Transmission Line Failures Research Articles

Transmission Defense Hardening Against Typhoon Disasters Under Decision-Dependent Uncertainty

Transmission defense hardening (TDH) is an effective practice to ensure the safe operation of the power system during and after natural disasters, such as typhoons. However, the coupling among the typhoon disaster, hardening decision, and transmission line status is not addressed in the previous research works. Besides, the enhancement measures for different types of transmission line failures have not yet been assessed. This paper proposes a comprehensive framework to improve power transmission system resilience against typhoon disasters. Firstly, the motion path and the wind field of typhoons are simulated using Monte Carlo sampling to quantify the spatiotemporal impacts of wind speed on the transmission line status. The decision-dependent uncertainty (DDU), which reflects the effects of hardening decisions on the transmission lines, is addressed by sampling according to the corresponding failure probabilities. Then, the scenario simulation is integrated into the proposed two-stage stochastic mixed-integer programming (SMIP) model considering various enhancement measures for different failures. Since the way to handle the DDU needs a large number of scenarios, it leads to high computation complexity. Hence, the sample average approximation (SAA) algorithm is introduced to cope with it. Finally, the proposed framework and its solution algorithm are carried out on the modified IEEE RTS-79 system and the modified IEEE 118-Bus system. The significant cost saving and resilience improvement demonstrate the effectiveness of the proposed framework.

Proactive Security-Constrained Unit Commitment Against Typhoon Disasters: An Approximate Dynamic Programming Approach

Proactive security-constrained unit commitment (SCUC) is one of the effective resilience-oriented responses to keep the secure operation of the power system during natural disasters. The approaches proposed in the previous research works cannot guarantee high-quality response timely to various emergencies during typhoon disasters. This paper proposes a proactive SCUC model solved by an approximate dynamic programming (ADP) algorithm to improve system resilience during typhoon disasters while meeting the requirements of the computational time. Both the uncertainty of the typhoon motion path and the wind speed-dependent transmission line failure probability are considered in the scenario generation. The optimization process is formulated as a Markov decision process (MDP), and a piecewise linear function (PLF) based ADP is employed for solving the model. With the exogenous information extracted from generated scenarios and recorded in the slopes of PLFs, the ADP algorithm can result in a near-optimal solution within a short computational time. Simulations are carried out using the modified IEEE RTS-79 system. The significant computational time saving and high-quality solution demonstrate the effectiveness of the proposed approach.

Analytical prediction of quasi-static responses of transmission lines under moving downbursts: A nonlinear model with linear approximation

Downbursts wind are believed to be responsible for most of weather-related transmission line failures worldwide. Based on a theoretical model of a hinged single-span transmission line structure under moving downbursts, this paper studies downburst -induced vibration of a multi-span transmission line-insulator system (MSTLIS). Firstly, a nonlinear analytical framework for quasi-static responses of the MSTLIS under moving downbursts is established, and linearized equations of the MSTLIS under moving downbursts with time-varying mean wind speeds are derived. Then, the influence line functions of the insulator tension and displacement of the MSTLIS are derived, based on which the quasi-static responses of the MSTLIS under fluctuating wind is calculated. A case study on a six-span transmission line-insulator subsystem is conducted. The proposed nonlinear analytical model and the approximate linearization approach is verified by finite element model (FEM) results. The proposed analytical framework with linear approximation is accurate and more efficient than FEM, and hence has a great potential for real application.

Research on lighting fault identification technology of transmission lines based on non-contact sensing

According to field operation records, lightning stroke accounts for 60% of transmission line failures. Therefore, it is of great significance to strengthen lightning protection of the power system. However, there are several lightning faults, and the corresponding protection methods differ. Consequently, identifying lightning stroke faults will be beneficial to take corresponding lightning protection measures. This paper investigates the mechanism of different lightning strike faults, and simulates them by a 110kV transmission line EMTP-ATP model. Analysis and simulation show that the direction of tower current represents lightning’s polarity; the insulator voltage’s direction differs when shielding failure or back striking occurs. If insulator flashovers, the voltage of the insulator drops down to zero, and as the transient process comes to an end, the voltage of the insulator on the nearby tower decreases to zero as well; after the occurrence of back striking flashover, the direction of insulator voltage on nearby tower alters. Based on those features, insulator voltage and tower current are introduced as a characteristic signal, and their direction and rms of them are formed as recognition parameters for lightning stroke identification. The EMTP-ATP simulations demonstrate that the proposed method is correct and effective, and the recognition rate of different lightning faults is 100% under the abovementioned method.

Adaptive Network Response to Line Failures in Power Systems

Transmission line failures in power systems propagate and cascade nonlocally. In this work, we propose an adaptive control strategy that offers strong guarantees in both the mitigation and localization of line failures. Specifically, we leverage the properties of network <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">bridge-block decomposition</i> and a frequency regulation method called the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">unified control</i> . If the balancing areas over which the unified control operates coincide with the bridge-blocks of the network, the proposed strategy drives the postcontingency system to a steady state where the impact of initial line outages is localized within the areas where they occurred whenever possible, stopping the cascading process. When the initial line outages cannot be localized, the proposed control strategy provides a configurable design that progressively involves and coordinates more balancing areas. We compare the proposed control strategy with the classical automatic generation control (AGC) on the IEEE 118-bus and 2736-bus test networks. Simulation results show that our strategy greatly improves overall reliability in terms of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N-k$</tex-math></inline-formula> security standard, and localizes the impact of initial failures in the majority of the simulated contingencies. Moreover, the proposed framework incurs significantly less load loss, if any, compared to AGC, in all our case studies.

