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Analysis of islanding detection capabilities of multi-inverter systems

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Analysis of islanding detection capabilities of multi-inverter systems

Zhang, Yongzheng (2006) Analysis of islanding detection capabilities of multi-inverter systems. Masters thesis, Concordia University.

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Abstract

Islanding is one important concern for grid connected distributed resources due to personnel and equipment safety. Inverter-resident islanding detection methods (IDMs) employ locally measured parameters to detect islanding. Passive type IDMs only monitor local variables such as voltage and frequency while active IDMs inject disturbances into the supply system and detect islanding based on system responses. Although very effective in systems with a single inverter, it is believed that active frequency drifting IDMs might have their effectiveness reduced in multi-inverter systems. This thesis investigates the islanding detection capabilities of multi-inverter systems. Three possible scenarios with passive-active, different and same type of active IDMs were discussed. Their performance was assessed using the concept of non-detection zones (NDZs) in a quality factor ( Q f ) vs. load resonant frequency ( f 0 ) load parameter space extended to multi-inverter systems. This thesis also proposes the use of a small dedicated reactive power source (STATCOM) as the sole active component in a multi-inverter system. In this way, interactions between inverters with active IDMs are prevented while effective islanding detection capability is provided by the islanding detection enhancer. The simulation and experiment results were presented to validate the theoretical analysis and the effectiveness of the proposed techniques.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Zhang, Yongzheng
Pagination:xvii, 95 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:2006
Thesis Supervisor(s):Lopes, Luiz A.C
Identification Number:LE 3 C66E44M 2006 Z49
ID Code:9250
Deposited By: Concordia University Library
Deposited On:18 Aug 2011 18:47
Last Modified:13 Jul 2020 20:06
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