Unintentional islanding detection

Suman, Mrinal; Kirthiga, M. Venkata

doi:10.1016/b978-0-12-817774-7.00017-x

Cited by 9 publications

(3 citation statements)

References 33 publications

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“…In the passive methods, the system parameters (including voltage, current, impedance, power and frequency) are monitored at the PCC or DG terminals and compared with pre-determined values for islanding detection. The traditional methods are: Rate of Change of Output Power (ROCOP) [174], Rate of Change of Frequency (ROCOF) and Phase jump detection method [184]. Active methods interact with the grid by injecting perturbation signals into the system (including signals variables of voltage, current, harmonic distortion and frequency), and then observing the behaviour of the system.…”

Section: Island Detectionmentioning

confidence: 99%

Grid Forming Inverters: A Review of the State of the Art of Key Elements for Microgrid Operation

et al. 2022

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In the past decade, inverter-integrated energy sources have experienced rapid growth, which leads to operating challenges associated with reduced system inertia and intermittent power generation, which can cause instability and performance issues of the power system. Improved control schemes for inverters are necessary to ensure the stability and resilience of the power system. Grid-forming inverters dampen frequency fluctuations in the power system, while grid-following inverters can aggravate frequency problems with increased penetration. This paper aims at reviewing the role of grid-forming inverters in the power system, including their topology, control strategies, challenges, sizing, and location. In order to facilitate continued research in this field, a comprehensive literature review and classification of the studies are conducted, followed by research gaps and suggestions for future studies.

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Section: Island Detectionmentioning

confidence: 99%

Grid Forming Inverters: A Review of the State of the Art of Key Elements for Microgrid Operation

et al. 2022

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“…It is necessary to state that this contingence can be intentional or unintentional. While the intentional islanding is a powerful tool to ensure power to isolated areas, unintentional islanding has no positive bias and provokes the growing of the THDv rates, electrical accidents, and out-of-phase reclosure [5].…”

Section: Introductionmentioning

confidence: 99%

Implementation and Critical Analysis of the Active Phase Jump with Positive Feedback Anti-Islanding Algorithm

2022

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The protection against the unintentional islanding of Grid-Tied inverters is an important electrical security issue addressed by the main Standards. This concern is justified in face of the fact that unintentional islanding can lead to abrupt variations of voltage and frequency, electrical damages, professional accidents, power quality degradation, and out-of-phase reclosure. In response to the islanding concern, the literature has proposed several Anti-Islanding Protection (AIP) schemes that can be divided in passive and active methods. Many of the active AIP is based on the insertion of some disturbance in the inverter current in order to deviate the frequency out of the allowed thresholds, tripping the inverter internal disconnection system. Thus, the main objective of this paper is to analyze the performance of the Active Phase Jump with Positive Feedback (APJPF) algorithm compared to other well-known frequency drift-based solutions. More than that, this work covers the Non-Detection Zone (NDZ) problem, analyzing its main mapping methodologies and the normative requirements, exposing the minimum normative recommendations a given AIP must reach to be considered functional. The last contributions of this paper are the proposal of a parametrization criterion for the Active Frequency Drift with Pulsating Chopping Factor (AFDPCF) and for the APJPF.

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“…But with the number of distributed generation (DG) systems rising, there is always a possibility of power instability [4] at the grid end, and as a result, protective schemes are required [5]. At times of power mismatch, the DGs may be unintentionally islanded from the grid [6] which may lead to a rapid loss of power, unbalanced frequency, and unregulated voltage, which can severely damage DGs. To limit the damage and avoid unintentional islanding, it is necessary that the operating state of the DGs are monitored and different faults are classified.…”

Section: Introductionmentioning

confidence: 99%

Data Description Technique-Based Islanding Classification for Single-Phase Grid-Connected Photovoltaic System

Haque

Alshareef

Khan

et al. 2020

Sensors

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This paper develops an islanding classification mechanism to overcome the problems of non-detection zones in conventional islanding detection mechanisms. This process is achieved by adapting the support vector-based data description technique with Gaussian radial basis function kernels for islanding and non-islanding events in single phase grid-connected photovoltaic (PV) systems. To overcome the non-detection zone, excess and deficit power imbalance conditions are considered for different loading conditions. These imbalances are characterized by the voltage dip scenario and were subjected to feature extraction for training with the machine learning technique. This is experimentally realized by training the machine learning classifier with different events on a 5 kW grid-connected system. Using the concept of detection and false alarm rates, the performance of the trained classifier is tested for multiple faults and power imbalance conditions. The results showed the effective operation of the classifier with a detection rate of 99.2% and a false alarm rate of 0.2%.

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Unintentional islanding detection

Cited by 9 publications

References 33 publications

Grid Forming Inverters: A Review of the State of the Art of Key Elements for Microgrid Operation

Grid Forming Inverters: A Review of the State of the Art of Key Elements for Microgrid Operation

Implementation and Critical Analysis of the Active Phase Jump with Positive Feedback Anti-Islanding Algorithm

Data Description Technique-Based Islanding Classification for Single-Phase Grid-Connected Photovoltaic System

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