A passive islanding detection strategy for multi-distributed generations

Abd-Elkader, Ahmad G.; Saleh, Saber M.; Eiteba, M.B. Magdi

doi:10.1016/j.ijepes.2018.01.005

Cited by 74 publications

(67 citation statements)

References 27 publications

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“…This method is more accurate and effective than the passive method due to relatively small NDZs, but it has slow response toward the perturbation. In addition, the power quality and system stability may degrade due to the external variable introduced in the system [59]. However, this method requires a remarkably higher cost of implementation [49].…”

Section: Active Methodsmentioning

confidence: 99%

Comparative Study of Different Approaches for Islanding Detection of Distributed Generation Systems

Shrestha

Kattel

Dachhepatic

et al. 2019

ASI

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The issue of unintentional islanding in grid interconnection still remains a challenge in grid-connected, Distributed Generation System (DGS). This study discusses the general overview of popular islanding detection methods. Because of the various Distributed Generation (DG) types, their sizes connected to the distribution networks, and, due to the concern associated with out-of-phase reclosing, anti-islanding continues to be an issue, where no clear solution exists. The passive islanding detection technique is the simplest method to detect the islanding condition which compares the existing parameters of the system having some threshold values. This study first presents an auto-ground approach, which is based on the application of three-phase, short-circuit to the islanded distribution system just to reclose and re-energize the system. After that, the data mining-decision tree algorithm is implemented on a typical distribution system with multiple DGs. The results from both of the techniques have been accomplished and verified by determining the Non-Detection Zone (NDZ), which satisfies the IEEE standards of 2 s execution time. From the analysis, it is concluded that the decision tree approach is effective and highly accurate to detect the islanding state in DGs. These simulations in detail compare the old and new methods, clearly highlighting the progress in the field of islanding detection.

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Section: Active Methodsmentioning

confidence: 99%

Comparative Study of Different Approaches for Islanding Detection of Distributed Generation Systems

Shrestha

Kattel

Dachhepatic

et al. 2019

ASI

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“…(24) where A_CMG is the number of submicrogrids managed autonomously based on PoB, n is the maximum number of submicrogrids in the whole microgrid, Yj is the total number of breaker openings detected at the PoCs, and m is the total number of PoCs in the whole microgrid. Microgrid performance ratio (MGPR) is defined as the ratio of number of submicrogrids managed autonomously to the total number of islanding events detected at the PoC.…”

Section: Probability Of Power Balance and The State Of Probability mentioning

confidence: 99%

“…The angle is negative for any transient event in the microgrid level, and thus only grid side fault was analysed. In Abd-Elkader et al 24 , islanding was performed by opening grid circuit breaker, and there has been unnecessary disconnection of load for reducing the NDZ for lower active power mismatches. For any loss of feeder within the microgrid, the DG is disconnected, and the islanding detection time is 0.28 to 0.25 second.…”

Section: Introductionmentioning

confidence: 99%

A combined islanding detection algorithm for grid connected multiple microgrids for enhanced microgrid utilisation

Radhakrishnan

Ashok

Sunitha

2019

Int Trans Electr Energ Syst

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SUMMARY There is an abundant interest in microgrids due to its innate ability to operate in either utility connected or isolated mode. The existing conventional methods disconnect the individual distributed generators on loss of utility. In this work, a combined islanding detection algorithm at the point of common coupling (PCC) of the whole microgrid is proposed. It detects islanding using islanding detection monitoring factor, rate of change of inverse hyperbolic cosecant function, and voltage at the PCC as the islanding detection elements with the help of phasor measurement units. On detection of islanding event, the whole microgrid is transferred to autonomous mode. Moreover, any fault in the microgrid side which may isolate the distributed generator is detected using dilation and erosion mathematical morphological operators. The algorithm estimates the probability of power balance and probability of islanding duration at the control centre for events within the microgrid. The decision for islanded operation or disconnecting the distributed generator is communicated based on this. The proposed method is tested on a microgrid test system and verified on a section of the realistic local feeder of the Indian utility system. The simulation results indicate that the developed algorithm is quick, reliable, and secure in discriminating between the islanding and nonislanding scenarios for the various cases during both import and export conditions with an accuracy of 100%. It eliminates the nondetection zone completely even during zero power mismatch conditions. With the proposed method, any unnecessary distributed generator outage can be avoided enhancing the microgrid utilisation.

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“…At first, different features are analyzed using signal processing methods and then these features applied to a deep learning-based algorithm to classified islanding and grid connected disturbances. A voltage index has been used in Reference [29] to detect the islanding condition for large power imbalances, also for small power imbalances, the line current measured to disconnect some loads, due to transfer small imbalances to large power mismatches.…”

Section: Introductionmentioning

confidence: 99%

An Effective Passive Islanding Detection Algorithm for Distributed Generations

et al. 2019

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Different issues will be raised and highlighted by emerging distributed generations (DGs) into modern power systems in which the islanding detection is the most important. In the islanding situation, a part of the system which consists of at least one DG, passive grid, and local load, becomes fully separated from the main grid. Several detection methods of islanding have been proposed in recent researches based on measured electrical parameters of the system. However, islanding detection based on local measurements suffers from the non-detection zone (NDZ) and undesirable detection during grid-connected events. This paper proposes a passive islanding detection algorithm for all types of DGs by appropriate combining the measured frequency, voltage, current, and phase angle and their rate of changes at the point of common coupling (PCC). The proposed algorithm detects the islanding situation, even with the exact zero power mismatches. Proposed algorithm discriminates between the islanding situation and non-islanding disturbances, such as short circuit faults, capacitor faults, and load switching in a proper time and without mal-operation. In addition, the performance of the proposed algorithm has been evaluated under different scenarios by performing the algorithm on the IEEE 13-bus distribution system.

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A passive islanding detection strategy for multi-distributed generations

Cited by 74 publications

References 27 publications

Comparative Study of Different Approaches for Islanding Detection of Distributed Generation Systems

Comparative Study of Different Approaches for Islanding Detection of Distributed Generation Systems

A combined islanding detection algorithm for grid connected multiple microgrids for enhanced microgrid utilisation

An Effective Passive Islanding Detection Algorithm for Distributed Generations

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