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Articles de revues sur le sujet « Microgrids Fault detection »

Auteur : Grafiati

Publié le 7 juin 2025

Mis à jour le 2 août 2025

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1

Modi, Sangeeta, and Pasumarthi Usha. "Microgrid confrontations and smart resolution." International Journal of Power Electronics and Drive Systems (IJPEDS) 15, no. 3 (2024): 1446. http://dx.doi.org/10.11591/ijpeds.v15.i3.pp1446-1455.

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Hybrid microgrids are emerging as an alternate solution for connecting distributed AC/DC energy resources. Effective fault detection and response are highly essential for the microgrid controller (MGC) for protection of the microgrid. The conventional schemes of protection cannot be applied in microgrid because of dynamic conduct and unconventional topology of the microgrids. It is highly essential to develop an appropriate scheme for detection and classification of faults for the effective protection of microgrids. In this paper, a novel and smart solution based on the application of an intel

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Modi, Sangeeta, and Pasumarthi Usha. "Microgrid confrontations and smart resolution." International Journal of Power Electronics and Drive Systems (IJPEDS) 15, no. 3 (2024): 1446–55. https://doi.org/10.11591/ijpeds.v15.i3.pp1446-1455.

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Hybrid microgrids are emerging as an alternate solution for connecting distributed AC/DC energy resources. Effective fault detection and response are highly essential for the microgrid controller (MGC) for protection of the microgrid. The conventional schemes of protection cannot be applied in microgrid because of dynamic conduct and unconventional topology of the microgrids. It is highly essential to develop an appropriate scheme for detection and classification of faults for the effective protection of microgrids. In this paper, a novel and smart solution based on the application of an intel

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Nasare, Ruchita, Sakshi Garad, Sakshi Patil, and Nikita Besekar. "Fault Detection and Isolation ofDCMicro-Grid." April-May 2023, no. 33 (May 25, 2023): 31–39. http://dx.doi.org/10.55529/jeet.33.31.39.

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In a microgrid, faults can lead to voltage instability, which can produce voltage sags, swells, or even a full collapse of the voltage. This may result in electrical equipment damage and interfere with the microgrid's operation. Faults can also produce safety risks including fire, explosion, or electrocution, which can endanger employees and harm equipment. By isolating or shutting down the system when a malfunction is found, the danger of harm or injury is reduced. The purpose of fault isolation and detection in a DC microgrid is to guarantee the microgrid's dependability and safety. The micr

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Mehmood, Musfira, Syed Basit Ali Bukhari, Abdullah Altamimi, et al. "Microgrid Protection Using Magneto-Resistive Sensors and Superimposed Reactive Energy." Sustainability 15, no. 1 (2022): 599. http://dx.doi.org/10.3390/su15010599.

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The concept of microgrids has emerged as an effective way to integrate distributed energy resources (DERs) into distribution networks. The presence of DERs in microgrids leads to challenges in the formulation of protection for microgrids. Protection problems arise in a microgrid due to varying fault current levels in different operating scenarios. In order to overcome the practical challenges arising from varying fault current levels leading to short-circuit faults in microgrids, this paper proposes a MagnetoResistive (MR) sensors-based protection scheme, with fault localization through Superi

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Salehimehr, Sirus, Seyed Mahdi Miraftabzadeh, and Morris Brenna. "A Novel Machine Learning-Based Approach for Fault Detection and Location in Low-Voltage DC Microgrids." Sustainability 16, no. 7 (2024): 2821. http://dx.doi.org/10.3390/su16072821.

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DC microgrids have gained significant attention in recent years due to their potential to enhance energy efficiency, integrate renewable energy sources, and improve the resilience of power distribution systems. However, the reliable operation of DC microgrids relies on the early detection and location of faults to ensure an uninterrupted power supply. This paper aims to develop fast and reliable fault detection and location mechanisms for DC microgrids, thereby enhancing operational efficiency, minimizing environmental impact, and contributing to resource conservation and sustainability goals.

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ADEYEYE, Adebimpe O., Abraham O. AMOLE, and Oluwaseun A. BAMIDO. "ANALYSIS OF RECURRENT NEURAL NETWORK AND LONG-SHORT TERM MEMORY BASED FAULT DETECTION SYSTEMS FOR MICROGRID APPLICATIONS." OAUSTECH Journal of Engineering and Intelligent Technology 1, no. 1 (2025): 1–14. https://doi.org/10.36108/ojeit/5202.10.0110.

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Microgrids are modern small-scale versions of centralized electricity systems, and due to their complexity and the significant impact of financial loss or damage in the event of a fault, the need for an effective method of fault detection is crucial. This study addressed the critical need for effective fault detection and classification to ensure timely system restoration in the vent of fault. The investigation was based on design and simulation of a microgrid model, strategically engineered to manifest fault scenarios such as varying transient faults to different types of short circuit faults

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Chen, Yong, Ruixiong Yang, Yingjie Zeng, and Shuping Gao. "Arc fault detection method for DC microgrid based on multiple features." Journal of Physics: Conference Series 2935, no. 1 (2025): 012006. https://doi.org/10.1088/1742-6596/2935/1/012006.

