Power utility efficiency improvements through novel data collection- ON-334

Project type: Research
Desired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences
Company: Fibos Inc.
Project Length: 4 to 6 months
Preferred start date: As soon as possible.
Language requirement: English
Location(s): Canada
No. of positions: 1
Desired education level: CollegeUndergraduate/BachelorMaster'sPhDPostdoctoral fellow
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About the company: 

Fibos has developed a fiber optic sensing platform that can enable data to be collected from environments not previously before possible. Fibos has the capabilities to develop strain based sensors, allowing for the collection of temperature, pressure, vibration and load in high voltage and high EMI areas.

Describe the project.: 

Fibos is looking to understand the grid level efficiency improvements that can be materialized by merging the data collected from a variety of power utility equipment (i.e. transformers, switch gear, transmission lines) and running that through algorthms that can predict future performance from historic data. The project will include both research of existing techniques, as well as research using new data provided into the project from real grid equipment. This data will be gathered from existing sensors, as well as from new sensors added to the grid level equipment. The project will help determine which data types are required from the grid level equipment and will attempt to quantify the value of the amalgomated data for a power utility (i.e. efficiencies, improved uptime, reduction in maintenance costs, equipment life extensions).

Required expertise/skills: 

  • Power Grid equipment expertise (i.e. what equipment is currently used, and what measurements are being captured)
  • Big data and machine learning from large datasets
  • Power utility regulations (not criticial but would be helpful to understand what can/cannot be added and what type of control would be allowed)