summary
The increasing cost, energy demand, and environmental issues has led many researchers to find approaches for energy monitoring, and hence energy conservation. The emerging technologies of Internet of Things (IoT) and Machine Learning (ML) deliver techniques that have the potential to efficiently conserve energy and improve the utilization of energy consumption. Smart Home Energy Management Systems (SHEMSs) have the potential to contribute in energy conservation through the application of Demand Response (DR) in the residential sector. In this research, we propose appliances Operation Modes Identification using Cycles Clustering (OMICC) which is SHEMS fundamental approach that utilizes the sensed residential disaggregated power consumption in supporting DR by providing consumers the opportunity to select lighter appliance operation modes. The cycles of the Single Usage Profile (SUP) of an appliance are extracted and reformed into features in terms of clusters of cycles. These features are then used to identify the operation mode used in every occurrence using K-Nearest Neighbors (KNN). Operation modes identification is considered a basis for many potential smart DR applications within SHEMS towards the consumers or the suppliers.
Publications
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MSc Thesis: Classifying Appliances Operation Modes Using Dynamic Time Warping and K Nearest Neighbors
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Demand Response for Residential Uses: A Data Analytics Approach
IEEE 6th World Forum on Internet of Things (WF-IoT), New Orleans, LA, USA
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Appliances Operation Modes Identification Using Cycles Clustering (OMICC)
submitted to IEEE Transactions on Smart Grid
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Smart Home Energy Visualizer: A Fusion of Data Analytics And Information Visualization
submitted to ACM-IEEE 17th CNSM 2021
Presentations
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Enhancing demand response by domestic electricity consumption by giving tips based on daily time series power consumption
Awards
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First Prize Winner at the UWORCS 2021 conference (best research proposal presentation category),Dept.of Computer Science, Western University
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First Prize Winner at the UWORCS 2019 conference (best research proposal presentation category),Dept.of Computer Science, Western University