
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
A Differential Sequence Component Protection Scheme for Microgrids With Inverter-Based Distributed Generators

The protection of a microgrid containing inverter- based distributed generators (IBDGs) presents several problems if traditional techniques which rely on the current (fuses and overcurrent relays) are used. A possible solution to these problems is the use of a new type of the relay which takes advantage of the enhanced processing techniques and communication infrastructure, both of which are recently becoming available for power networks application. This paper proposes a new communication-based protection scheme for isolated microgrids where a data mining approach is used to identify the relay settings and parameters. A feature selection technique is implemented to help identify the most relevant electrical features required for the fault detection and to establish the best communication strategy to use between relays. The proposed approach is tested using a MATLAB simulation of a facility scale isolated microgrid embedded with IBDGs. The results show that a differential protection scheme that relies on symmetrical components is the most effective strategy for protecting microgrids with IBDGs.
- MASDAR INSTITUTE OF SCIENCE AND TECHNOLOGY NON PROFIT INSTITUTION United Arab Emirates
- MASDAR INSTITUTE OF SCIENCE AND TECHNOLOGY NON PROFIT INSTITUTION United Arab Emirates
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).206 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