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Abstract DC microgrids can improve energy structure change and enhance the use of new energy sources. However, it is challenging to find series arcs in DC microgrid systems. In order to detect series arc faults in DC microgrids, this study suggests a multi-feature based approach. By calculating the standard deviation of the system arc current, the root mean square(RMS) of the d5 wavelet coefficients and the marginal spectral eigenfrequency amplitude, a triple fault criterion is constituted. Then the threshold comparison weighting method is utilized to achieve fault identification. Finally, the

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Dutt, Amit, and G. Karuna. "Machine learning approaches for fault detection in renewable microgrids." MATEC Web of Conferences 392 (2024): 01192. http://dx.doi.org/10.1051/matecconf/202439201192.

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This study focuses on investigating and using machine learning (ML) methods to identify faults in renewable microgrids. It highlights the difficulties and intricacies associated with these dynamic energy systems. The examination of real-world data obtained from solar and wind power production, battery storage status, fault signals, and machine learning model performance highlights the complex nature of fault detection techniques in renewable microgrids. An analysis of data on renewable energy production demonstrates oscillations in the outputs of solar and wind power, highlighting differences

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Cepeda, Cristian, Cesar Orozco-Henao, Winston Percybrooks, et al. "Intelligent Fault Detection System for Microgrids." Energies 13, no. 5 (2020): 1223. http://dx.doi.org/10.3390/en13051223.

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The dynamic features of microgrid operation, such as on-grid/off-grid operation mode, the intermittency of distributed generators, and its dynamic topology due to its ability to reconfigure itself, cause misfiring of conventional protection schemes. To solve this issue, adaptive protection schemes that use robust communication systems have been proposed for the protection of microgrids. However, the cost of this solution is significantly high. This paper presented an intelligent fault detection (FD) system for microgrids on the basis of local measurements and machine learning (ML) techniques.

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Srinivas, Nirupama P., and Sangeeta Modi. "A Memory Based Current Algorithm for Pole-to-Pole Fault Detection in Microgrids." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 365–77. http://dx.doi.org/10.22214/ijraset.2022.42182.

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Abstract: The world’s growing attention to sustainable energy and development can be causal to the recently observed disrupt in the existing global power system networks. Moreover, an additional incentive towards this change are the challenges associated with the traditional power grid, including its rigid structure, aging architecture, and ecologically profligate nature. Modern power systems have observed a rapidly growing trend of decentralized energy generation in the recent past. A prominent structure incorporating decentralized energy generation and renewable energy are microgrids. While

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Modi, Sangeeta. "Microgrid Protection and Fault Analysis." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (2022): 4501–12. http://dx.doi.org/10.22214/ijraset.2022.44163.

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Abstract: Microgrid is an active distribution network. It can be operated in various modes of operation such as grid connected mode and islanded mode. Integration of distributed generation can provide solution to the power crisis over the globe. But there are various challenges involved in integration of microgrids to the conventional grid. One of the major challenges in the implementation of microgrid is protection of the microgrid. Very little attention has been paid towards microgrids protection which is highly required to ensure safety and reliability of the overall system. In this paper ,

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Dutt, Amit, M. N. Sandhya Rani, Manbir Singh Bisht, Manisha Chandna, and Abhishek Singla. "Machine Learning Approaches for Fault Detection in Renewable Microgrids." E3S Web of Conferences 511 (2024): 01030. http://dx.doi.org/10.1051/e3sconf/202451101030.

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This paper presents a novel use of machine learning techniques for identifying faults in renewable microgrids within the field of decentralized energy systems. The study investigates the effectiveness of machine learning models in identifying abnormalities in dynamic and variable microgrid environments. It utilizes a comprehensive dataset that includes parameters such as solar, wind, and hydro power generation, energy storage status, and fault indicators. The investigation demonstrates a notable 94% precision in identifying faults, highlighting the superiority of machine learning compared to c

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Abdali, Ali, Kazem Mazlumi, and Josep M. Guerrero. "Integrated Control and Protection Architecture for Islanded PV-Battery DC Microgrids: Design, Analysis and Experimental Verification." Applied Sciences 10, no. 24 (2020): 8847. http://dx.doi.org/10.3390/app10248847.

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Direct current (dc) microgrids have gained significant interest in research due to dc generation/storage technologies—such as photovoltaics (PV) and batteries—increasing performance and reducing in cost. However, proper protection and control systems are critical in order to make dc microgrids feasible. This paper aims to propose a novel integrated control and protection scheme by using the state-dependent Riccati equation (SDRE) method for PV-battery based islanded dc microgrids. The dc microgrid under study consists of photovoltaic (PV) generation, a battery energy storage system (BESS), a c

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Grcić, Ivan, Hrvoje Pandžić, and Damir Novosel. "Fault Detection in DC Microgrids Using Short-Time Fourier Transform." Energies 14, no. 2 (2021): 277. http://dx.doi.org/10.3390/en14020277.

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Fault detection in microgrids presents a strong technical challenge due to the dynamic operating conditions. Changing the power generation and load impacts the current magnitude and direction, which has an adverse effect on the microgrid protection scheme. To address this problem, this paper addresses a field-transform-based fault detection method immune to the microgrid conditions. The faults are simulated via a Matlab/Simulink model of the grid-connected photovoltaics-based DC microgrid with battery energy storage. Short-time Fourier transform is applied to the fault time signal to obtain a

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Al Hassan, Hashim, Andrew Reiman, Gregory Reed, Zhi-Hong Mao, and Brandon Grainger. "Model-Based Fault Detection of Inverter-Based Microgrids and a Mathematical Framework to Analyze and Avoid Nuisance Tripping and Blinding Scenarios." Energies 11, no. 8 (2018): 2152. http://dx.doi.org/10.3390/en11082152.

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Traditional protection methods such as over-current or under-voltage methods are unreliable in inverter-based microgrid applications. This is primarily due to low fault current levels because of power electronic interfaces to the distributed energy resources (DER), and IEEE1547 low-voltage-ride-through (LVRT) requirements for renewables in microgrids. However, when faults occur in a microgrid feeder, system changes occur which manipulate the internal circuit structure altering the system dynamic relationships. This observation establishes the basis for a proposed, novel, model-based, communica

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Lee, Kyung-Min, and Chul-Won Park. "Ground Fault Detection Using Hybrid Method in IT System LVDC Microgrid." Energies 13, no. 10 (2020): 2606. http://dx.doi.org/10.3390/en13102606.

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Low voltage direct current (LVDC) microgrid systems have many advantages over low voltage alternating current (LVAC) systems. Furthermore, LVDC microgrids are growing in use because they are easy to link to distributed energy resources (DER) and energy storage systems (ESS), etc. Currently, IT system LVDC microgrids are widely used in direct current (DC) railways, hospitals, photovoltaic (PV) systems, and so on. When a ground fault occurs in an IT system LVDC microgrid, the ground fault may not be detected because the fault current is very small and there is no current path. In this paper, gro

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Bui, Duong Minh, Shi-Lin Chen, Keng-Yu Lien, and Jheng-Lun Jiang. "A Generalised Fault Protection Structure Proposed for Uni-grounded Low-Voltage AC Microgrids." International Journal of Emerging Electric Power Systems 17, no. 2 (2016): 69–89. http://dx.doi.org/10.1515/ijeeps-2015-0151.

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Abstract This paper presents three main configurations of uni-grounded low-voltage AC microgrids. Transient situations of a uni-grounded low-voltage (LV) AC microgrid (MG) are simulated through various fault tests and operation transition tests between grid-connected and islanded modes. Based on transient simulation results, available fault protection methods are proposed for main and back-up protection of a uni-grounded AC microgrid. In addition, concept of a generalised fault protection structure of uni-grounded LVAC MGs is mentioned in the paper. As a result, main contributions of the paper

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Hosseinzadeh, Mehdi, and Farzad Rajaei Salmasi. "Islanding Fault Detection in Microgrids—A Survey." Energies 13, no. 13 (2020): 3479. http://dx.doi.org/10.3390/en13133479.

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This paper provides an overview of islanding fault detection in microgrids. Islanding fault is a condition in which the microgrid gets disconnected from the microgrid unintentionally due to any fault in the utility grid. This paper surveys the extensive literature concerning the development of islanding fault detection techniques which can be classified into remote and local techniques, where the local techniques can be further classified as passive, active, and hybrid. Various detection methods in each class are studied, and advantages and disadvantages of each method are discussed. A compreh

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Huiyin, Cai, and Li Zhenyu. "Short-circuit Fault Detection in Low-voltage DC Microgrids Based on Improved Current Change Rate." Journal of Physics: Conference Series 2564, no. 1 (2023): 012027. http://dx.doi.org/10.1088/1742-6596/2564/1/012027.

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Abstract Along with the explosion of new energy sources, DC microgrid has obvious advantages as well as better development paths, but reliable fault detection is still one of the key issues to be solved for DC microgrid. The fault current characteristics are analyzed by a fault RLC equivalent circuit, and the characteristics at different fault location points are further analyzed on the independent DC microgrid model composed of a PV generation unit, an energy storage unit, and a load unit. A fault detection method based on the improved current change rate is proposed by combining the current

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Wang, Deming, Fei Li, and Yingliang Li. "A Communication-Assisted Distance Protection for AC Microgrids considering the Fault-Ride-Through Requirements of Distributed Generators." International Journal of Energy Research 2023 (December 16, 2023): 1–13. http://dx.doi.org/10.1155/2023/2000611.

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The conventional overcurrent protection is ineffective in isolating faults in microgrids due to the low fault current levels contributed by inverter-interfaced distributed generations (IIDGs). To extend the microgrid protection methods, the distance protection is considered as a common alternative to detect faults. However, the fault-ride-through (FRT) requirements and the high impedance fault (HIF) detection challenge the application of the conventional distance protection. To solve the two problems, a new inverse-time distance (ITD) protection for medium-voltage AC microgrids was proposed in

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Bayati, Navid, and Mehdi Savaghebi. "Protection Systems for DC Shipboard Microgrids." Energies 14, no. 17 (2021): 5319. http://dx.doi.org/10.3390/en14175319.

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In recent years, shipboard microgrids (MGs) have become more flexible, efficient, and reliable. The next generations of future shipboards are required to be equipped with more focuses on energy storage systems to provide all-electric shipboards. Therefore, the shipboards must be very reliable to ensure the operation of all parts of the system. A reliable shipboard MG should be protected from system faults through protection selectivity to minimize the impact of faults and facilitate detection and location of faulty zones with the highest accuracy and speed. It is necessary to have an across-th

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Forouzesh, Alireza, Mohammad S. Golsorkhi, Mehdi Savaghebi, and Mehdi Baharizadeh. "Support Vector Machine Based Fault Location Identification in Microgrids Using Interharmonic Injection." Energies 14, no. 8 (2021): 2317. http://dx.doi.org/10.3390/en14082317.

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This paper proposes an algorithm for detection and identification of the location of short circuit faults in islanded AC microgrids (MGs) with meshed topology. Considering the low level of fault current and dependency of the current angle on the control strategies, the legacy overcurrent protection schemes are not effective in in islanded MGs. To overcome this issue, the proposed algorithm detects faults based on the rms voltages of the distributed energy resources (DERs) by means of support vector machine classifiers. Upon detection of a fault, the DER which is electrically closest to the fau

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Modi, Sangeeta, and P. Usha. "Microgrid Protection Challenges and Solution." IOP Conference Series: Materials Science and Engineering 1295, no. 1 (2023): 012014. http://dx.doi.org/10.1088/1757-899x/1295/1/012014.

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Abstract Microgrids are embryonic as inspiring solution to the various concerns such as environmental, economic, depletion of the resources for the fuel availability and power mismatch. Microgrids are going to become one of the core components of the upcoming power system. So, it is essential to understand various issues and challenges in microgrid. Power management, constant voltage and frequency, control of various distributed generators and Protection of the microgrid are major areas of concern. Not much work has been done on the protection side of the microgrid. Detecting fault and obtaini

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Li, Yijin, Jianhua Lin, Geng Niu, Ming Wu, and Xuteng Wei. "A Hilbert–Huang Transform-Based Adaptive Fault Detection and Classification Method for Microgrids." Energies 14, no. 16 (2021): 5040. http://dx.doi.org/10.3390/en14165040.

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Fault detection in microgrids is of great significance for power systems’ safety and stability. Due to the high penetration of distributed generations, fault characteristics become different from those of traditional fault detection. Thus, we propose a new fault detection and classification method for microgrids. Only current information is needed for the method. Hilbert–Huang Transform and sliding window strategy are used in fault characteristic extraction. The instantaneous phase difference of current high-frequency component is obtained as the fault characteristic. A self-adaptive threshold

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Hategekimana, Pascal, Adria Junyent Ferre, Joan Marc Rodriguez Bernuz, and Etienne Ntagwirumugara. "Fault Detecting and Isolating Schemes in a Low-Voltage DC Microgrid Network from a Remote Village." Energies 15, no. 12 (2022): 4460. http://dx.doi.org/10.3390/en15124460.

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Fault detection and isolation are important tasks to improve the protection system of low voltage direct current (LVDC) networks. Nowadays, there are challenges related to the protection strategies in the LVDC systems. In this paper, two proposed methods for fault detection and isolation of the faulty segment through the line and bus voltage measurement were discussed. The impacts of grid fault current and the characteristics of protective devices under pre-fault normal, under-fault, and post-fault conditions were also discussed. It was found that within a short time after fault occurrence in

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Sistani, Alireza, Seyed Amir Hosseini, Vahideh Sadat Sadeghi, and Behrooz Taheri. "Fault Detection in a Single-Bus DC Microgrid Connected to EV/PV Systems and Hybrid Energy Storage Using the DMD-IF Method." Sustainability 15, no. 23 (2023): 16269. http://dx.doi.org/10.3390/su152316269.

