Advancing Grid Electrification through Machine Learning Algorithms

On a global scale, there’s a big effort to set ambitious goals for cutting down on the amount of carbon emissions we release into the atmosphere. To achieve this, we need to upgrade and expand our electrical grid so it can handle the increased use of electricity in various sectors. The problem is that there are challenges in ensuring that everything runs smoothly, performs at its best, and stays reliable. Now, EdgeTunePower (ETP) and Simon Fraser University (SFU) are teaming up for a big project. Their main goal is to use advanced technology like machine learning and data science to process and analyze real-time data from electrical energy systems. By doing this, they hope to solve problems like not having enough grid capacity, making the system more reliable, and ensuring it can bounce back quickly if something goes wrong. The ultimate aim is to make it easier to use electricity for things like transportation, heating, and mining, without causing harm to the environment.

Faculty Supervisor:

Mariana Resener

Student:

Partner:

EdgeTunePower Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Simon Fraser University

Program: