A Novel Approach for Enhanced Real-Time Event Diagnosis for Grid Connected Microgrid with Multiple Distributed Energy Resources (DERs)

Author:

Singh Bhuwan Pratap1,Goyal Sunil Kumar1,Siddiqui Shahbaz Ahmed2,Shrivastava Divya Rishi3,Singh Satyendra4,A. Alotaibi Majed5,Malik Hasmat6,García Márquez Fausto Pedro7,Afthanorhan Asyraf8

Affiliation:

1. Department of Electrical Engineering, Manipal University Jaipur, Rajasthan, India.

2. Department of Mechatronics Engineering, Manipal University Jaipur, Rajasthan, India.

3. Department of Electrical Engineering, Manipal University Jaipur, Rajasthan, India.

4. Faculty of Electrical Skills, Bhartiya Skill Development University Jaipur, India.

5. Department of Electrical Engineering, College of Engineering, King Saud University, Riyadh, Saudi Arabia.

6. Department of Electrical Power Engineering, Universiti Teknologi Malaysia (UTM), Johor Bahru, Malaysia. & Department of Electrical Engineering, Graphic Era (Deemed to be University), Dehradun, 248002, Uttarakhand, India.

7. Ingenium Research Group, Universidad Castilla-La Mancha, Altagracia,13071, Ciudad Real, Spain.

8. Universiti Sultan Zainal Abidin (UniSZA), Gong Badak, Kuala Terengganu, 21300, Terengganu, Malaysia.

Abstract

Effective microgrid control for system recovery and restoring normal operation necessitates fast event detection and implementation of remedial action (if need arises). However, fast and reliable event detection in microgrids is challenging because of low observability and inconsistencies in measurements. A novel technique is proposed in the present work for the real-time event detection and to identify the various emerging abnormalities in the microgrid. The continuous energy signature using TKEO (Teager-Kaiser Energy Operator) of the continuous varying voltage and frequency signal are extracted through μPMU. REII (Robust Event Identification Index) is constructed from these energy signatures and based on its abrupt post-event deviation from the nominal values an event is flagged in the proposed method. The proposed method is data–driven and only depends on the real-time inputs through μPMUs thus it automatically adapts the uncertainties associated with the intermittent sources of energy in the microgrid under different operating conditions. The traditional event detection techniques fail in identification of abnormalities for a microgrid connected to the transmission systems and equipped with multiple DERs such as PVDG, WG etc. To address this challenge, an integrated microgrid with multiple DERs viz. PVDG, WG and a SG (Synchronous Generator) is first developed in this work. The complexity of simultaneous operation of a static generator i.e. PVDG along with a rotor-based generator such as WG and SG is handled by the modeling the dynamic controllers of PVDG and WG for their frequency and voltage control. The simulation results depict the efficiency, accuracy and robustness of the proposed technique in terms of estimation time, event accuracy and applicability in all types of events. Moreover, the presented methodology is also compared with the four AI/ML based methods to highlight the superiority of the method.

Publisher

Ram Arti Publishers

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