Intelligent single-point energy consumption monitoring for intensive energy sectors applications

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Smart meters are considered key component in the deployment of automatic metering infrastructure (AMI) in the smart grid evolution. Despite such meters' capabilities in reporting the total energy consumption along with time of use (TOU) to electric utilities and consumers, there is still lack of effective processes and methodologies to minimize the energy waste in intensive energy sectors such as industrial facilities, commercial buildings, university campuses, etc. Such large sectors are characterized by stranded equipment, which makes monitoring the electric energy consumption at individual equipment level from economic and practical perspectives infeasible. Given this fact, the process of identifying the energy waste in specific equipment, selecting candidate loads for demand side provision, equipment troubleshooting, and finding optimal operating strategies for this equipment considering TOU while ensuring not to compromise the whole sector goals/objectives become challenging to realize. Substantial research effort is needed to achieve a non-intrusive and cost-effective energy consumption monitoring approach that paves the road toward realizing smarter, efficient, and accurate metering infrastructure. The proposed research work aims to bridge the gap between existing energy monitoring system and smart energy consumption through the development of intelligent algorithms for AMI based on single-point sensing and innovative un-supervised learning to breakdown the aggregated energy consumption in the targeted sectors hence better quantify the electricity usage and identify the energy waste. With close co-operation with the industrial partners of this project, the proposed research work will supply Hydro One with the necessary information that will help reducing the impact on their transmission/distribution systems, increase the lifetime/performance of their assets, expand the capabilities of the energy monitoring products of Siemens Canada while ensuring low product cost and more energy consumption information accessibility. Moreover, the proposed research work will also help Ontario Power Generation to reduce their generation production cost and reduce their carbon foot print.