Date of Award

Spring 2022

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2022.

Department

Electrical and Computer Engineering

First Advisor

Maryam Khanbaghi

Abstract

Santa Clara University is a large loads in Santa Clara needed two finders and a maximum of over 8MW peak demand; however, this consumption will only increase as the student body and electric vehicles on campus continue to grow. To meet this rising demand in both a sustainable and environmentally friendly manner, we proposed and simulated a complete energy management system with cost analysis of energy savings of a microgrid capable of reducing the power supplied to Santa Clara University’s campus from the grid by 40% using renewable energy, vehicle-to-grid (V2G) functionality, and real SCU energy data. The project further used machine learning to match SCU’s energy demand with the renewable generation for future use of optimizing the proposed system. The microgrid was simulated in MATLAB while the machine learning algorithm was developed in python. The benefits of this project provide SCU with a path to 100% clean energy, increased power reliability, and reduced operating cost for SCU. Increasing solar output on campus is the best way to achieve 100% renewable energy because the fuel cells on campus have a byproduct of carbon dioxide and are therefore not 100% renewable. Our vehicle to grid analysis showed that it is not currently a viable solution to help SCU run on 100% renewable energy; however, as electric vehicle charging capacity at SCU increases, vehicle to grid could become an important part of SCU achieving carbon neutrality.

Download

Share

COinS