Relevant bibliographies by topics / Microgrids Fault detection

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Microgrids Fault detection'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Microgrids Fault detection"

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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. 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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Dissertations / Theses on the topic "Microgrids Fault detection"

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Brucoli, Maria. "Fault behaviour and fault detection in islanded inverter-only microgrids." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/7893.

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The increase in popularity of the microgrid concept requires the analysis and solution of the numerous technical issues arising from the operation and integration of the microgrid into the original distribution network. The work presented in this thesis is centred on the study of the fault behaviour of inverter-only microgrids and on the development of a suitable fault detection technique. This task is approached by first understanding the behaviour of a microgrid during a fault and the factors affecting it. A complete description and analysis of the key elements in the study of microgrid faul
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García-Gutiérrez, Luis Antonio. "Développement d'un contrôle actif tolérant aux défaillances appliqué aux systèmes PV." Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30071.

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Cette thèse de doctorat aborde la problématique de la réalisation d'un système de contrôle actif de détection de défaut et diagnosis (FDD) pour un système de conversion photovoltaïque. Ce type de système de production d'énergie électrique est composé de panneaux solaires, d'un dispositif MPPT, d'un convertisseur de courant DC-DC, d'un onduleur DC-AC et d'une charge. Le système de contrôle actif à tolérance de pannes qui a été développé dans cette thèse est composé de deux étages : * Un étage assurant la fonction de diagnostic et comprenant les fonctions de détection de défauts, la fonction d'i
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Dewadasa, Jalthotage Manjula Dinesh. "Protection of distributed generation interfaced networks." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/43681/1/Jalthotage_Dewadasa_Thesis.pdf.

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With the rapid increase in electrical energy demand, power generation in the form of distributed generation is becoming more important. However, the connections of distributed generators (DGs) to a distribution network or a microgrid can create several protection issues. The protection of these networks using protective devices based only on current is a challenging task due to the change in fault current levels and fault current direction. The isolation of a faulted segment from such networks will be difficult if converter interfaced DGs are connected as these DGs limit their output currents
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Fadhel, Siwar. "Efficacité énergétique et surveillance d’un microgrid à courant continu alimenté par des panneaux photovoltaïques." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASS001.

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Les systèmes photovoltaïques (PV) sont régulièrement exposés à de nombreux défauts entraînant des pertes de production coûteuses. Le travail proposé dans cette thèse porte sur l’amélioration de l’efficacité énergétique d’un microgrid à courant continu en minimisant les pertes liées à l’apparition des défauts PV. D’abord, nous avons présenté un état de l’art sur les défauts les plus fréquents et les méthodes de leur diagnostic. L’analyse de la littérature nous a orienté vers le choix d’une approche de diagnostic pilotée par les données. Ensuite, la méthode de l’Analyse en Composantes Principale
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Cabatac, Mark Tristan Angelo Morena, and 崔思安. "Fault Detection and Location by Static Switch in Microgrids Using Wavelet Transform and Taguchi-based Artificial Neural Network." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/3wz4w9.

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碩士<br>中原大學<br>電機工程研究所<br>106<br>This study presents a fault detection, classification and localization using the multiresolution analysis (MRA) of the discrete wavelet transform (DWT) and a Taguchi-based artificial neural network (ANN). The difference of wavelet energies of the three-phase fault voltages, three-phase fault currents and the wavelet energy of the ground fault current are utilized as inputs to the neural network. The wavelet energies are obtained from the local fault signals at the static switch located at the secondary side of the main transformer in the microgrid. The neural ne
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(9754367), Pallavi Madhav Kulkarni. "Contributions to Autonomous Operation of a Deep Space Vehicle Power System." Thesis, 2020.

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<div>The electric power system of a deep space vehicle is mission-critical, and needs to operate autonomously because of high latency in communicating with ground-based mission control. Key tasks to be automated include managing loads under various physical constraints, continuously monitoring the system state to detect and locate faults, and efficiently responding to those faults. </div><div><br></div><div>This work focuses on three aspects for achieving autonomous, fault-tolerant operation in the dc power system of a spacecraft. First, a sequential procedure is proposed to estimate the node
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Ustun, Taha Selim. "Design and development of a communication-assisted microgrid protection system." Thesis, 2013. https://vuir.vu.edu.au/22016/.

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Climate change concerns due to the rising amounts of the carbon gas in the atmosphere have in the last decade or so initiated a fast pace of technological advances in the renewable energy industry. Such developments in technology and the move towards cleaner sources of energy have made renewable resources based Distributed Generators (DGs) more desirable.
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Gu, Jun-Liang, and 古俊良. "TSK-based FPGA Design for Fault Detection in Microgrid." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/80445839068228345234.

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碩士<br>中原大學<br>電機工程研究所<br>102<br>A static switch is an important device in a micro-grid. In order to ensure the micro-grid can operate normally, the static switch must disconnect the faulted zone from the unfaulted zones. This thesis presents a fault detection/classification method which integrates Park transform, wavelet transform and Takagi-Sugeno-Kang fuzzy reasoning. This work uses an FPGA chip to realize the presented method by Xilinx System Generator. Finally, the developed FPGA incorporating with the micro-grid modeled using Simulink is studied in a hardware-in-the-loop simulation
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YANG, ZHONG-XIAN, and 楊忠憲. "LabVIEW-FPGA-Based Microgrid Lines of Fast Fault Detection Device." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/89962681831953549988.

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碩士<br>中華科技大學<br>飛機系統工程研究所<br>102<br>Owing to the more and more usage of distributed generation (DG), various countries have engaged to the development for adding the DG into the traditional power system. The system consists of various DG and load can be named by micro-grid system. Because of the different characteristics between various type of DG and load, it is very important to set up an appropriate protection scheme. In this thesis, we will discuss the microgrid test report which was developed in CERTS of United States. However, it belongs to 480V single-point grounding system, which is d
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Saleem, Hafiz. "Development of a Fault Detection Model for Cyber Physical Power System." Thesis, 2018. https://vuir.vu.edu.au/39495/.

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This thesis investigates and implements a fault detection scheme for cyber-physical power system (CPPS). An un-interruptible supply of energy is the biggest challenge faced by the power engineers. Due to the involvement of information and communication technology (ICT), the behavior of the power grid has transformed completely in recent years. The evolution of the existing grid system has resulted in bidirectional power flow. That means the entities once only consumed power now can generate and send power back to the main grid, behaving as a microgrid. The grid is made up of microgrids, which
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Book chapters on the topic "Microgrids Fault detection"

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Fathima S, Faazila, and L. Premalatha. "Arduino-Based Fault Detection Schemes for DC Microgrids." In Smart Buildings Digitalization. CRC Press, 2021. http://dx.doi.org/10.1201/9781003201069-12.

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Jena, Smrutisikha, Debani Prasad Mishra, and Surender Reddy Salkuti. "Fault Detection, Classification, and Location in Underground Cables." In Power Quality in Microgrids: Issues, Challenges and Mitigation Techniques. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2066-2_10.

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Schulte, Horst, and Alexander Pascal Cesarz. "Fault Detection and Isolation of Distributed Inverter-Based Microgrids." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50936-1_123.

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Anudeep, Bhatraj, Prakriti Kumar Srivastava, Sauvik Biswas, and Paresh Kumar Nayak. "High Impedance Fault Detection in Microgrids Using Cross-Alienation Coefficient." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0275-7_4.

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Pradhan, Rudranarayan, G. Venkat Shyam Sunder, Monali Nayak, and Baidhar Hembram. "Integrating Decision Tree for Enhanced Fault Detection in AC Microgrid." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-0824-9_7.

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Roy, Gargi, Soyel Ghosh, and Arpendra Roy. "A Novel Approach to Microgrid Fault Detection Using Empirical Mode Decomposition." In Studies in Autonomic, Data-driven and Industrial Computing. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7305-4_11.

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Narzary, Daijiry, Subrat Kumar Swain, Jagat Rath, and Kalyana C. Veluvolu. "Detection of Sensor Fault in a DC Microgrid Using Supertwisting Observer." In Recent Advances in Mechanical Infrastructure. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7660-4_12.

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Niharika and Lini Mathew. "Real Time Analysis of Artificial Neural Network-Based Fault Detection and Fault Location in the AC Microgrid." In Advances in Intelligent Systems and Computing. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3590-9_25.

