Key performance indicators modeling for optimized microgrid configuration

Distribution system is so vulnerable to failures. These failures can be the result of natural or manmade threats. Blackouts are one of the distribution systems failures. Many people can be affected by blackouts. Therefore, microgrids can be a suitable candidate to have a robust and secure distribution power system Microgrids can support the distribution systems while they are having problems. Microgrids can be operated in small levels such as hospitals, government buildings, hotels and airports. Microgrids need to be studied in details. Models must be developed and analyzed to see the effect of the microgrid on the overall grid system. Microgrids can play a significant role in reducing the distribution systems dependency on the main grid as they have local distributed energy resources (DER) such as wind turbine, solar photovoltaic, diesel generator, gas engine, micro turbine, fuel cells, etc. In order to evaluate microgrids, key performance indicators (KPIs) need to be studied. These performance indicators are essential to evaluate and optimize the configuration of microgrids. These KPIs are reliability indicators, environmental indicators, economic indicators, and power quality factors. This research consists of two parts. The first part is optimizing a hybrid system design using GA (PV panels, wind turbines, and storage devices) by minimizing the system cost and maximizing the efficiency. The second part of the thesis focuses on KPIs in order to evaluate the performance of the microgrid. The proposed microgrid is modeled in MATLAB. Different scenarios are analyzed and the results are captured. In addition, AHP is used to evaluate the KPIs in a microgrid to determine which KPIs are the most important ones.

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

2015

Author dc:creator

• Honarmand, Negar

Advisor dc:contributor.advisor

• Gaber, Hossam

• Optimization
• Microgrid
• KPI modeling

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10155/606

OAI identifier oai:identifier

oai:ontariotechu.scholaris.ca:10155/606