Filter Extracted Sliding Mode Approach for DC Microgrids

Author:

Yasin Abdul RehmanORCID,Yasin AminaORCID,Riaz MudassarORCID,Ehab Muhammad,Raza AliORCID

Abstract

The advantages offered by DC microgrids, such as elimination of skin effect losses, no requirement of frequency synchronization and high efficiency for power transmission are the major reasons that microgrids have attracted the attention of researchers in the last decade. Moreover, the DC friendly nature of renewable energy resources makes them a perfect choice for integration with DC microgrids, resulting in increased reliability and improved stability. However, in order to integrate renewable energy resources with the DC microgrids, challenges like equal load sharing and voltage regulation of the busbar under diverse varying load conditions are to be addressed. Conventionally, droop control with PI compensation is used to serve this purpose. However, this cascaded scheme results in poor regulation to large load variations and steady state errors. To address this issue, this paper presents a sliding mode control-based approach. Key features of SMC are its ease of implementation, robustness to load variations, and fast dynamic response. The system model is derived and simulated to analyze the stability and performance of the proposed controller. An experimental test bench is developed to demonstrate the effectiveness of SMC against modeled dynamics and is compared with the droop controller. The results show an improvement of 26% and 27.4% in the rise time and settling time, respectively. Robustness of the proposed scheme is also tested by switching it with a step load and an improvement of 40% has been observed.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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