Across the power grid infrastructure, deployed power transmission systems are susceptible to incipient faults that interrupt standard operations. These incipient faults can range from being benign in impact to causing massive hardware damage and even...
This study presents a machine learning-based method for predicting the power grid state subjected to heavy-rain hazards. Machine learning models can recognize key knowledge from a dataset without any preliminary knowledge about the dataset. Hence, ma...
With the large-scale deployment of sensors, both the smart grid and the power communication network should jointly deal with different kinds of big data. The fusion of both networks should bring unpredictable accidents, even leading a catastrophic de...
The rapid expansion of Artificial Intelligence is fueling the growth of hyperscale data centers, which introduces significant challenges to existing power systems. This paper aims to provide a comprehensive survey of these integration challenges, spe...
Events detection is a key challenge in power grid frequency disturbances analysis. Accurate detection of events is crucial for situational awareness of the power system. In this paper, we study the problem of events detection in power grid frequency...
The demand for computing power has increased at a rate never seen before due to the quick development of artificial intelligence (AI) technologies and applications. Consequently, AI data centers, referring to computing facilities specifically designe...
In order to complete the function of power grid fault diagnosis accurately, rapidly and comprehensively, the power grid fault diagnosis system based on multi-data sources is proposed. The integrated system uses accident-level information, warning-lev...
This work proposes a data-driven approach to controlling the alternating current (AC) voltage via a static synchronous compensator (STATCOM). This device offers a fast dynamic response injecting reactive power to compensate the voltage profile, not o...
Disruptive events and the rapid evolution of urban energy systems highlight the need for robust methods to reconstruct critical infrastructure networks. Comprehensive, up-to-date power grid representations are essential for both researchers developin...
Targeting the problem of the power grid facing greater risks with the connection of large-scale wind power, a method for power grid state analysis using big data is proposed. First, based on the big data, the wind power matrix and the branch power ma...
This study presents the phasor measurement unit (PMU) placement strategy in the presence of false data injection attacks which is one of the most serious security threats against power grid. It is focused on applications related to supervisory contro...
The efficient management of the green power grid supply chain is of great significance in addressing global energy transformation and achieving sustainable development goals. However, traditional methods struggle to effectively cope with the complexi...
As global warming continues to intensify, typhoon disasters will more frequently occur in East and Southeast Asia, posing a high risk of causing large-scale power outages in the power system. To investigate the impact of typhoon disasters on high-vol...
For data-driven dynamic stability assessment (DSA) in modern power grids, DSA models generally have to be learned from scratch when faced with new grids, resulting in high offline computational costs. To tackle this undesirable yet often overlooked p...
Bulk power grid interconnection and the access of various smart devices make the current grid highly complex. Timely and accurately identifying the power grid operation state is crucial for monitoring the operation stability of the power grid. For th...
Power system decarbonization will be one of the main challenges confronting society over the next twenty to thirty years. Renewable energy sources (RES), such as wind and solar, will be the main resources supplying the power grid. Given their volatil...
Power grids deal with the business of generation, transmission, and distribution of electric power. Current systems monitor basic electrical quantities such as voltage and current from major pole transformers using their temperature. We improve the c...
Significant amounts of data need to be transferred in order to optimize the operation of power grids. The development of advanced metering and control infrastructure ensures a growth in the amount of data transferred within smart grids. Data compress...
The internet data center (IDC) has experienced rapid growth recently. Computing power tasks have the characteristic of flexible adjustment and can participate in demand-side response; thus, they are suitable for balancing stochastic wind and solar po...
Monitoring what application or type of applications running on a computer or a cluster without violating the privacy of the users can be challenging, especially when we may not have operator access to these devices, or specialized software. Smart gri...
Electric power grids are a crucial infrastructure for the proper operation of any country and must be preserved from various threats. Detection of illegal electricity power consumption is a crucial issue for distribution system operators (DSOs). Mini...
With the rapid development of artificial intelligence (AI), AI has been widely applied in anomaly analysis detection and fault location in power grid data and has made significant research progress. Through looking back on traditional methods and dee...
The key advantage of smart meters over traditional metering devices is their ability to transfer consumption information to remote data processing systems. Besides enabling the automated collection of a customer’s electricity consumption for billing...
Agrometeorological models are great tools for predicting yields and improving decision-making. High-quality climatic data are essential for using these models. However, most developing countries have low-quality data with low frequency and spatial co...
To face the impact of climate change in all dimensions of our society in the near future, the European Union (EU) has established an ambitious target. Until 2050, the share of renewable power shall increase up to 75% of all power injected into nowada...
In power grid surveying, it is often necessary to fuse panchromatic and multispectral imagery for the design of power lines. Despite the abundance of deep learning networks for fusing these images, the results often suffer from spectral information l...
More and more countries and utilities are trying to develop smart grid projects to make transformation of their power infrastructure towards future grids with increased share of renewable energy production and near zero emissions. The intermittent na...
This study proposes a data-driven methodology for modeling power and hydrogen generation of a sustainable energy converter. The wave and hydrogen production at different wave heights and wind speeds are predicted. Furthermore, this research emphasize...
Modern societies need a constant and stable electrical supply. After relying primarily on formal mathematical modeling from operations research, control theory, and numerical analysis, power systems analysis has changed its attention toward AI predic...
Integration of information technologies with power systems has unlocked unprecedented opportunities in optimization and control fields. Increased data collection and monitoring enable control systems to have a better understanding of the pseudo-real-...
This paper centers on the design and installation of a robust photovoltaic (PV)-based microgrid data acquisition system (DAS) that can monitor different PV systems simultaneously. The PV-based microgrid consists of three solar systems: off-grid, hybr...
A wireless sensor network (WSN) is made up of multiple sensors deployed in a specific sensing area to identify the occurrence of events and quickly transmit useful information back to the base station (BS). In WSNs, schemes to reduce energy consumpti...
In recent years, we have seen an increasing dependency between different urban critical infrastructures, which raises the demands on their analysis and cybersecurity. Current open-source solutions do not provide simulations of interconnected data net...
Understanding and analyzing cascading failures in power grids have been the focus of many researchers for years. However, the complex interactions among the large number of components in these systems and their contributions to cascading failures are...
As renewable energy penetration increases, the volatility and uncertainty of photovoltaic generation and load demand pose significant challenges to power-system stability. This paper proposes a data-driven probabilistic load-flow method that employs...
Fault diagnosis (FD) is a critical challenge for the smart grid and the power communication network, especially when both heterogeneous networks are exponentially becoming enormous and complicated. Consequently, some conventional FD schemes based on...
With major effects on power grids and people’s lifestyles, the quick uptake of electric vehicles (EVs) poses serious problems for the robustness of charging infrastructure. By enabling spatiotemporally optimal charging strategies that optimize...
With recent technological advancements, advanced communication technology, sensors and distributed generation (DG), it is an undeniable fact that modern power systems are flooded with massive amounts of data. These vast amount of generated data are d...
Cyber-physical power systems (CPPS) integrate information and communication technology into conventional electric power systems to facilitate bidirectional communication of information and electric power between users and power grids. Despite its ben...
The accurate forecasting of financial flow data in power-grid operations is critical for improving operational efficiency. To tackle the challenges of low forecasting accuracy and high error rates caused by the long sequences, nonlinearity, and multi...
With the advancement in the “dual carbon” strategy and the integration of high proportions of renewable energy sources, AC/DC ultra-high-power grids are facing new security challenges such as commutation failure and multi-infeed coupling...
Amidst the accelerating growth of intelligent power systems, the integrity of vast and complex datasets has become essential to promoting sustainable energy management, ensuring energy security, and supporting green living initiatives. This study int...
In the power grid scheduling process, load forecasting serves as the foundation for ensuring stability and economic dispatch. It not only optimizes resource allocation but also strengthens the system’s productivity and stability, helps prevent...
Electrical data analysis based on smart grids has become a fundamental tool used by electrical grid stakeholders to understand the energy consumption patterns of users, although many proposals in this area do not consider reactive energy as another s...
As a key enabling technology for energy transition, the smart grid is propelling the global power system to evolve toward greater efficiency, reliability, and sustainability. Based on the three-dimensional analysis framework of “technology&ndas...
The growth of renewable energy generation in the power grid brings attention to high-voltage direct current (HVDC) transmission as a valuable solution for stabilizing the system. Robust hybrid power system state estimation could enhance the resilienc...
Renewable energy systems design using average year weather data is a standard approach that works well for grid-tied systems, but for stand-alone ones, it leads to dramatic mistakes. We considered the effect of meteorological data temporal resolution...
The advanced metering infrastructure (AMI) of the smart grid plays a critical role in energy management and billing by enabling the periodic transmission of consumers’ power consumption readings. To optimize data collection efficiency, AMI empl...
Smart grid is an emerging system providing many benefits in digitizing the traditional power distribution systems. However, the added benefits of digitization and the use of the Internet of Things (IoT) technologies in smart grids also poses threats...
The large-scale deployment of pervasive sensors and decentralized computing in modern smart grids is expected to exponentially increase the volume of data exchanged by power system applications. In this context, the research for scalable and flexible...
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