Advanced Solar Photovoltaic (PV) Data Analysis and Performance Predictor using Edge Computing

This project focuses on giving the commercial or industrial property (i.e. non-solar professional) owners and facilities managers the ability to accurately calculate the predicted output of a small to medium-size solar plant and compare that value to what it is producing. This comparison is helpful to the facilities manager as it gives a way to monitor for, pick up on and rectify issues with their solar plant, thereby ensuring their return on their investment. These predictive comparative outputs will be created via external sensors placed within the Solar plant communicating with a mini-computer to process the data. Finally, the information will be sent to a cloud service for data storage and display.

Faculty Supervisor:

Kyle Valdock

Student:

Partner:

Voltaire Power

Discipline:

Engineering

Sector:

Other services (except public administration)

University:

Seneca College

Program: