Grid Accidents Research Articles

Power grid accident warning based on real-time analysis of hazard sources and weights

Abstract The power grid system has diverse structures consisting of multiple subnets, equipment, and components that are interrelated and mutually influential. At the same time, there are various types of power grid accidents, including short circuits, open circuits, overloads, grounding faults, etc. Each type of fault may have its specific cause and manifestation. This complexity and diversity make establishing a comprehensive and accurate early warning model difficult. Therefore, this study proposes an adaptive warning method based on hazard sources and weighted coefficients for power grid accidents. To transform raw data containing a large amount of redundant information and noise into data with targeted features for representation, power grid accident information feature labels are generated based on weighted coefficients. Based on this, based on the improved YOLOv3, potential risks in the power grid are identified and assessed. Identification based on implementing risk prevention and control measures defines multiple warning levels to achieve adaptive warning of power grid accidents. Test data validation shows that the proposed solution has an accuracy up to 97.85%. There is also a significant improvement in other indicators, all of which remain above 98%. Indicator validation shows that the research method meets the actual process standards. For the entire day period, the precision and recall of the research method remained stable at over 90%.

Scenario construction and vulnerability assessment of natural hazards-triggered power grid accidents

In light of escalating urbanization trends and climate change impacts worldwide, the susceptibility of urban power grids to natural disasters has become an overarching global concern. Prior research has predominantly concentrated on singular calamities while often disregarding cumulative repercussions from multiple concurrent events affecting power grid resilience. This investigation presents an exhaustive framework for assessing grid vulnerabilities by quantifying diverse impacts from potential natural disaster scenarios and delineating adaptive pathways for evaluating inadvertent occurrences. The framework amalgamates an extensive array of metrics— including probability assessments, system state evaluations, trigger threshold analyses, responsiveness measurements, and adaptability adjustments— within a dynamic scenario-oriented model. The inquiry progresses through distinct stages: formulating an all-encompassing methodology for assessing vulnerabilities; assessing varied impacts stemming from different environmental perils; mapping out post-disaster evolutions; and executing a case analysis focusing on an urban power grid.Concentrating specifically on rainfall, snowfall, and freezing incidents, the case analysis uses locale-specific data to appraise grid susceptibilities while employing multi-criteria decision analysis (MCDA) to facilitate decision-making. During this deliberative process, optimal strategies are derived, and mitigative actions are recommended with the aim of diminishing power-grid vulnerabilities. This investigation underscores intricate risk dynamics within urban power grids while presenting a feasible framework for sustainable planning and effective emergency responses in confronting natural hazards.

Research on key technologies of digital sensing and fault warning of isolation switch in GIS

Abstract GIS device is a small electrical device. It is widely used in power systems due to its small size, easy installation, reliable operation, and anti-noise. In recent years, GIS isolation switches have frequently caused power grid accidents due to their own reasons, causing great economic losses to the power grid and users. Therefore, in GIS, in order to improve the stability of the power system, the isolation switch in GIS must be monitored and fault diagnosed. This article analyzes the primary and secondary working mechanisms of GIS. Starting from the basic principles of primary and secondary, this paper conducts a theoretical analysis of various parameters in GIS, and conducts a simple analysis of its sensing performance and monitoring system. It also briefly introduces common faults in GIS, providing a theoretical basis for research on key technologies of digital sensing and fault warning of isolation switch in GIS.

Impacts of battery energy storage system on power grid smartness: Case study of Taiwan Power Company

This case study work aims to quantitatively validate the hypothesis that battery energy storage system (BESS) can enhance the smartness of power grid. Our targeted power grid was the Taiwan Power Company (Taipower), which ranked second worldwide in both 2021 and 2022 according to the Smart Grid Index (SGI), a global grid smartness indicator. Besides collecting data from Taipower, this study examined 53 upstream and downstream energy storage companies and 48 ancillary service companies in Taiwan. Through cross-domain data analysis, the evidences were obtained to verify the hypothesis.The initial piece of evidence suggests that BESS is a key evaluation indicator for determining the smartness of a power grid. Of the 36 and 38 power utilities in 2021 and 2022, 77.8–80 % of power utilities with high smartness scores were equipped with energy storage systems, compared to only 14.3–15 % of power utilities with low scores.Further evidence indicates that the data on two power failure events indicate BESS can prevent power grid accidents. Thus, the supply reliability can be improved. Estimated data shows that annual SAIDI index scores dropped from 14.936 to 11.978 and SAIFI index scores dropped from 0.185 to 0.151 after the implementation of BESS.The third piece of quantitative evidence is that data on grid-level BESS construction achievements shows that SGI scores increased from 28.0 to 94.6 over five years, moving from a ranking lower than the global average to rank second in the world.In addition to verify the hypothesis, the aforementioned evidences also lead to novel results. This case study is pioneering in its first-time analysis of state grid data and the organization of items of smartness within global girds, resulting in a proposed flowchart for constructing a smart grid. The establishment of the flowchart will contribute to enhancing the smartness of power grids through the design of ancillary services.

