Applications Of Data-Driven Analytics and Decision-Making Optimization for Solar-powered Energy Hubs Integrated With Electrical Vehicles

The worldwide urge to seek solutions for global warming and its negative environmental impacts, has driven the increased adoption of renewable energy resources and electric vehicles (EVs). This increase in the share of renewable energy generation and EV users has widened the implementation of distributed energy resources (DERs) systems and encouraged the move towards developing and modeling smart energy hubs. Boxbrite Technologies is a leading cleantech company in the region of Waterloo and develops software solutions for the renewable energy industry that aims to optimize energy systems. The solar charging systems that are overseen by Boxbrite are examples of energy hub systems, which can be better optimized via the full utilization of available data. However, several challenges are imposed on the energy hub optimization that include EVs charging system due to high degree of uncertainties in renewable DERs power output, demand, and unavailability of accurate forecasting profiles for the renewable power generation and EV charging behaviour. This research will take the full advantage of recent advancements in big data tools by strategically integrating them within the energy system decision-making. The proposed project is designed to be a top-to-bottom comprehensive study to investigate how energy hubs powered by renewable energy and EV infrastructure can be utilized to enhance the profitability of all stakeholders involved. It is expected that this project will guide the deployment of renewable DER on a larger scale, providing deeper visibility into the performance of energy hubs as one of the potential solutions to Canada’s decarbonization goals.

Faculty Supervisor:

Ali Elkamel

Student:

Partner:

Boxbrite Technologies Inc.;Net Zero Atlantic

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program: