LAPSE:2023.7617
Published Article

LAPSE:2023.7617
Optimal Ultra-Local Model Control Integrated with Load Frequency Control of Renewable Energy Sources Based Microgrids
February 24, 2023
Abstract
Since renewable energy sources (RESs) have an intermittent nature, conventional secondary frequency control, i.e., load frequency control (LFC), cannot mitigate the effects of variations in system frequency. Thus, this paper proposes incorporating ultralocal model (ULM) control into LFC to enhance microgrid (µG) frequency stability. ULM controllers are regarded as model-free controllers that yield high rejection rates for disturbances caused by load/RES uncertainties. Typically, ULM parameters are set using trial-and-error methods, which makes it difficult to determine the optimal values that will provide the best system performance and stability. To address this issue, the African vultures optimization algorithm (AVOA) was applied to fine-tune the ULM parameters, thereby stabilizing the system frequency despite different disturbances. The proposed LFC controller was compared with the traditional secondary controller based on an integral controller to prove its superior performance. For several contingencies, the simulation results demonstrated that the proposed controller based on the optimal ULM coupled with LFC could significantly promote RESs into the µG.
Since renewable energy sources (RESs) have an intermittent nature, conventional secondary frequency control, i.e., load frequency control (LFC), cannot mitigate the effects of variations in system frequency. Thus, this paper proposes incorporating ultralocal model (ULM) control into LFC to enhance microgrid (µG) frequency stability. ULM controllers are regarded as model-free controllers that yield high rejection rates for disturbances caused by load/RES uncertainties. Typically, ULM parameters are set using trial-and-error methods, which makes it difficult to determine the optimal values that will provide the best system performance and stability. To address this issue, the African vultures optimization algorithm (AVOA) was applied to fine-tune the ULM parameters, thereby stabilizing the system frequency despite different disturbances. The proposed LFC controller was compared with the traditional secondary controller based on an integral controller to prove its superior performance. For several contingencies, the simulation results demonstrated that the proposed controller based on the optimal ULM coupled with LFC could significantly promote RESs into the µG.
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Keywords
African vultures optimization approach, high-penetration renewable energy sources (RESs), load frequency control (LFC), microgrid (µG), ultralocal model (ULM) control
Subject
Suggested Citation
Bakeer A, Magdy G, Chub A, Jurado F, Rihan M. Optimal Ultra-Local Model Control Integrated with Load Frequency Control of Renewable Energy Sources Based Microgrids. (2023). LAPSE:2023.7617
Author Affiliations
Bakeer A: Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt [ORCID]
Magdy G: Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt; Department of Electrical Engineering, University of Jaén, 23700 Linares, Spain [ORCID]
Chub A: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Jurado F: Department of Electrical Engineering, University of Jaén, 23700 Linares, Spain [ORCID]
Rihan M: Electrical Engineering Department, Faculty of Engineering, South Valley University, Qena 83521, Egypt [ORCID]
Magdy G: Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt; Department of Electrical Engineering, University of Jaén, 23700 Linares, Spain [ORCID]
Chub A: Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia [ORCID]
Jurado F: Department of Electrical Engineering, University of Jaén, 23700 Linares, Spain [ORCID]
Rihan M: Electrical Engineering Department, Faculty of Engineering, South Valley University, Qena 83521, Egypt [ORCID]
Journal Name
Energies
Volume
15
Issue
23
First Page
9177
Year
2022
Publication Date
2022-12-03
ISSN
1996-1073
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Original Submission
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PII: en15239177, Publication Type: Journal Article
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LAPSE:2023.7617
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https://doi.org/10.3390/en15239177
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Feb 24, 2023
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