Islanding Detection Thesis Statement

Term of Award

Spring 2015

Degree Name

Master of Science in Applied Engineering (M.S.A.E.)

Document Type and Release Option

Thesis (open access)

Department

Department of Electrical Engineering

Committee Chair

Rami Haddad

Committee Member 1

Youakim Kalaani

Committee Member 2

Frank Goforth

Committee Member 3

Adel El Shahat

Abstract

Distributed Generation (DG) sources have become an integral part of modern decentralized power systems. However, the interconnection of DG systems to the power grid can present several operational challenges. One such major challenge is islanding detection. Islanding occurs when a DG system is disconnected from the rest of the power grid. Islanding can present serious safety hazards and therefore an accurate and fast islanding detection technique is mandated by DG interconnection standards such as IEEE 1547 and UL 1741. Conventional islanding detection techniques passively monitor the local power system parameters such as voltage and frequency to detect islanding. These techniques have large non-detection zones and are prone to nuisance tripping. Therefore, two improved and computationally inexpensive passive islanding detection techniques for inverter-based DG systems were proposed. The techniques monitor the ripple content in the rate of change of frequency and voltage amplitude waveforms using time domain-spectral analysis. The proposed techniques were tested for inverter-based DG systems modeled according to IEEE 929-2000 standard. Results indicated that both techniques were not only capable of detecting islanding, but also able to accurately distinguish between islanding and non-islanding events under a wide range of operating conditions. Furthermore, a novel Smart DG system which is able to detect and classify events was proposed. This added intelligence has considerable impact on the safety and operation of such DG systems. This feature will help the system operator develop a clear understanding of the operating requirements needed to mitigate the effects of such events. The event classification technique has been implemented using artificial neural networks (ANN) with a set of local input parameters. Five parallel ANNs have been designed with a majority vote final stage to represent the final classification output. A total of 310 event cases have been generated to test the performance of the technique. This technique classified the events within 10 cycles of their occurrence with a 98% average classification accuracy.

Recommended Citation

Guha, Bikiran, "Smart Distributed Generation Systems Using Improved Islanding Detection and Event Classification" (2015). Electronic Theses & Dissertations. 1262.
https://digitalcommons.georgiasouthern.edu/etd/1262

Keywords

Algorithms, amplitude estimation, distributed algorithm, distributed energy resources, distributed generation, dynamic estimator, inverter based distributed generation, islanding, islanding detection methods, non detection zone, non linear observer, over/under frequency protection, over/under voltage protection, point of common coupling, quality factor, sandia frequency shift, scheduled perturbation, stiffness, transient response

Abstract

Recently, a lot of research work has been dedicated toward enhancing performance, reliability and integrity of distributed energy resources that are integrated into distribution networks. The problem of islanding detection and islanding prevention (i.e. anti-islanding) has stimulated a lot of research due to its role in severely compromising the safety of working personnel and resulting in equipment damages. Various Islanding Detection Methods (IDMs) have been developed within the last ten years in anticipation of the tremendous increase in the penetration of Distributed Generation (DG) in distribution system. This work proposes new IDMs that rely on transient and distributed behaviors to improve integrity and performance of DGs while maintaining multi-DG islanding detection capability. In this thesis, the following questions have been addressed: How to utilize the transient behavior arising from an islanding condition to improve detectability and robust performance of IDMs in a distributive manner? How to reduce the negative stability impact of the well-known Sandia Frequency Shift (SFS) IDM while maintaining its islanding detection capability? How to incorporate the perturbations provided by each of DGs in such a way that the negative interference of different IDMs is minimized without the need of any type of communication among the different DGs? It is shown that the proposed techniques are local, scalable and robust against different loading conditions and topology changes. Also, the proposed techniques can successfully distinguish an islanding condition from other disturbances that may occur in power system networks. This work improves the efficiency, reliability and safety of integrated DGs, which presents a necessary advance toward making electric power grids a smart grid.

Notes

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Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Electrical Engineering and Computer Science

Degree Program

Electrical Engineering

URL

http://purl.fcla.edu/fcla/etd/CFE0005295

Length of Campus-only Access

1 year

Access Status

Doctoral Dissertation (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science, Engineering and Computer Science -- Dissertations, Academic

STARS Citation

Al Hosani, Mohamed, "Transient And Distributed Algorithms To Improve Islanding Detection Capability Of Inverter Based Distributed Generation" (2013). Electronic Theses and Dissertations. 2888.
http://stars.library.ucf.edu/etd/2888

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