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Singh, Priya, Nitin Singh, and Niraj Kumar Choudhary. "Fault Detection and Classification in Microgrid Using Wavelet Transform and Artificial Neural Network." In Lecture Notes in Electrical Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6840-4_2.

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Konathala, Aravinda Shilpa, Jasmitha Kandregula, Saranya Munukutla, Chandrika Bankupalli, Pujitha Vugiri, and Villuri Mahalakshmi Naidu. "Artificial Neural Network-Based Fault Detection, Classification, and Location of AC-DC Microgrid." In Studies in Autonomic, Data-driven and Industrial Computing. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-5862-3_16.

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Conference papers on the topic "Microgrids Fault detection"

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Ajayi, Oluwadamilola, Mohammadreza Mirjafari, Peter B. Idowu, and Md Habib Ullah. "Explainable AI for Fault Detection and Classification in Microgrids." In 2024 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2024. https://doi.org/10.1109/ecce55643.2024.10861648.

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Chakraborty, Soham, Yue Chen, Ahmed Zamzam, and Jing Wang. "SVM-Based Synchronized Fault Detection for 100% Renewable Microgrids." In IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2024. https://doi.org/10.1109/iecon55916.2024.10905850.

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Naeiji, Soroush, Hamid Jafarabadi Ashtiani, Amir Shabani, and Z. John Shen. "Unified Machine Learning Based Fault Detection Strategy Through Voltage-Sensing for Both AC and DC Side Faults in Photovoltaic Farms." In 2024 IEEE Sixth International Conference on DC Microgrids (ICDCM). IEEE, 2024. http://dx.doi.org/10.1109/icdcm60322.2024.10664829.

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Aboelezz, Asmaa M., Magdi M. El-Saadawi, Abdelfattah A. Eladl, and Bishoy E. Sedhom. "Enhancing Fault Detection in Smart Microgrids using Centralized Artificial Neural Networks." In 2024 25th International Middle East Power System Conference (MEPCON). IEEE, 2024. https://doi.org/10.1109/mepcon63025.2024.10850168.

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Adeyeye, Adebimpe O., Abraham O. Amole, and Nosagieagbon O. Imarhiagbe. "A Theoretical Review on Trends in Fault Detection Techniques for Microgrids." In 2024 IEEE 5th International Conference on Electro-Computing Technologies for Humanity (NIGERCON). IEEE, 2024. https://doi.org/10.1109/nigercon62786.2024.10927137.

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Yang, Ge, Luis Herrera, and Xiu Yao. "Data-Driven Observer Based Detection for Series Arc Fault in DC Microgrids." In 2024 IEEE Energy Conversion Congress and Exposition (ECCE). IEEE, 2024. https://doi.org/10.1109/ecce55643.2024.10861403.

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Hussain, Arif, and Gelli Ravikumar. "Deep Learning-based Autoencoder for Fault Detection and Localization in DER-Microgrids." In 2025 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge). IEEE, 2025. https://doi.org/10.1109/gridedge61154.2025.10887428.

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MS, Akhila, and Akhil Chacko. "Fault Detection and Monitoring in Microgrids using Intelligent Controllers and Synchrophasor Integration." In 2025 2nd International Conference on Trends in Engineering Systems and Technologies (ICTEST). IEEE, 2025. https://doi.org/10.1109/ictest64710.2025.11042657.

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Zhi, Na, Yiding Ding, Hang Zhang, and Jilin Qiu. "Research on Fault Detection and Localization in Meshed DC Microgrids Based on Local Information Measurements." In 2025 IEEE 16th International Symposium on Power Electronics for Distributed Generation Systems (PEDG). IEEE, 2025. https://doi.org/10.1109/pedg62294.2025.11060406.

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Jadidi, Saeedreza, and Xiaodong Liang. "A Gramian Angular Summation Field-Convolutional Neural Network-Based Openswitch Fault Detection Technique for Interfacing Inverters in Microgrids." In 2024 IEEE Industry Applications Society Annual Meeting (IAS). IEEE, 2024. https://doi.org/10.1109/ias55788.2024.11023740.

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Reports on the topic "Microgrids Fault detection"

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El Khatib, Mohamed, Javier Hernandez Alvidrez, and Abraham Ellis. Fault Analysis and Detection in Microgrids with High PV Penetration. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1367437.

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