Research on identification method of weak links in transmission network considering strong wind in severe cold weather

The ice disaster has brought many adverse effects on the power transmission system, which is mainly studied from the transmission line failure rate perspective. Strong winds often accompany the ice disaster weather, the motion path of wind is considered when identifying the weak location of transmission network system. According to the theory of meteorological simulation, and the mathematical relationship between the effective wind speed and the forced outage rates is obtained. A transient stability risks assessment method is proposed considering the ice disaster in the case of a strong wind moving path. According to the fault probability of transmission lines, a predictive fault set for power grid risk assessment is established. The IEEE-39 bus system is used as an example to analyze the effectiveness of the proposed method. The simulation results show that meteorological parameters, geographical environment, and other factors, especially the meteorological advance speed and the direction of transmission lines, will cause greater damage to the stability of the transmission system.

Review of Aging Evaluation Methods for Silicone Rubber Composite Insulators

Silicone rubber insulation material is widely used for the external insulation of power systems. During the continuous service of a power grid, it will be seriously aged due to the influence of high voltage electric fields and harsh climate environments, which will reduce its insulation performance and service life and cause transmission line failure. How to evaluate the aging performance of silicone rubber insulation materials scientifically and accurately is a hot and difficult issue in the industry. Starting from the composite insulator, which is the most widely used insulating device of silicone rubber insulation materials, this paper expounds the aging mechanism of silicone rubber materials, analyzes the applicability and effectiveness of various existing aging tests and evaluation methods, especially discusses the magnetic resonance detection methods emerging in recent years, and finally summarizes the characterization and evaluation technology of the aging state of silicone rubber insulation materials.

TRANSMISSION LINE CRISIS MANAGEMENT

Multiple failures of transmission lines caused by climatic/atmospheric impact plague many electric power systems. Direct damage from such failures is quite huge, yet it is marginal compared with the social damage caused by the reduction in the supply of electricity. As it is not economical to construct weatherproof transmission lines, preventive actions should be employed the most effective restoration, or to reduce restoration time. A working group of CIGRÉ (WG B2 13) has prepared emergency guidelines based on the experience of large-scale disruptions. Our experience with multiple transmission line failure, as well as the importance of our power grid, lead to the conclusion that it would be wise for HEP OPS to begin with an appropriate organisation of preventive actions in agreement with HERA. To a lesser extent, this also applies to 400 kV buses.

Data-Integrity Aware Stochastic Model for Cascading Failures in Power Grids

The reliable operation of power grids during cascading failures is heavily dependent on the interdependencies between the power grid components and the supporting communications and control networks. Moreover, the system operators’ expertise in dealing with cascading failures can play a pivotal role during contingencies. In this paper, a dynamical probabilistic model is developed based on Markov-chains, which captures the dynamics of cascading failures in the power grid. Specifically, a previously developed Markov-chain based model is extended to capture the trade-off between the benefits of having a robust communication infrastructure and its vulnerability from data integrity (e.g., cyber-attacks). State-space reduction of the complex interactions between power grids, communication networks and system operators is achieved by judiciously specifying the state variables of the Markov chain. The impact of system operators’ probability of error during a cascade-mitigation action is incorporated into the model as a function of the state variables of the Markov chain. A point of diminishing returns is observed beyond which the effect of information infidelity outweighs the benefits of having more information. For a given level of cyber threat, an optimal size of a communication network is observed that minimizes the expected number of transmission-line failures before the cascade stops.

Power system contingency classification using machine learning technique

One of the most effective ways for estimating the impact and severity of line failures on the static security of the power system is contingency analysis. The contingency categorization approach uses the overall performance index to measure the system's severity (OPI). The newton raphson (NR) load flow technique is used to extract network variables in a contingency situation for each transmission line failure. Static security is categorised into five categories in this paper: secure (S), critically secure (CS), insecure (IS), highly insecure (HIS), and most insecure (MIS). The K closest neighbor machine learning strategy is presented to categorize these patterns. The proposed machine learning classifiers are trained on the IEEE 30 bus system before being evaluated on the IEEE 14, IEEE 57, and IEEE 118 bus systems. The suggested k-nearest neighbor (KNN) classifier increases the accuracy of power system security assessments categorization. A fuzzy logic approach was also investigated and implemented for the IEEE 14 bus test system to forecast the aforementioned five classifications.