Detection of false data injection attacks on power systems based on measurement-eigenvalue residual similarity test

Existing False data injection attack (FDIA) detection methods based on measurement similarity testing have difficulty in distinguishing between actual power grid accidents and FDIAs. Therefore, this paper proposes a detection method called the measurement-eigenvalue residual similarity (MERS) test, which can accurately detect FDIAs in AC state estimationof power system and effectively distinguish them from actual power grid accidents. Simulation results on the IEEE 39-bus system demonstrate that the proposed method achieves higher detection rates and lower false alarm rates than traditional methods under various operation conditions.

Research on the construction and implementation of power grid fault handling knowledge graphs

Power grid fault disposal has important guiding significance for the efficient and orderly emergency work of power grid accidents. The knowledge graph technology is used to extract, express and manage the fault disposal information. It is also used to assist dispatchers in fault handling, which can effectively improve the power grid emergency handling capacity and dispatching intelligence level. The unstructured content in the form of a large number of texts in the power grid dispatching operation link is condensed into a structured knowledge network that can be expressed, operated and reasoned. For example, operating procedures, disposal plans, dispatching rules, etc. A top-down and bottom-up knowledge graph construction method for power grid fault handling is proposed. The knowledge graphs are divided into three categories: entity graph of power grid equipment, logic graph of fault handling and case graph. The data and technical means required for graph construction are described. In the process of practice, the knowledge organization structure, notion types, and relationships between notions of the knowledge graphs are defined to form the model layer of knowledge graph. Finally, according to the function realization of each link, the solution ideas and key technologies are analyzed. So as to realize fault information analysis and discrimination based on knowledge atlas, intelligent aided decision-making and multi-dimensional human–computer interaction.

A dynamic and integrated approach of safety investment decision-making for power grid enterprises

Recently, the consequences caused by frequent large-scale power grid accidents are more significant with arousing great attention of power grid enterprises. Scientific safety investments are essential to improve the overall safety level of the power grid enterprises and promote safe production. This study proposed a dynamic and integrated approach for safety investment decision-making of power grid enterprises based on the entropy weight method (EWM) and the system dynamics (SD) theory. By applying the accident loss assessment and the safety performance evaluation, the SD-based model for the safety investment decision-making for power grid enterprises was developed. The results show that risk assessment is the critical factor for power grid safety, followed by safety training, organizational investment, and technological investment. Moreover, the proposed safety investment decision-making model can be continuously updated and optimized with future emerging data to support the dynamic prediction of power grid safety investment.

The Vibroacoustic Characteristics Analysis of Transformer Core Faults Based on Multi-Physical Field Coupling

Power transformers play an important role in the safe and reliable operation of the whole power grid. Once a fault occurs, it will endanger the normal operation of the transformer, and even result in power grid accidents. Accurate and practical methods of transformer fault monitoring and type identification have attracted extensive attention in the field of electrical engineering. However, it is difficult to obtain a large number of measurement data for different fault types on a large power transformer. The vibroacoustic characteristics of transformer faults have significant asymmetry. For the power transformer in service, it is complex and uneconomic to obtain the vibroacoustic signals under different fault conditions. To handle this problem, this paper proposes simulation methods of several common transformer core faults, based on multi-physical field coupling, and then analyzes the vibroacoustic signals generated by the operating transformer. Finally, it verifies the results of acoustic and vibration signals under several faults, through physical experiments. The results show that the transformer fault simulation method is reasonable and accurate. Furthermore, a change in the transformer core state will cause a change in the transformer vibroacoustic characteristics, and different types of core faults can be distinguished by the analysis of vibroacoustic characteristics.

A safety investment optimization model for power grid enterprises based on System Dynamics and Bayesian network theory

In recent years, frequent large-scale power grid accidents have caused serious economic losses and bad social impact, which has drawn great attention from power grid enterprises. As one of the key elements of production, safety investment plays an important role in improving the safety level and reducing accident loss. In this paper, System dynamics (SD) and Bayesian network (BN) are integrated to develop a novel safety investment optimization model for power grid enterprises, which takes into account the impact of safety investment factors on accidents and the interactions between them. Based on sensitivity analysis, critical safety investment factors are determined to form the subsystem of the SD model. Subsequently, the optimal safety investment strategy is determined by a three-step simulation. The simulation results show that there are barrel effects and a diminishing marginal utility in safety investment. The proposed safety investment optimization model is practical to provide technical supports and guidance for determining an effective safety investment strategy in power grid enterprises.

