Development of a Novel Backup Fault Protection Algorithm for Low-Voltage DC Microgrids based on Local Measurements and Chi-square Statistics

Author:

Bui Duong Minh,Le Duy Phuc,Nguyen Hieu Minh

Abstract

A direct-current microgrid (MG) can be susceptible to extremely high fault currents contributed by the output filter capacitors of power converters and can also face protection challenges because of the non-zero crossing of fault currents. In a Low-Voltage Direct Current (LVDC) MG, low-fault-tolerance converters such as boost converters and bidirectional converters mostly require a fast and adaptable fault protection scheme that can detect and clear quickly faults irrespective of a wide range of fault impedances in the system. Several current- and voltage-derivative-based protection methods with communication support have been developed to primarily protect DC MGs due to their high sensitivity and selectivity. Over-current and under-voltage-based protection schemes are mostly suggested as backup protections for the DC MGs. To accurately detect and rapidly clear the faults even in the case of communication failure from the primary protection, this paper proposes a novel backup fault protection scheme with high selectivity, adaptability, and scalability for islanded LVDC MGs based on local measurements along with Chi-square-distribution-based statistics. Specifically, this developed backup protection not only applies a cumulative summation methodology for the locally measured signals to extract derivative and integral characteristics of the current and voltage, but also uses the Chi-square-distribution-based statistics to consistently calculate tripping thresholds for the effective detection of different fault events in the LVDC MG, regardless of variable fault resistances and the communication-link damage. As a result, the proposed backup protection is capable of accurately detecting various DC faults to secondarily protect the source and load branches of the system within the expected time frame of a few milliseconds and has been validated through multiple staged fault tests from an off-grid and ungrounded 1kW and 48VDC MG testbed.

Publisher

Engineering, Technology & Applied Science Research

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3