Hierarchical Fuzzy Framework for EV Supported Islanded Microgrid Frequency Stabilization

This article delves into the intricate challenge of frequency stabilization within islanded microgrids (IMGs), particularly exacerbated by the integration of low-inertia renewable power generations. A hierarchical control strategy is proposed, comprising a fuzzy rule-based controller, a two-degree-o...

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Main Authors: Abdul Latif, S. M. Suhail Hussain, Ahmed Al-Durra, Atif Iqbal
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Journal of the Industrial Electronics Society
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10585315/
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author Abdul Latif
S. M. Suhail Hussain
Ahmed Al-Durra
Atif Iqbal
author_facet Abdul Latif
S. M. Suhail Hussain
Ahmed Al-Durra
Atif Iqbal
author_sort Abdul Latif
collection DOAJ
description This article delves into the intricate challenge of frequency stabilization within islanded microgrids (IMGs), particularly exacerbated by the integration of low-inertia renewable power generations. A hierarchical control strategy is proposed, comprising a fuzzy rule-based controller, a two-degree-of-freedom fractional-order PI controller, and a proportional resonant controller. The bolstering of frequency stabilization is achieved by the integration of aggregated electric vehicle storage into the IMG. Adaptive tuning of the fuzzy rule-based load frequency controller's parameters is facilitated by a novel quasi-oppositional prairie dog technique (QOPDT), developed within this study. A comprehensive comparison is conducted between the efficacy of the QOPDT technique and various other optimization methods. Significant improvements in system frequency stability across diverse scenarios are observed with the adoption of the QOPDT-based controller, as evidenced by qualitative assessment. Furthermore, the investigation extends to consider the impact of time-varying delay on the integrated electric vehicle system, broadening the scope of the investigation. Validation of the effectiveness and practicality of the proposed control framework is undertaken utilizing the real-time OPAL-RT 5700 testbed platform.
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institution Kabale University
issn 2644-1284
language English
publishDate 2024-01-01
publisher IEEE
record_format Article
series IEEE Open Journal of the Industrial Electronics Society
spelling doaj-art-fb2f1de9231e4568926a8b8364258c022025-01-17T00:00:48ZengIEEEIEEE Open Journal of the Industrial Electronics Society2644-12842024-01-01570472110.1109/OJIES.2024.342166910585315Hierarchical Fuzzy Framework for EV Supported Islanded Microgrid Frequency StabilizationAbdul Latif0S. M. Suhail Hussain1https://orcid.org/0000-0002-7779-8140Ahmed Al-Durra2https://orcid.org/0000-0002-6629-5134Atif Iqbal3https://orcid.org/0000-0002-6932-4367Advanced Power and Energy Center, EECS Department, Khalifa University, Abu Dhabi, UAEElectrical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi ArabiaAdvanced Power and Energy Center, EECS Department, Khalifa University, Abu Dhabi, UAEElectrical Engineering Department, Qatar University, Doha, QatarThis article delves into the intricate challenge of frequency stabilization within islanded microgrids (IMGs), particularly exacerbated by the integration of low-inertia renewable power generations. A hierarchical control strategy is proposed, comprising a fuzzy rule-based controller, a two-degree-of-freedom fractional-order PI controller, and a proportional resonant controller. The bolstering of frequency stabilization is achieved by the integration of aggregated electric vehicle storage into the IMG. Adaptive tuning of the fuzzy rule-based load frequency controller's parameters is facilitated by a novel quasi-oppositional prairie dog technique (QOPDT), developed within this study. A comprehensive comparison is conducted between the efficacy of the QOPDT technique and various other optimization methods. Significant improvements in system frequency stability across diverse scenarios are observed with the adoption of the QOPDT-based controller, as evidenced by qualitative assessment. Furthermore, the investigation extends to consider the impact of time-varying delay on the integrated electric vehicle system, broadening the scope of the investigation. Validation of the effectiveness and practicality of the proposed control framework is undertaken utilizing the real-time OPAL-RT 5700 testbed platform.https://ieeexplore.ieee.org/document/10585315/Electric vehicle (EV)fuzzy rule-based control (FRC)load frequency regulation (LFR)quasi-oppositional prairie dog technique (QOPDT)communication delay
spellingShingle Abdul Latif
S. M. Suhail Hussain
Ahmed Al-Durra
Atif Iqbal
Hierarchical Fuzzy Framework for EV Supported Islanded Microgrid Frequency Stabilization
IEEE Open Journal of the Industrial Electronics Society
Electric vehicle (EV)
fuzzy rule-based control (FRC)
load frequency regulation (LFR)
quasi-oppositional prairie dog technique (QOPDT)
communication delay
title Hierarchical Fuzzy Framework for EV Supported Islanded Microgrid Frequency Stabilization
title_full Hierarchical Fuzzy Framework for EV Supported Islanded Microgrid Frequency Stabilization
title_fullStr Hierarchical Fuzzy Framework for EV Supported Islanded Microgrid Frequency Stabilization
title_full_unstemmed Hierarchical Fuzzy Framework for EV Supported Islanded Microgrid Frequency Stabilization
title_short Hierarchical Fuzzy Framework for EV Supported Islanded Microgrid Frequency Stabilization
title_sort hierarchical fuzzy framework for ev supported islanded microgrid frequency stabilization
topic Electric vehicle (EV)
fuzzy rule-based control (FRC)
load frequency regulation (LFR)
quasi-oppositional prairie dog technique (QOPDT)
communication delay
url https://ieeexplore.ieee.org/document/10585315/
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AT smsuhailhussain hierarchicalfuzzyframeworkforevsupportedislandedmicrogridfrequencystabilization
AT ahmedaldurra hierarchicalfuzzyframeworkforevsupportedislandedmicrogridfrequencystabilization
AT atifiqbal hierarchicalfuzzyframeworkforevsupportedislandedmicrogridfrequencystabilization