Algorithms, Available technologies, Clean Technologies, Electrical and Electronic components, Energy, Engineering, Information and communications technology (ICT)

SMART MEASUREMENT SYSTEM AND METHOD OF POWER ESTIMATION FOR ENERGY MANAGEMENT APPLICATIONS

Quickly deployable solution for load management responding in real-time and an adaptive manner

Challenge in utility resources management

  • Demand Side Management Programs (DSMs) aim to reduce overall energy consumption as well as the resources used to meet the demand of consumers.
  • The adoption of DSM initiatives is being established by the electric providers to diminish power demand during the critical periods of the power grid.
  • These initiatives mainly depend on implementation costs and convenience for both the utility provider and consumers.
  • Estimating the energy needed to heat a residential building is crucial for thermal performance evaluation.
  • Current DSM programs and DSM systems are based on predicting aggregated utility consumption (i.e. day-ahead or hours-ahead), scheduled utility network control, and utility consumption reduction incentives require communication between the utility provider and utility consumers.
  • Such DSM programs and systems rely on utility network control signals exchanged between the utility grid and the consumers. To provide these exchanges, additional implementation costs are necessary.
  • Such DSM programs may affect the comfort level of the electric utility consumer, adding some resistance to adopt such programs.
  • There is therefore a need for a method and system for managing utility resources, which is more easily deployable and scalable, while proving interesting for both the utility provider and consumers.

Smart energy management system

  • The present technology relates to a method for detecting, in real-time, power grid electric transients, analyzing these transients and providing a performance index from local measurements at the consumer side.
  • The performance index represents the state of power consumption seen by the power network and can be used for load management purposes at the consumer side.
  • The estimation of the power consumption is achieved through real-time signal processing method.
  • This method comprises a measurement unit and analog-to-digital conversion phase, a digital filtering process, an elementary statistical analysis and finally an estimation phase.
  • Technology developed by Prof. Kodjo Agbossou and his team at Université du Québec à Trois-Rivières.

Competitive advantages 

  • Permit a quickly deployable solution for load management responding in real-time and an adaptive manner.
  • Overcome the communications required between the electric provider managing the power grid and the local controller at the consumer side.
  • Permit to implement DSM and grid friendly Home Energy Management System programs at the consuming facility side, based on local measurements and transient analysis.
  • Reduce costs and complexity for a massive deployment.

Market applications

  • Home Energy Management Systems
  • Demand Side Management programs
  • Grid responsive / friendly loads

Business opportunity

  • US patent application 15,969,828
  • CA patent application 3,003,857
  • Technology available for partnering and licensing

CONTACT

If you are interested by this technology, please contact :
Pierre des Lierres, Director Business Development, Engineering
pdeslierres@aligo.ca, (514) 571-6556

UNIVERSITY

Université du Québec à Trois-Rivières (UQTR)

Main inventors

agbossou

Kodjo Agbossou, Professor, Electrical and Computer Engineering Department

Prof. Agbossou received the B.S., M.S., and Ph.D. degrees in electronic measurements from the Université de Nancy I, Nancy, France, in 1987, 1989, and 1992, respectively.,He is currently the Head of the Engineering School with the Université du Québec à Trois-Rivières (UQTR), Trois-Rivières, QC, Canada. His current research activities are in the area of renewable energy, integration of hydrogen production, storage and electrical energy generation systems, hybrid electrical vehicles, and control and measurements.

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