Precise and comprehensive model development is essential for predicting power network balance and maintaining power system analysis and optimization. The development of big data technologies and measurement systems has introduced new challenges in po...
The issue of counting independent sets of a graph, G, represented as i(G), is a significant challenge within combinatorial mathematics. This problem finds practical applications across various fields, including mathematics, computer science, physics,...
Edge even graceful labeling (e.e.g., l.) of graphs is a modular technique of edge labeling of graphs, introduced in 2017. An e.e.g., l. of simple finite undirected graph G = ( V ( G ) , E ( G ) ) of order P = | ( V ( G ) | and siz...
Amid the escalating climate crisis, integrating variable renewables into power systems demands innovative carbon-conscious grid management. This research presents a Graph Convolutional-Optimization Framework that synergizes Graph Convolutional Networ...
Robotic exploration in dynamic and complex environments requires advanced adaptive mapping strategies to ensure accurate representation of the environments. This paper introduces an innovative grid flex-graph exploration (GFGE) algorithm designed for...
Sea surface temperature (SST) is an important factor in the marine environment and has significant impacts on climate, ecology, and maritime activities. Most existing SST prediction methods consider the ocean as a uniform field and use a uniform grid...
Amidst the large-scale integration of renewable energy, power grid operations are increasingly characterized by higher levels of uncertainty, challenging the system’s safety and stability. Traditional model-driven dispatch methods are computati...
Let G and H be graphs. A mapping f from the vertices of G to the vertices of H is known as a homomorphism from G to H if, for every pair of adjacent vertices x and y in G, the vertices f(x) and f(y) are adjacent in H. A rectangular grid graph is the...
With the increasing complexity of power grid field operations, frequent operational violations have emerged as a major concern in the domain of power grid field operation safety. To support dispatchers in accurately identifying and addressing violati...
Accurate sea surface temperature (SST) forecasting in coastal upwelling systems requires predictive models capable of representing complex oceanic geometries. This work revisits grid-to-mesh coupling strategies in Graph Neural Networks (GNNs) and ana...
Distribution grids are complex networks containing multiple pieces of equipment. These components are interconnected, and each of them is described by various attributes. A knowledge graph is an interesting data format that represents pieces of infor...
Accurate transformer–customer relationships are crucial for the efficient operation and high-quality service of the low-voltage distribution grid (LVDG). This paper proposes a novel two-stage transformer–customer relationship identificati...
A relevant problem in combinatorial mathematics is the problem of counting independent sets of a graph G, denoted by i(G). This problem has many applications in combinatorics, physics, chemistry and computer science. For example, in statistical physi...
A weak homomorphism from graph G to graph H is a mapping f:V(G)→V(H), where either f(x)=f(y) or {f(x),f(y)}∈E(H) hold for all {x,y}∈E(G). A rectangular grid graph is formed by taking the Cartesian product of two paths. Counting weak ho...
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...
Edge Even Graceful Labelingwas first defined byElsonbaty and Daoud in 2017. An edge even graceful labeling of a simple graph G with p vertices and q edges is a bijection f from the edges of the graph to the set { 2 , 4 , &...
With the continuous development of the power grid, its structure is becoming increasingly complex. The occurrence of faults in transmission lines may lead to cascading failures in the power grid, ultimately resulting in widespread power outages. The...
To overcome the limitations of traditional convolutional and recurrent neural networks in capturing spatio-temporal dynamics in flow fields on unstructured grids, this study proposes a novel Spatio-Temporal Graph Neural Network (ST-GNN) model that in...
Accurate prediction of carbon emissions is crucial for both providing effective carbon reduction guidance to the power grid sector and driving society-wide carbon emission reduction. Existing methods based on power flow calculation theory heavily rel...
Accurate topological connectivity is critical for the safe operation and management of low-voltage distribution grids (LVDGs). However, due to the complexity of the structure and the lack of measurement equipment, obtaining and maintaining these topo...
Air conditioning loads in power systems exhibit spatiotemporal heterogeneity across geographical regions, complicating accurate load forecasting. This study proposes a framework that integrates Deep Reinforcement Learning-guided DBSCAN (DRL-DBSCAN) c...
The normal operation of automated equipment is essential for power grid regulation, making the accurate identification and diagnosis of defects in this equipment highly significant. Constructing a knowledge graph for automated equipment defects offer...
To address the lack of effective risk-identification methods during the commissioning of new power grid equipment, we propose a knowledge graph construction approach for both scheme generation and risk identification. First, a gated attention mechani...
Amidst the escalating need for stable power supplies and high-quality communication services in remote regions globally, due to challenges associated with deploying a conventional power communication infrastructure and its susceptibility to natural d...
This paper proposes a one-to-one trajectory synthetization method with stable long-term individual mobility behavior based on a generalizable area embedding. Previous methods concentrate on producing highly detailed data on short-term and restricted...
Smart grids, together with the Internet of Things, are considered to be the future of the electric energy world. This is possible through a two-way communication between nodes of the grids and computer processing. It is necessary that the communicati...
The standard of manual operation in smart grid, which require accurate manipulation, is high, especially in experimental, practice, and training systems based on virtual reality (VR). In the VR training system, data gloves are often used to obtain th...
Supergrid graphs are derived by computing stitch paths for computerized embroidery machines. In the past, we have studied the Hamiltonian-related properties of supergrid graphs and their subclasses of graphs. In this paper, we propose a generalized g...
Accurate forecasting of city-level large-scale traffic flow is crucial for efficient traffic management and effective transport planning. However, previously proposed traffic flow prediction methods model dynamic spatial correlations across entire tr...
Power grids are constantly evolving, and data changes are increasing. Operational technology (OT) is controlled by IT technologies in smart grids, where changes in the physical world impose changes in the software data model, as well as the continuou...
The objective imbalance between the taxi supply and demand exists in various areas of the city. Accurately predicting this imbalance helps taxi companies with dispatching, thereby increasing their profits and meeting the travel needs of residents. Th...
Energy saving and emission reduction have become common concerns in countries around the world. In China, with the implementation of the new strategy of “carbon peak and neutrality” and the rapid development of the new smart grid infrastr...
Based on the four sets of faults data measured in the practical LCC-HVDC transmission project of China Southern Power Grid Tianshengqiao (Guangxi Province, China)–Guangzhou (Guangdong Province, China) HVDC transmission project, a fault diagnosi...
With the in-depth integration of electric vehicles (EVs) and smart grids, the Cyber–Physical System for Vehicle–Grid (CPSVG) has become a crucial component of power systems. However, its inherent characteristic of deep cyber–physica...
Photovoltaic power generation prediction is crucial for the effective integration of renewable energy into the grid, real-time grid balancing, and the optimization of energy storage systems. However, PV power generation is highly dependent on environ...
We present a method of segmenting human parts in depth images, when provided the image positions of the body parts. The goal is to facilitate per-pixel labelling of large datasets of human images, which are used for training and testing algorithms fo...
Natural disasters have great destructive power and can potentially wipe out great lengths of power lines. A resilient grid can recover from adverse conditions and restore service quickly. Therefore, the present work proposes a novel methodology to re...
The grid terminal deploys numerous types of communication equipment for the digital construction of the smart grid. Once communication equipment failure occurs, it might jeopardize the safety of the power grid. The massive amount of communication equ...
The gradual increase in the maturity of sensor electronics has resulted in the increasing demand for wireless sensor networks for many industrial applications. One of the industrial platforms for efficient usage and deployment of sensor networks is s...
With the increasing complexity of modern power systems, traditional risk assessment methods relying on expert experience and historical data face challenges in accuracy and adaptability. This study proposes a knowledge graph-augmented ERNIE-CNN metho...
An efficient, hierarchical, two-dimensional (2D) path-planning method for large complex environments is presented in this paper. For mobile robots moving in 2D environments, conventional path-planning algorithms employ single-layered maps; the propos...
In the last decade, the main attacks against smart grids have occurred in communication networks (ITs) causing the disconnection of physical equipment from power networks (OTs) and leading to electricity supply interruptions. To deal with the deficie...
Air target intention recognition (ATIR) is critical for unmanned systems in modern air defense operations. Through the analysis of typical air defense combat scenarios, first, the paper defines the intention space and intention parameters of air unit...
This paper presents a time-dependent reliability analysis created for a critical energy infrastructure use case, which consists of an interconnected urban power grid and a communication network. By utilizing expert knowledge from the energy and commu...
This paper examines an approach that allows one to build an efficient system for protecting the information resources of smart power supply networks from cyberattacks based on the use of graph models and artificial neural networks. The possibility of...
The loss of power grid efficiency is affected by a number of factors, including the physical characteristics of the equipment used, the operational characteristics of the power grid itself, the characteristics of the electricity being used, and the n...
High voltage direct current (HVDC) transmission systems play a critical role to optimize resource allocation and stabilize power grid operation in the current power grid thanks to their asynchronous networking and large transmission capacity. To ensu...
In recent years, near-field networks have become a vital part of smart grids, raising growing concerns about their security. Studying threat evolution mechanisms is key to building proactive defense systems, while early identification of threats enha...
Despite notable advances in load forecasting and fault detection, current power system operation and maintenance (O&M) technologies remain fragmented into independent and primarily reactive modules. Load forecasting estimates future demand, where...
There is an increasing interest in low voltage direct current (LVDC) distribution grids due to advancements in power electronics enabling efficient and economical electrical networks in the DC paradigm. Power flow equations in LVDC grids are non-line...
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