A Probabilistic Approach for the Evaluation of Fault Detection Schemes in Microgrids

Eslami, Reza; Sadeghi, S.H.H.; Abyaneh, Hossein Askarian

doi:10.48084/etasr.1472

Cited by 15 publications

(9 citation statements)

References 20 publications

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“…The non-fault signal data represent normal switching, load switching, and capacitance switching, while the fault signal data represents the HIF [27]. The data set, which is obtained from various cases taken into account and is shown in Table I, is used in the proposed fault and non-fault signal detection method [28]. A total of 1500 HIF cases and 1100 non-HIF cases, such as linear load switching, Non-Linear Load (NLL) switching, and capacitor switching, were considered (Table I).…”

Section: A Fault and Non-fault Signal Datamentioning

confidence: 99%

A Deep Learning Technique for Detecting High Impedance Faults in Medium Voltage Distribution Networks

Lavanya¹,

Prabakaran²,

Kumar³

2022

Eng. Technol. Appl. Sci. Res.

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Utility companies always struggle with the High Impedance Fault (HIF) in the electrical distribution systems. In this article, the current signal is seen in situations involving 10,400 different samples, with and without HIF, like linear, non-linear load, and capacitance switching. A better method that processes signals very fast and with low sample rates, requiring less memory and computational labor, is demonstrated by Mathematical Morphology (MM). For HIF identification, Deep Convolution Neural Networks (DCNNs) are being developed. This paper presents a novel method for signal processing with low sample rates, high signal processing speed, and low computational and memory requirements. The suggested six-layer DCNN is compared with other models, such as the four-layer and eight-layer DCNN models and the results are discussed.

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Section: A Fault and Non-fault Signal Datamentioning

confidence: 99%

A Deep Learning Technique for Detecting High Impedance Faults in Medium Voltage Distribution Networks

Lavanya¹,

Prabakaran²,

Kumar³

2022

Eng. Technol. Appl. Sci. Res.

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“…Fuzzy logic is used to define the frequency droop coefficient. Authors in [6] proposed and evaluated a fault detection method which is independent of the MG topology. Authors in [7] proposed a decentralized controller with low bandwidth communication to enhance high reliability, low voltage regulation, and equal load sharing.…”

Section: Imentioning

confidence: 99%

Hierarchical Control of a Low Voltage DC Microgrid with Coordinated Power Management Strategies

Muchande¹,

Thale²

2022

Eng. Technol. Appl. Sci. Res.

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A microgrid consists of a cluster of renewable energy sources, energy storage elements, and loads. One of the main objectives of a microgrid is to provide reliable and high-quality power to the loads. Under normal operating conditions, this is achieved through suitable Power Management Strategy (PMS). However, under emergency conditions, such as the failure of any source, overloads, or faults, the PMS may not be able to retain the microgrid in operating conditions. Any emergency condition may demand a significant change in control and coordination between various subsystems of the microgrid to survive and continue the operation. This feature makes a microgrid "a fault resilient" system as visualized in its objectives. This paper proposes a novel Coordinated Power Management (CPM) strategy based on three-layer hierarchical control for an autonomous Low Voltage DC (LVDC) microgrid. The proposed CPM strategy ensures the continuation of the microgrid operation under normal and emergency conditions. An emergency control layer is established to extend the microgrid operation during an emergency condition. The performance of the proposed control scheme is validated through simulation and experimental results.

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“…Moreover, there are other methods employed for protection using different techniques such as wavelets [ 25 , 26 , 27 ], fuzzy logic [ 28 ], recursive least square [ 29 , 30 ], differential phase angle [ 31 ], s-transform [ 32 ], power spectral density and transform [ 33 ], deep belief network [ 34 ], Hilbert-Huang transform [ 35 ]. However, these techniques require a complex computational process and a relatively high cost of implementation.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Smart THD-Based Fault Protection Techniques for Distribution Networks

Hanaineh

Matas

Guerrero

2023

Sensors

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The integration of Distributed Generators (DGs) into distribution systems (DSs) leads to more reliable and efficient power delivery for customers. However, the possibility of bi-directional power flow creates new technical problems for protection schemes. This poses a threat to conventional strategies because the relay settings have to be adjusted depending on the network topology and operational mode. As a solution, it is important to develop novel fault protection techniques to ensure reliable protection and avoid unnecessary tripping. In this regard, Total Harmonic Distortion (THD) can be used as a key parameter for evaluating the grid’s waveform quality during fault events. This paper presents a comparison between two DS protection strategies that employ THD levels, estimated amplitude voltages, and zero-sequence components as instantaneous indicators during the faults that function as a kind of fault sensor to detect, identify, and isolate faults. The first method uses a Multiple Second Order Generalized Integrator (MSOGI) to obtain the estimated variables, whereas the second method uses a single SOGI for the same purpose (SOGI-THD). Both methods rely on communication lines between protective devices (PDs) to facilitate coordinated protection. The effectiveness of these methods is assessed by using simulations in MATLAB/Simulink considering various factors such as different types of faults and DG penetrations, different fault resistances and fault locations in the proposed network. Moreover, the performance of these methods is compared with conventional overcurrent and differential protections. The results show that the SOGI-THD method is highly effective in detecting and isolating faults with a time interval of 6–8.5 ms using only three SOGIs while requiring only 447 processor cycles for execution. In comparison to other protection methods, the SOGI-THD method exhibits a faster response time and a lower computational burden. Furthermore, the SOGI-THD method is robust to harmonic distortion, as it considers pre-existing harmonic content before the fault and avoids interference with the fault detection process.

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A Probabilistic Approach for the Evaluation of Fault Detection Schemes in Microgrids

Cited by 15 publications

References 20 publications

A Deep Learning Technique for Detecting High Impedance Faults in Medium Voltage Distribution Networks

A Deep Learning Technique for Detecting High Impedance Faults in Medium Voltage Distribution Networks

Hierarchical Control of a Low Voltage DC Microgrid with Coordinated Power Management Strategies

A Comparative Study of Smart THD-Based Fault Protection Techniques for Distribution Networks

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