Geomagnetically Induced Current-Monitoring Method Based on High Voltage Wires for Transformers

Hall sensors have a relatively low withstand voltage but have been used at the neutral point of transformers to monitor geomagnetically induced currents (GICs). However, when introduced into monitoring devices via sensor wiring, high voltages at the transformer neutral point can lead to damage to electronic components and increase the risk of serious power grid accidents. For monitoring GICs from the neutral point of the transformer, this paper proposes a transformer GIC monitoring method based on high-voltage wire equipotentials and a transformer GIC power (GIC-Q) algorithm based on the proportional coefficient K value method. A transformer monitoring device based on the proposed methods was tested at a 500 kV substation in China. In addition, we verified the accuracy of the proposed method and validity of the monitoring data produced using geomagnetic disturbance data with a Kp-index of 4 from the Man Zhouli Geomagnetic Observatory Station.

Research on Influencing Factors of Power Grid Security Risk Based on “Cognitive-Constraint” Model

With the improvement of the intelligent level of the power grid, the operation safety of the power system has received extensive attention. The current accident analysis mostly relies on the experience of personnel, which is prone to omissions. Firstly, this article analyzes the safety risk factors of power grid accidents from four aspects: man factors, equipment factors, management factors, and environmental factors based on the accident causes theory. Secondly, the fault tree model is used to explore the mechanism of each failure factor and quantify the structural importance of each event. Finally, summarize the rules of accidents and make reasonable suggestions for scientifically and reasonably avoiding similar accidents and building a safe power grid.

The influence of excavation of combined foundations of high-voltage transmission towers and spoils loading on landslide stability

With the construction of “West-to-East Power Transmission” and national networked engineering projects, high-voltage transmission towers, which are important components of transmission lines, are important power engineering facilities. They are inevitably erected on the ridges, edges of steep slopes, and river banks. Therefore, induced by internal factors and external factors, it is easy to cause landslide disasters in these areas, resulting in power grid accidents such as tilting of power poles, disconnections, and trips. This article takes the Yanzi landslide in Badong County and 500kV transmission tower on the landslide as the research object. For the combined foundation excavation form of the tower foundation, the relative positions of different tower foundations and landslides and the loading of spoil are analyzed. The influence of excavation of transmission tower foundation and pile dumping on the stability of the landslide is discussed. The research results show that the effect of the combined foundation excavation on the stability of the landslide is negligible, but it will affect the stability of the local landslide, and the stability of the local landslide is related to the relative position of the tower foundation and the landslide. In addition, the pile loading of spoil will also affect the stability of local landslides, and the degree of impact is related to the size of the spoil pile.

Design and Application of a Case Analysis System for Handling Power Grid Operational Accidents Based on Case-Based Reasoning

In recent years, power grid accidents have occurred frequently and higher requirements have been placed on their safety operation. In current safety management in the world, there is an effective practice that uses a unified standard for structuring an accident case database and based on that database, conducts quantitative analysis to cope with accident risks. However, that is not the case for power safety management. Case-based reasoning (CBR) is such a process that solves new problems based on the solutions to similar past problems. It works by matching a current problem with historical cases and solutions in a database, in order to obtain similar case solutions or inspirations. In the matching process, if necessary, such past solutions may be modified in order to better adapt to the current actual problems. Based on the CBR method, this paper proposes how to construct a case database of power grid operational accidents, provide data support for management of power grid risks and provide knowledge services for accurate grasping of grid accident development dynamics and making quick decisions to rapidly response to the emergencies. First, it designs an operational accident case database after considering the following three aspects: case features, power grid features and accident features based on safety management theory. Secondly, in terms of how to use the power grid operational accident case database, it proposed a two-level search strategy, as well as the corresponding similarity calculation methods for different feature attributes of the case. Finally, it carried out a demonstration to verify the model by selecting four typical grid accidents. The grid database and CBR strategy proposed in this article could help China’s power grids practice intelligent analysis of grid operational accidents and improve digitalization in safety management.

Development of multi‐parameter online monitoring equipment for EHV transformer bushing

To diagnose the running state of bushing and avoid serious power grid accidents, online multi-parameter monitoring equipment for dissolved hydrogen, oil pressure and temperature in bushing oil was developed. The equipment includes three units: signal acquisition, control cabinet and data analysis. A new hydrogen sensor without oil–gas separation membrane and based on palladium alloy film technology was developed. A three-in-one sensor for hydrogen, oil temperature and pressure monitoring has been developed, which has the advantages of miniaturisation, lightweight and easy installation. Test results show the hydrogen measurement range of the sensor is 0–5000 ppm, and the accuracy can reach 10% or 15 ppm (with larger values). The pressure measurement range is 0–1.0 MPa, the resolution is 0.1 kPa, and the accuracy can reach 0.25 grade. The temperature measurement range is −40 to 105°C, and the accuracy is ±1°C. The measurement performance of the device fully meets the requirement of online monitoring of transformer bushing. The equipment has been put into operation in a 330 kV substation, which can monitor the bushing status online and help eliminate the early latent fault of bushing in the weak budding state.