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Variations in fault currents, short times to clear the fault, and a lack of a natural current zero-crossing point are the most important challenges that DC microgrid protection faces. This challenge becomes more complicated with the presence of electric vehicles and energy storage systems due to their uncertainties. For this reason, in this paper, a new method for fault detection in DC microgrids with the presence of electric vehicles and energy storage systems is proposed. The new proposed method uses the combination of dynamic mode decomposition and instantaneous frequency for fault detectio

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Jing, Liuming, Tong Zhao, Lei Xia, and Jinghua Zhou. "An Improved High-Resistance Fault Detection Method in DC Microgrid Based on Orthogonal Wavelet Decomposition." Applied Sciences 13, no. 1 (2022): 393. http://dx.doi.org/10.3390/app13010393.

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High-resistance faults in direct current (DC) microgrids are small and thus difficult to detect. Such faults may be “invisible” in that grid operation continues for a considerable time, which damages the grid. It is essential to detect and remove high-resistance faults; we present a detection method herein. First, the transient DC current during the fault is subjected to hierarchical wavelet decomposition to identify high-resistance faults accurately and sensitively; the wavelet coefficients are detected using the singular value decomposition (SVD) method. The SVD valve can denoise the dc micr

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Ramaprasanna Dalai, Et al. "Protection Scheme based on Artificial Neural Network for Fault Detection and Classification in Low Voltage PV-Based DC Microgrid." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 1960–70. http://dx.doi.org/10.17762/ijritcc.v11i9.9193.

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With the expansion of the DC distribution market, protection, and operational concerns for Direct Current (DC) Microgrids have increased. Different systems have been investigated for detecting, finding, and isolating defects utilising a variety of protective mechanisms. It might be difficult to locate high-resistance faults and shorted DC faults on low-voltage DC (LVDC) microgrids. Therefore, in this study, a Field Transform Technique like Short-Time Fourier Transform (STFT) is proposed for detecting the Fault Current (FC). This method detects the faults Pole-ground (PG), pole-pole (PP), and A

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D Patil, Dipti, Bindu S, and Sushil Thale. "A Novel Method for Real Time Protection of DC Microgrid Using Cumulative Summation and Wavelet Transform." International journal of electrical and computer engineering systems 13, no. 4 (2022): 311–21. http://dx.doi.org/10.32985/ijeces.13.4.7.

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DC microgrid is a compact framework comprising interconnected nearby sources and loads. The renewable energy source used in DC microgrids being intermittent leads to the change in the power availability as well as the fault current levels. In such situations, detecting and clearing the faults is very important to protect the DC microgrid without compromising on fault clearing time and interruption of the load. This paper proposes a hybrid Cumulative Sum (CumSum) and Wavelet transform-based approach to detect the fault. The CumSum value raises the amplitude by averaging the fault current. Wavel

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Xiao, Chun, Yulu Ren, Qiong Cao, Ruifen Cheng, and Lei Wang. "Propagation Mechanism and Suppression Strategy of DC Faults in AC/DC Hybrid Microgrid." Processes 12, no. 5 (2024): 1013. http://dx.doi.org/10.3390/pr12051013.

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Due to their efficient renewable energy consumption performance, AC/DC hybrid microgrids have become an important development form for future power grids. However, the fault response will be more complex due to the interconnected structure of AC/DC hybrid microgrids, which may have a serious influence on the safe operation of the system. Based on an AC/DC hybrid microgrid with an integrated bidirectional power converter, research on the interaction impact of faults was carried out with the purpose of enhancing the safe operation capability of the microgrid. The typical fault types of the DC su

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Ma, Bowen, Qing Lu, and Zhou Gu. "Resilient Event-Based Fuzzy Fault Detection for DC Microgrids in Finite-Frequency Domain against DoS Attacks." Sensors 24, no. 9 (2024): 2677. http://dx.doi.org/10.3390/s24092677.

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This paper addresses the problem of fault detection in DC microgrids in the presence of denial-of-service (DoS) attacks. To deal with the nonlinear term in DC microgrids, a Takagi-Sugeno (T-S) model is employed. In contrast to the conventional approach of utilizing current sampling data in the traditional event-triggered mechanism (ETM), a novel integrated ETM employs historical information from measured data. This innovative strategy mitigates the generation of additional triggering packets resulting from random perturbations, thus reducing redundant transmission data. Under the assumption of

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Rajitha, Morampudi, A. Raghu Ram, Ch Shravani, and Ch Lokeshwar Reddy. "Towards Sustainable DC Microgrids: A Comprehensive Review of IoT-Driven Frameworks." E3S Web of Conferences 616 (2025): 03031. https://doi.org/10.1051/e3sconf/202561603031.

