Performance of a new hybrid approach for detection of islanding for inverter-based DGs

Kusuma, G.; Jyothsna, T. R.; Yirrinki, V.V.S.Narayana

doi:10.1016/j.ref.2022.08.001

Cited by 5 publications

(6 citation statements)

References 25 publications

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“…However, the gain of the positive feedback can degrade inverter stability. One form of overcoming this issue is through the bilateral variation of ancillaries parameters, as exposed in [132] or by the adoption of adaptive gains with [174]- [169] or without machine learning techniques.…”

Section: Discussionmentioning

confidence: 99%

“…In [169], is proposed a hybrid method in which the SFS perturbation is activated by the reactive power monitoring. More than that, it uses the Adaptive Particle Swarm Optimization (APSO) in order to calculate the optimum value of the gain K to guarantee correct islanding detection with minimum THDi and to mitigate the stability impacts.…”

Section: ) Sfs Based Hybrid Approachesmentioning

confidence: 99%

“…This subsection, in this context, will cover the timeline evolution of each intelligent AIP approach. It is important to state that some active methods such as [174] and [169] use some kind of Machine Learning (ML) algorithm. However, they will not be included in this section, as the application of ML is limited to the dynamic parameterization of the methods and is not directly related to the islanding decision itself.…”

Section: E Intelligent Passive Techniquesmentioning

confidence: 99%

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Anti-Islanding Techniques for Integration of Inverter-Based Distributed Energy Resources to the Electric Power System

Resende,

Simões,

Freitas

2024

IEEE Access

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The emergence of microgrids and the increasing adoption of Distributed Generation Systems (DGS) have created an opportunity to replace traditional fossil fuels with renewable resources. Such a shift poses security and power quality challenges that must be addressed by academics and industrial research paradigms. Unintentional islanding is an important security concern, as it can result in power quality degradation, electrical hazards, and equipment damage. To address this problem and find efficient solutions, many anti-islanding techniques to detect and eliminate the phenomenon can be found in the specialized literature. These solutions can be classified as passive, active, remote, hybrid, or based on machine learning and signal processing techniques. In this context, this paper provides a comprehensive review of existing antiislanding methods, highlighting their importance in preventing dangerous situations. The review includes a detailed analysis of advantages and limitations found for each method, as well as its suitability for practical applications. The goal is to provide a valuable resource for researchers and practitioners in the field of distributed power systems, enabling them to choose the most appropriate anti-islanding method for their specific needs. Overall, this paper aims to address the challenges posed by unintentional islanding and promote the adoption of renewable energy resources for a more sustainable future.

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Section: Discussionmentioning

confidence: 99%

Section: ) Sfs Based Hybrid Approachesmentioning

confidence: 99%

Section: E Intelligent Passive Techniquesmentioning

confidence: 99%

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Anti-Islanding Techniques for Integration of Inverter-Based Distributed Energy Resources to the Electric Power System

Resende,

Simões,

Freitas

2024

IEEE Access

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“…Furthermore, the approach demonstrated strong performance in multi-DG contexts and weak grid situations, with the ability to differentiate between IS and non-IS eventualities. A hybrid approach is presented in 161 , wherein reactive power monitoring triggers the SFS disturbance. Furthermore, it makes use of APSO to determine the ideal gain K value to minimize stability implications and ensure accurate IS identification with the lowest possible THDi.…”

Section: Islanding Detection Methodsmentioning

confidence: 99%

“…Because they extract features from the signal and use them as input for judgment, these classifiers do away with the difficulty of setting detection thresholds. It is noteworthy that certain active approaches, such as those covered in 124 , 161 , use ML and its algorithms. Though they don't directly affect the IS decision, they are left out of this part because the main goal of using ML is to dynamically parameterize the techniques.…”

Section: Islanding Detection Methodsmentioning

confidence: 99%

Enhancing grid resiliency in distributed energy systems through a comprehensive review and comparative analysis of islanding detection methods

Kulkarni,

Mishra,

Sudabattula

et al. 2024

Sci Rep

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Reduction of fossil fuel usage, clean energy supply, and dependability are all major benefits of integrating distributed energy resources (DER) with electrical utility grid (UG). Nevertheless, there are difficulties with this integration, most notably accidental islanding that puts worker and equipment safety at risk. Islanding detection methods (IDMs) play a critical role in resolving this problem. All IDMs are thoroughly evaluated in this work, which divides them into two categories: local approaches that rely on distributed generation (DG) side monitoring and remote approaches that make use of communication infrastructure. The study offers a comparative evaluation to help choose the most efficient and applicable IDM, supporting well-informed decision-making for the safe and dependable operation of distributed energy systems within electrical distribution networks. IDMs are evaluated based on NDZ outcomes, detection duration, power quality impact, multi-DG operation, suitability, X/R ratio reliance, and efficient functioning.

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Comparison of a Novel AFPSO-SFS & PSO-SFS Approaches for Islanding Protection of Inverter-Based DGs

Gottapu,

Yirrinki,

Siva Ramakrishna

et al. 2024

Electric Power Components and Systems

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Performance of a new hybrid approach for detection of islanding for inverter-based DGs

Cited by 5 publications

References 25 publications

Anti-Islanding Techniques for Integration of Inverter-Based Distributed Energy Resources to the Electric Power System

Anti-Islanding Techniques for Integration of Inverter-Based Distributed Energy Resources to the Electric Power System

Enhancing grid resiliency in distributed energy systems through a comprehensive review and comparative analysis of islanding detection methods

Comparison of a Novel AFPSO-SFS & PSO-SFS Approaches for Islanding Protection of Inverter-Based DGs

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