Optimization of Energy Distribution for Electric Vehicles Charging

This project addresses the growing challenges associated with the increasing demand for Electric Vehicles (EVs) within the context of a global shift towards sustainable energy solutions. The surge in EV adoption, while beneficial for the environment, poses challenges on the energy grid due to frequent and high-powered charging, leading to more frequent peaks and potential failures of the energy grid. The proposed solution involves storing energy during off-peak hours and discharging it strategically, but the complexities arise from the impact of charging patterns on battery life cycle. Leveraging the power of Artificial Intelligence (AI) and optimization, the project aims to develop an innovative solution. Specifically, it suggests scheduling slow charging during off-peak hours through a collaboration between Carleton University and BluWave.ai. This strategic partnership combines expertise in data engineering, computational geometry, and advanced optimization techniques to create an optimizer. The primary objective is to achieve a harmonious balance between the load on the energy grid and the longevity of EV batteries, fostering a sustainable and efficient approach to electric vehicle charging.

Faculty Supervisor:

Prosenjit Bose

Student:

Partner:

Bluwave-AI

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Carleton University

Program: