Article
Energy & Fuels
Shreyasi Som, Rajarshi Dutta, Amir Gholami, Anurag K. Srivastava, Saikat Chakrabarti, Soumya Ranjan Sahoo
Summary: This research proposes a data-driven approach for event detection in microgrids using phasor measurements from DPMUs. The method can determine whether a change in phasor measurement is caused by an event or measurement anomalies.
Article
Chemistry, Analytical
Saleh Almasabi, Turki Alsuwian, Muhammad Awais, Muhammad Irfan, Mohammed Jalalah, Belqasem Aljafari, Farid A. Harraz
Summary: This paper focuses on detecting false data injection (FDI) attacks by using moving averages, correlation, and machine learning algorithms on phasor measurement units. The proposed approach has been tested and validated on IEEE 14-bus and IEEE 30-bus test systems, showing sufficient performance in detecting the location and attack instances under different scenarios and circumstances.
Article
Engineering, Electrical & Electronic
Mohammad Alqudah, Martin Pavlovski, Tatjana Dokic, Mladen Kezunovic, Yi Hu, Zoran Obradovic
Summary: This paper proposes an end-to-end supervised learning method for fault detection in the electric grid using Big Data from multiple Phasor Measurement Units (PMUs). The approach includes preprocessing steps to reduce data noise and dimensionality, and utilizes six classification models for fault detection. The experiments show that the CNN-based models outperform traditional methods in outage detection over the entire grid.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
P. Lakshminarayana, K. Mercy Rosalina, Venkatesan Mani
Summary: This study proposes an online dynamic state estimation approach that integrates PMU and conventional measurements to prevent and regulate network blackouts. The deployment of PMUs at sensitive buses is determined using constrained integer linear programming, and the results are evaluated using the RMSE metric. Experimental results demonstrate the effectiveness of the proposed approach in different bus networks.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Jhonny Gonzalez, Panagiotis N. Papadopoulos, Jovica V. Milanovic, Goran Peskir, John Moriarty
Summary: This paper addresses the problem of 'quickest possible' online transient stability assessment by optimizing event detection and generator group prediction while respecting predefined probabilistic error constraints. The approach is shown to be two to three times faster on average than strategies based on fixed assessment times with comparable error rates in simulated measurements from interconnected systems.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Engineering, Electrical & Electronic
Fayha Almutairy, Lazar Scekic, Mustafa Matar, Ramadan Elmoudi, Safwan Wshah
Summary: The widespread use of Phasor Measurement Units (PMUs) contributes significantly to the quality of power system monitoring. However, the lack of encryption in GPS receivers used in PMUs makes them vulnerable to GPS Spoofing Attacks (GSAs), causing phase shifts in measurements. This paper introduces the first application of deep learning in detecting and mitigating the effects of GSAs on PMUs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Felipe V. Lopes, Arthur Mouco, Rafael O. Fernandes, Felipe C. Neto
Summary: Transmission line fault location is crucial for power system restoration after outages, with existing methods mainly relying on fundamental phasors. Traditional fault locators typically use phasor estimations from protective relays or P-class Phasor Measurement Units, but there is limited research on using M-class data for fault location. This study found that M-class phasor measurements can be effectively used in fault location applications, yielding errors within expected levels for phasor-based methods.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Mohammad Reza Shadi, Mohammad-Taghi Ameli, Sasan Azad
Summary: This paper introduces a novel hierarchical methodology using deep learning to detect and classify Frequency Disturbance Events (FDEs) with significant accuracy in terms of classification and location precision. The proposed models have achieved competitive performance in terms of classification accuracy and event location precision, compared to conventional algorithms and frequency-based DL models.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Lakshan Bernard, Sunny Goondram, Behrooz Bahrani, Athanasios A. Pantelous, Reza Razzaghi
Summary: This paper proposes a novel approach based on MPM and PCA to estimate the fundamental frequency, harmonic and interharmonic phasors in power networks. The method allows concurrent estimation of all frequency components without additional computational cost, and is compliant with IEEE requirements for PMUs. It provides accurate harmonic phasor estimation for both M- and P-class PMUs.
IEEE SENSORS JOURNAL
(2021)
Article
Automation & Control Systems
Alexey Bobtsov, Romeo Ortega, Nikolay Nikolaev, Nicolai Lorenz-Meyer, Johannes Schiffer
Summary: This article presents a solution to the globally convergent state estimation problem for multimachine power systems equipped with PMUs and described by the fourth-order flux-decay model. The design of the observer relies on parameter estimation and the use of the DREM technique, overcoming issues of lack of persistent excitation and showing improved performance compared to a locally stable gradient-descent-based observer.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
A. Raqib Hussain, M. K. Elango
Summary: This manuscript proposes a hybrid technique, named DMO-POA approach, for determining the optimum location of mu-PMUs in the distribution system. The approach aims to avoid supply discontinuity, reduce cost, and achieve maximum measurement-redundancy for complete system observability. It also considers the requirements of the communication system and the reconfiguration of smart distribution grids.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2023)
Article
Energy & Fuels
Ahmed Amirul Arefin, Khairul Nisak Binti Md Hasan, Mohammad Lutfi Othman, Mohd Fakhizan Romlie, Nordin Saad, Nursyarizal Bin Mohd Nor, Mohd Faris Abdullah
Summary: The study aims to propose a new method for setting island detection thresholds using the slip angle and acceleration angle from phasor measurement unit voltage angle data. In simulations on a modified IEEE 30 bus system equipped with DG, the proposed method can quickly and accurately determine island thresholds in different interconnection scenarios, distinguishing between real island conditions and transient fault conditions.
Article
Automation & Control Systems
Tong Wu, Ying-Jun Angela Zhang, Xiaoying Tang
Summary: The article presents an online data-driven approach for rapid event detection and mitigation of low-quality data impact, involving an adaptive and online isolation forest-based detection method, data augmentation method, and adaptive training process.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Engineering, Multidisciplinary
Abdelfattah A. Eladl, Ahmed N. Sheta, Mohammed A. Saeed, Mohammed A. Abido, Mohamed A. Hassan
Summary: This study proposed a method for optimally allocating Phasor Measurement Units (PMUs) in power systems using binary integer programming technique, achieving complete observability of the network and reducing the number of PMUs. Through testing and comparison, it was found that this method can effectively place PMUs and save time consumption.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Computer Science, Information Systems
Meysam Shahriyari, Hamid Khoshkhoo, Josep M. Guerrero
Summary: In this article, a new scheme is proposed for fast transient stability status (TSS) prediction without requiring postfault data. This method utilizes phasor measurement units (PMUs) to gather time-synchronized data and applies a decision tree classifier to predict TSS using fault-on and prefault information. The results show that the proposed method accurately forecasts TSS even with fewer PMUs and considering measurement errors.
IEEE SYSTEMS JOURNAL
(2022)