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A comprehensive review of cyber-physical architectures for DC microgrids is presented, focusing on the integration of deep learning and LoRa technology for secure, efficient, and scalable communication networks. DC microgrids, with their decentralized energy resources and low inertia, face challenges such as real-time monitoring, fault detection, and vulnerability to cyber-attacks. The review highlights the potential of LoRa technology for long-range, low-power communication, ensuring seamless data exchange between distributed components, including renewable energy sources, storage systems, an

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Eslami, R., S. H. H. Sadeghi, and Abyaneh H. Askarian. "A Probabilistic Approach for the Evaluation of Fault Detection Schemes in Microgrids." Engineering, Technology & Applied Science Research 7, no. 5 (2017): 1967–73. https://doi.org/10.5281/zenodo.1037195.

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An important challenge in protection of a microgrid is the process of fault detection, considering the uncertainties in its topologies. Equally important is the evaluation of proposed methods as their incorrect performances could result in unreasonable power outages. In this paper, a new fault detection and characterization method is introduced and evaluated subject to the uncertainties of network topologies. The features of three-phase components together with the positive, negative and zero sequences of current and voltage waveforms are derived to detect the occurrence of a fault, its locati

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Yılmaz, Alper, and Gökay Bayrak. "Real-Time Disturbance Detection Using STFT Method in Microgrids." Academic Perspective Procedia 2, no. 3 (2019): 1115–21. http://dx.doi.org/10.33793/acperpro.02.03.124.

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Power quality disturbances are the main concerns to be eliminated in microgrids and decrease the power quality and reliability of the grid. Numerous methods based on signal processing have been proposed in the literature for the detection of power quality disturbances. In this study, the proposed STFT-based method is applied to the voltage signal in real-time at the point of PCC in microgrids. By using the proposed method, it is tried to detection the sudden frequency changes and the over/under voltage events in case of fault conditions. As a result, the proposed method can detect faults in mi

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Eslami, R., S. H. H. Sadeghi, and H. Askarian Abyaneh. "A Probabilistic Approach for the Evaluation of Fault Detection Schemes in Microgrids." Engineering, Technology & Applied Science Research 7, no. 5 (2017): 1967–73. http://dx.doi.org/10.48084/etasr.1472.

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An important challenge in protection of a microgrid is the process of fault detection, considering the uncertainties in its topologies. Equally important is the evaluation of proposed methods as their incorrect performances could result in unreasonable power outages. In this paper, a new fault detection and characterization method is introduced and evaluated subject to the uncertainties of network topologies. The features of three-phase components together with the positive, negative and zero sequences of current and voltage waveforms are derived to detect the occurrence of a fault, its locati

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Liu, Yang, Shidong Zhang, Lisheng Li, et al. "A machine learning-based fault identification method for microgrids with distributed generations." Journal of Physics: Conference Series 2360, no. 1 (2022): 012019. http://dx.doi.org/10.1088/1742-6596/2360/1/012019.

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The development of renewable energy sources such as solar and wind based on distributed generators are growing rapidly in the face of the global energy crisis. As a connection between distributed generation and the main grid, microgrids are also growing rapidly. However, due to the randomness and uncertainty of the output of the solar and wind power, as well as the bidirectional characteristic of current flow, the faults in microgrids are difficult to identify using the traditional fault detection methods. To address this problem, this paper proposes a machine learning-based fault identificati

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Mahdavi, Mohammad Saeed, Mohammad Saleh Karimzadeh, Tohid Rahimi, and Gevork Babamalek Gharehpetian. "A Fault-Tolerant Bidirectional Converter for Battery Energy Storage Systems in DC Microgrids." Electronics 12, no. 3 (2023): 679. http://dx.doi.org/10.3390/electronics12030679.

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Battery energy storage systems (BESSs) can control the power balance in DC microgrids through power injection or absorption. A BESS uses a bidirectional DC–DC converter to control the power flow to/from the grid. On the other hand, any fault occurrence in the power switches of the bidirectional converter may disturb the power balance and stability of the DC microgrid and, thus, the safe operation of the battery bank. This paper presents a fault-tolerant topology along with a fault diagnosis algorithm for a bidirectional DC–DC converter in a BESS. The proposed scheme can detect open circuit fau

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Majee, Anay, Souradeep Nanda, and Gnana Swathika O.V. "Active Node Detection in A Reconfigurable Microgrid using Minimum Spanning Tree Algorithms." Indonesian Journal of Electrical Engineering and Computer Science 5, no. 3 (2017): 502. http://dx.doi.org/10.11591/ijeecs.v5.i3.pp502-507.