State Early Warning Technology for UHV AC Substation Equipment

With the development of UHV power transmission and transformation projects in China, as a key technology to prevent power grid accidents caused by faults of power transmission and transformation equipment, the state early warning technology of UHV AC power transformation equipment urgently needs to carry out and perfect corresponding research. This paper introduces the key technology of state warning for UHV AC substation equipment, and analyzes the principle and method of state alarm technology. And put forward the views on the current problems and future development of UHV AC equipment status warning technology.

An Intelligent Per-decision Method of State Grid Accidents in Big Data Environments

Aiming at the problem of hard to per-alarm the state grid accidents in big data environment, this paper proposes an intelligent per-decision method of state grid accidents. This method divides the management of state grid data into two parts, i.e. analysis of state grid data and intelligent expert database. The part of analysis of state grid data consists of input layer, facility layer and accident layer. Establish the self-learning intelligent expert database by means of connecting weight values of input and output nodes and threshold values of output nodes. Compare with the per-data that comes from the part of analysis of state grid data and the data from intelligent expert database, then achieve the goal of per-decision of state grid accidents and dispatch the accidents. A case and simulation results show that this method is implementable. In addition, this method provides beneficial thinking to solve the state grid accidents per-alarm in big data environment.

Occurrence and countermeasures of urban power grid accident

With the advance of technology, the development of network communication and the extensive use of power grids, people can get to know power grid accidents around the world through the network timely. Power grid accidents occur frequently. Large-scale power system blackout and casualty accidents caused by electric shock are also fairly commonplace. All of those accidents have seriously endangered the property and personal safety of the country and people, and the development of society and economy is severely affected by power grid accidents. Through the researches on several typical cases of power grid accidents at home and abroad in recent years and taking these accident cases as the research object, this paper will analyze the three major factors that cause power grid accidents at present. At the same time, combining with various factors and impacts caused by power grid accidents, the paper will put forward corresponding solutions and suggestions to prevent the occurrence of the accident and lower the impact of the accident.

Frequency Response Model of Regional Power Grid Based on Parameter Identification on Trip Process of Transmission Line

Many large power grid accidents show that the tripped transmission line has great impact on system stability. The primary frequency regulation effects of generation units play key roles during a trip procedure. In this paper, a frequency stability dynamic mathematic model of regional power grid was built based on records of a practical trip accident of transmission line between regional grids. Key parameters of the model were identified. The identified parameters are within their reasonable regions. The simulation results show that the modeling method based on parameter identification can be used for modeling of transmission line trip accident procedure and relative frequency stability analyses on power grids.

Taxonomic analysis of Chinese power transmission and distribution industry accidents based on hazard components

Power transmission and distribution were critical components for the development of Chinese economy. As in all sectors of the economy it was important to reduce the accidents rate as low as possible. This research adapted accident taxonomic analysis to identify the main factors associated with accidents and then provided accident prevention countermeasures in the industry in China. Because of lack of systematic power transmission and distribution accident information in China, 324 power grid accidents from 1961 to 2008 were collected through a wide range of sources and classified according to hazard elements which were target and threat, hazard element and initiating mechanism respectively and then the initiating mechanisms were further classified by hazard types. Through taxon structures the direct and indirect factors were identified in the industry accidents and strategies of accident prevention were recommended based on them. The taxon structures also can be further developed to form tailored safety checklist for the front workers.

Analysis of Leak and Water Absorption Test Results for Water-Cooled Generator Stator Windings

Cases of insulation breakdown damage of water-cooled generator stator windings occur frequently due to coolant leakage and water absorption worldwide. Such serious accidents may cause not only enormous economic loss but also very serious grid accidents in terms of stable supply of electric power. More than 50 % of domestic generators have been operated for more than 15 years, and leak and water absorption problem of windings are often found during the planned preventive maintenance period. Since 2005, leak and water absorption tests have been performed for total watercooled stator windings after fully drying the inside of the windings. The results are then comprehensively analyzed. The result of the test performed by GE, a foreign manufacturer, for 141 generators showed failures in 80 of them (failure rate: 57 %), whereas in the tests carried out in Korean domestic power plants, only 14 out of 50 generators showed failures (failure rate: 28 %).