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Ground Fault Detection Using Pole Differential Current Measurement for 2-Terminal Bipolar HVDC Lines Read chapter Read first chapter

2021 | OriginalPaper | Chapter

A Comprehensive Review of Conventional and Computational Islanding Diagnosis of Distributed Generator in Distribution Network

Authors : Akshat Kumar, Shaik Riyaz, R. N. Mahanty

Published in: Recent Advances in Power Systems

Publisher: Springer Singapore

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Abstract

Sustainable energy generation methods are considered extremely beneficial for resolving future energy and environmental issues. Distributed generation (DG) is one such methodology to utilize renewable resources. Grid integration with various types of distributed sources such as wind, hydro, PV etc. can enhance energy efficiency and solve energy crisis problems. Distributed generators may work under both grid-connected and islanding modes. Islanding mode suffers certain challenges. Swift and precise islanding detection is key for the successful operation of distributed generators in distributed network. Various islanding techniques based upon passive, communication, active and hybrid have been put forward. Despite that each methodology has certain defects which may cause erroneous islanding diagnosis. These days’ intelligent methodologies because of their robust and flexible behavior in dealing with the complex non-linear system are a viable alternative which can resolve this issue. This paper presents comparative overview of a comprehensive analysis of conventional and computational intelligent techniques employed for islanding diagnosis of DG.

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previous chapter Optimal Share of DG and DSTATCOM in Distribution Network Using Firefly Algorithm
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Metadata
Title
A Comprehensive Review of Conventional and Computational Islanding Diagnosis of Distributed Generator in Distribution Network
Authors
Akshat Kumar
Shaik Riyaz
R. N. Mahanty
Copyright Year
2021
Publisher
Springer Singapore
Book
Recent Advances in Power Systems

Print ISBN: 978-981-15-7993-6

Electronic ISBN: 978-981-15-7994-3

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-7994-3_47