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<p>Microgrids are the solution to the growing demand for energy in the recent times. It has the potential to improve local reliability, reduce cost and increase penetration rates for distributed renewable energy generation. Inclusion of Renewable Energy Systems (RES) which have become the topic of discussion in the recent times due to acute energy crisis, causes the power flow in the microgrid to be bi-directional in nature. The presence of the RES in the microgrid system causes the grid to be reconfigurable. This reconfiguration might also occur due to load or utility grid connection an

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Taheri, Behrooz, Seyed Amir Hosseini, and Hamed Hashemi-Dezaki. "Enhanced Fault Detection and Classification in AC Microgrids Through a Combination of Data Processing Techniques and Deep Neural Networks." Sustainability 17, no. 4 (2025): 1514. https://doi.org/10.3390/su17041514.

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This paper introduces an innovative method for the intelligent protection of AC microgrids that incorporate renewable energy sources and electric vehicle charging stations. To extract relevant features, current signals from both sides of the distribution line are sampled. Subsequently, the differential current is calculated, and the resultant signals are processed using Compressed Sensing Theory and Variational Mode Decomposition to extract key features. These extracted features serve as input data for training the proposed wide and deep learning model. The proposed method was evaluated on a m

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Jiajian Lin, Yuting Sheng, Yutong Zhou, and Jalal Tavalaei. "AI-Driven Microgrids: A Review of Enabling Technologies and Future Prospects." International Journal of Latest Technology in Engineering Management & Applied Science 14, no. 6 (2025): 630–58. https://doi.org/10.51583/ijltemas.2025.140600071.

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Abstract: Microgrids represent a transformative paradigm in modern energy systems, enabling localized, efficient, and resilient energy management. With the growing urgency to decarbonize power systems and accommodate the increasing penetration of renewable energy sources, microgrids have emerged as a practical solution for integrating distributed energy resources (DERs), such as solar photovoltaics, wind turbines, and energy storage systems. Their ability to operate in grid-connected and islanded modes enhances energy reliability and autonomy, particularly in remote or disaster-prone areas. Ho

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Oliveira, Hércules A., Luiza H. S. Santos, Luiz A. de S. Ribeiro, José G. De Matos, and Lucas de P. A. Pinheiro. "Challenges in Microgrids with Medium Voltage Circuit." Eletrônica de Potência 30 (January 23, 2025): e202511. https://doi.org/10.18618/rep.e202511.

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This paper presents and discusses challenges in microgrids (uGrid) that arise when they operate isolated from the main grid. Specifically, these challenges occur because the system becomes an ungrounded delta configuration, and the microgrid power sources exhibit low short-circuit capacity. The important issues addressed include the failure to detect ground overcurrent during an earth fault event, voltage imbalances recorded by voltage transformers (VTs) connected between phases and earth, and the phenomenon of ferroresonance. These issues directly impact the coordination of electrical protect

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Sonal and Yogesh Tiwari. "An efficient ensemble based protection strategy for DC microgrid." i-manager's Journal on Power Systems Engineering 10, no. 4 (2023): 27. http://dx.doi.org/10.26634/jps.10.4.19271.

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A significant amount of interest from the scientific community has been focused on Direct Current (DC) microgrids in recent years, as a direct result of the proliferation of appliances that run on DC power. Nevertheless, the acceptability of DC microgrids by power utilities is still restricted owing to the challenges connected with the construction of a dependable protection system. This is because obtaining dependable protection for DC microgrids might be difficult due to the large size of DC fault current, its quick rate of rise, and the lack of zero crossing. In addition, the intermittent n

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Hong, Junho, Dmitry Ishchenko, and Anil Kondabathini. "Implementation of Resilient Self-Healing Microgrids with IEC 61850-Based Communications." Energies 14, no. 3 (2021): 547. http://dx.doi.org/10.3390/en14030547.

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Due to the high penetration of distributed energy resources (DER) and emerging DER interconnection and interoperability requirements, fast and standardized information exchange is essential for stable, resilient, and reliable operations in microgrids. This paper proposes fast fault detection, isolation, and restoration (F-FDIR) for microgrid application with the IEC 61850 Generic Object Oriented Substation Event (GOOSE) communication considering the communication/system failure. GOOSE provides a mechanism for lightweight low latency peer-to-peer data exchange between devices, which reduces the

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V., Prasanna Moorthy, and Ashok Kumar N. "Performance Analysis of Deep Neural Network-based Fault Detection in Standalone Photovoltaic DC Ring Microgrids." Journal of Soft Computing Paradigm 7, no. 1 (2025): 44–62. https://doi.org/10.36548/jscp.2025.1.004.

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This study explores the application of Deep Neural Networks (DNN) for fault detection in a standalone photovoltaic (PV)-based DC ring microgrid system. It follows a structured five-step methodology, beginning with the identification of various fault types, including short circuits, open circuits, hot spots, overheating, mismatch, and partial shading. Current and voltage signals undergo pre-processing steps such as data cleaning, normalization, and segmentation before being used to train the DNN model. The training and evaluation are conducted using simulation data from a PV-based DC ring stand

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Faazila Fathima, S., and L. Premalatha. "Implementation and impact of graph theory algorithm in Z-source breaker for the protection of DC microgrid." IOP Conference Series: Earth and Environmental Science 1281, no. 1 (2023): 012001. http://dx.doi.org/10.1088/1755-1315/1281/1/012001.

