Islanding detection of distributed generation in presence of fault events

The investiture in Distributed Generations (DGs) technologies have begun to monopolies transmission system's architecture instantaneously after announcing its liberation and deregulation of the energy market to the public. Such movement has propelled vicious competitions among power generation...

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Bibliographic Details
Published in:TENCON 2017 - 2017 IEEE Region 10 Conference pp. 1919 - 1924
Main Authors: Ramadan, Muhammad, Hao, Edwin Chiang Jia, Logenthiran, T., Naayagi, R. T., Woo, W. L.
Format: Conference Proceeding
Language:English
Published: IEEE 01-11-2017
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Summary:The investiture in Distributed Generations (DGs) technologies have begun to monopolies transmission system's architecture instantaneously after announcing its liberation and deregulation of the energy market to the public. Such movement has propelled vicious competitions among power generation companies to initiate superior innovations in meeting consumers' needs, administering high power quality yet economical. With the integration of DG technologies, power grid operations have dynamically benefited from such commendable services which apprehend power failures from transpiring; securing power quality, accommodating capricious demand curve, fault compensatory applications and other auxiliary services. Subsequently, the presence of DGs have revolutionised power grid management to conceive off-grid and self-sustaining criterion where microgrid/islanding topology adaptations are commonly affiliated. However, employing islanding-mode proposition, potential exposure to unplanned islanded paradox due to ineffectual detection control scheme is tenable. Prolonged accidental islanding-mode operation can afflict undesirable annihilation of utility's resources and deemed economically unprofitable which results in compromising safety and serviceability. Thus, this paper demonstrates contrasting dynamics in adopting either passive or active islanding detection approaches based on selected algorithms; Over/Under Voltage and Frequency detection (Passive) or Active Frequency Drift and Sandia Frequency Shift detection (Active). Comparisons of the proposed methodologies are presented using MATLAB/Simulink to view superiority and applicability in determining the status of the grid's operating mode.
ISSN:2159-3450
DOI:10.1109/TENCON.2017.8228172