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University of Ontario Institute of Technology

Design and control of resilient micro-inverter system

Abstract

dc:description.abstract

The growing implications of climate change have created an increasing demand for clean and renewable energy sources. Solar photovoltaics (PV) are increasingly popular as an alternative energy source due to the fact that they produce clean and renewable power with zero operating emissions. However, PV industries are facing issues of unreliability and low product life spans for the connected inverters. These issues can hinder the future growth of the industry. The aim of this research was therefore to design a micro-inverter system with improved resiliency for grid connected applications. The thesis is broken into the Inverter phase and the Resiliency phase. The Inverter phase consisted of the design of two inverters: a 300W micro-inverter and a 600W inverter simulated in PSIM. The Resiliency phase focused on the application of the designed inverters into four case studies for improving the resiliency of a PV system. It was found that placing an extra micro-inverter in parallel to the overall system was the most cost effective design with a high efficiency.

Degree

thesis:*
Name thesis:degree_name
Master of Applied Science (MASc)
Discipline thesis:degree_discipline
Electrical and Computer Engineering
Grantor
University of Ontario Institute of Technology
Year dc:date.issued
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Runge, Jason
Advisor dc:contributor.advisor
  • Gabbar, Hossam

Subjects

dc:subject × 5

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10155/664
OAI identifier oai:identifier
oai:ontariotechu.scholaris.ca:10155/664

Chain of custody

source
Harvested from
Ontario Institute of Technology
Base URL
ontariotechu.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Runge, Jason. Design and control of resilient micro-inverter system. University of Ontario Institute of Technology, 2016. https://hdl.handle.net/10155/664