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Abstract Integrating renewable energy resources is the solution for the power demand crisis in the power energy market, reducing carbon emissions and energy loss. Autonomous acting grids, like DC microgrids, can provide power to rural areas, which neglects grid congestion. However, a proper protection scheme still needs to be determined, as the bidirectional power flow in microgrids exists. Initially, the status of the buses in the network needs to be monitored and addressed continuously so inactive buses are identified and faulted lines are noted easily. Also, the occurrence of a fault may pr

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Uzair, Muhammad, Mohsen Eskandari, Li Li, and Jianguo Zhu. "Machine Learning Based Protection Scheme for Low Voltage AC Microgrids." Energies 15, no. 24 (2022): 9397. http://dx.doi.org/10.3390/en15249397.

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The microgrid (MG) is a popular concept to handle the high penetration of distributed energy resources, such as renewable and energy storage systems, into electric grids. However, the integration of inverter-interfaced distributed generation units (IIDGs) imposes control and protection challenges. Fault identification, classification and isolation are major concerns with IIDGs-based active MGs where IIDGs reveal arbitrary impedance and thus different fault characteristics. Moreover, bidirectional complex power flow creates extra difficulties for fault analysis. This makes the conventional meth

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K, Jayanarayanan Unny V., and Keerthana Unni. "Detection of Voltage Sag Source in a Hybrid Microgrid Using Directional Relays." International Journal of Environmental Sciences 11, no. 6s (2025): 299–309. https://doi.org/10.64252/p92xyg19.

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The proliferation of hybrid microgrids incorporating renewable energy sources has introduced significant challenges in power quality management, particularly in the detection and localization of voltage sag sources. This research investigates the application of directional relays for accurate identification of voltage sag origins in hybrid microgrid systems. The study employs a comprehensive methodology combining simulation analysis using MATLAB/Simulink with real-time hardware implementation to evaluate the effectiveness of directional relay-based detection algorithms. Primary data collection

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Aqamohammadi, Amir Reza, Taher Niknam, Sattar Shojaeiyan, Pierluigi Siano, and Moslem Dehghani. "Deep Neural Network with Hilbert–Huang Transform for Smart Fault Detection in Microgrid." Electronics 12, no. 3 (2023): 499. http://dx.doi.org/10.3390/electronics12030499.

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The fault detection method (FDM) plays a crucial role in controlling and operating microgrids (MGs), because it allows for systems to rapidly isolate and restore faults. Due to the fact that MGs use inverter-interfaced distributed production, conventional FDMs are no longer appropriate because they are dependent on substantial fault currents. This study presents a smart FDM for MGs based on the Hilbert–Huang transform (HHT) and deep neural networks (DNNs). The suggested layout aims to prepare the fast detection of fault kind, phase, and place data to protect MGs and restore services. The HHT p

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Nair, Divya Shoba, Thankappan Nair Rajeev, and Sindhura Miraj. "Enhanced fault identification in grid-connected microgrid with SVM-based control algorithm." Indonesian Journal of Electrical Engineering and Computer Science 36, no. 1 (2024): 115. http://dx.doi.org/10.11591/ijeecs.v36.i1.pp115-126.

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<p>The penetration of renewable energy sources, electric vehicles (EVs) and load dynamics, and network complexities often lead to nuisance tripping in grid-connected microgrids. Traditional protection methods fail to discriminate fault and other dynamic volatilities in the system. The paper presents a novel two-level adaptive relay algorithm to avoid nuisance tripping in a grid-connected microgrid under varying grid dynamics. The novelty of the adaptive relay algorithm is that nuisance tripping is eliminated by precisely determining normal system-level dynamics at the first level using a

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Divya, Shoba Nair Thankappan Nair Rajeev Sindhura Miraj. "Enhanced fault identification in grid-connected microgrid with SVM-based control algorithm." Indonesian Journal of Electrical Engineering and Computer Science 36, no. 1 (2024): 115–26. https://doi.org/10.11591/ijeecs.v36.i1.pp115-126.

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The penetration of renewable energy sources, electric vehicles (EVs) and load dynamics, and network complexities often lead to nuisance tripping in grid-connected microgrids. Traditional protection methods fail to discriminate fault and other dynamic volatilities in the system. The paper presents a novel two-level adaptive relay algorithm to avoid nuisance tripping in a grid-connected microgrid under varying grid dynamics. The novelty of the adaptive relay algorithm is that nuisance tripping is eliminated by precisely determining normal system-level dynamics at the first level using a phase de

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