Analysis of shielding failure of transmission line based on pilot model

Since the main way of power transmission in China is overhead line transmission, some overhead lines are in a harsh outdoor environment. Among them, the bypass attack is more serious. Shielding Failure is a severe form of lightning damage. Based on the situation, this article studies the lightning shielding phenomenon of transmission lines. This article uses the pilot development model to simulate the lightning strike process, analyzes the different target objects of the lightning strike, and elaborates and calculates the lightning shielding trip rate. In addition, by changing the protection angle, the height of the tower, the ground inclination of the area where the line is located, and the number of lines, the impact of these four factors on the lightning shielding trip rate is discussed. According to the influencing factors, measures to strengthen the lightning protection performance of the line are proposed.

Portable Non-Destructive Magnetic Resonance Sensor for Assessing the Aging Status of Silicon Rubber Insulators.

Silicone rubber insulators (SRIs) are widely used in high-voltage power grids. Due to high-voltage fields and harsh environmental conditions, SRIs eventually deteriorate with use in the power grid, decreasing their insulating performance and operational life and contributing to transmission line failures. Therefore, quantitatively assessing the aging status of SRIs is crucial. In this study, we evaluated the viability of the magnetic resonance method for assessing the age of SRIs at the level of chemical structure; we built and made a portable magnetic resonance sensor, and evaluated the sensor's functionality. By measuring the SRI sheds at various service times, it was discovered that the equivalent transverse relaxation time, T2eff, can describe the degree of aging of the SRIs. The results of the magnetic resonance measurements were also compared with those of the static contact angle method, and the two measurement methods yielded the same conclusions. However, the magnetic resonance method was more sensitive than the one using the static contact angle method.

Algorithm for Solving Trip‐Out Rate Due to Shielding Failure of Bent Transmission Line

Accurate assessment of lightning protection performance of extra high voltage transmission lines is important for transmission line design and different lightning protection. Based on the electro‐geometrical model, this paper introduces the angle influence factor, and presents an algorithm for shielding failure trip‐out rate of angle tower, and the existing algorithm is expanded. By establishing the three‐dimensional geometric model of the angle tower, the electrical geometric relations of conductors and ground wires on both sides are analyzed, respectively, and the projection area algorithm for shielding failure is modified. To further verify the application value of the calculation algorithm, the change of the shielding failure trip‐out rate of the typical angle tower with the bending angle of transmission line and the tower height in a 500 kV transmission line is analyzed. The analysis results show that the trip‐out rate of the outside corner is higher than that of the inside one, and with the increase of the angle and the height of the tower, the trip‐out rate shows an upward trend. When the tension tower height is 71.5 m and the angle increases from 0° to 80°, the outside shielding failure trip‐out rate increased by 10.9% and the inside decreased by 9.3%. Compared with the classical electro‐geometrical model calculation, the difference of trip‐out rate is 4.3% when the bending angle is 80°. When the tangent tower height is 70 m and the angle increases from 0° to 40°, the shielding failure trip‐out rate on the outside increased by 5.9% while the inside decreased by 6.2%. The research results provide a simple algorithm for solving bending transmission line and give some reference for lightning protection design of EHV transmission lines. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Effect of Particle Trap on Motion Characteristics of Metal Particles in AC GILs and Parameter Optimization

Metal particle contamination is an important reason for insulation failure of gas-insulated transmission lines (GILs). Particle trap is the common method for particle suppression. At present, research on the motion characteristics of metal particles near a particle trap and the optimization of trap parameters under AC voltage is insufficient. Based on that, firstly, a dynamic model of metal particles under AC voltage was established, and the motion characteristics of particles in front of the trap were studied, combined with experiments. Then, the influence of trap parameters on the capture effect was analyzed, and the optimization of the trap was realized by simulation. The results showed that, under AC voltage, the randomness of metal particle movement was strong, and the activity was low. The particles mainly moved away from the trap. Among the particles moving towards the trap, some stayed in front of the trap, and some fell into the trap from above. The thickness and height of the trap were the key parameters affecting the capture effect, and with the increase in height and thickness, the capture rate showed a trend of increasing first and then decreasing. The above conclusions can provide a reference for the optimization of a metal particle trap under AC voltage in engineering.

Numerical model of cascade failure of transmission lines under downbursts

Transmission line’s cascades have played a major role in several serious accidents around the world, as they are particularly prone to occurring in the presence of strong winds. The failure of a line component overloads the system, inducing a progressive failure that can involve many transmission line (TL) supports. Due to their localized nature, downbursts, in particular, cause unequal wind forces on various towers of a transmission line; the collapse of one tower can affect the adjacent towers through the unbalanced forces that develop in the conductors, which can lead to a cascaded-type of failure along the entire line. In this study, a numerical model is developed in-house to predict this type of line failure. A major challenge in this numerical model is the prediction of the geometric configuration of the tower and of the conductor forces after the tower collapses. Details of this unique numerical model are presented in this paper along with a case study for illustration.

Critical Propagation Path Identification for Cascading Overload Failures With Multi-Stage MILP

Cascading overload failures of transmission lines are one of the dominant factors that induce catastrophic blackouts. The reliability risk of cascading overload failures is significantly underestimated in traditional adequacy assessment studies. This paper proposes an evaluation model for the assessment of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N-k</i> contingencies as cascading overloading failures. The interactions between outaged lines in the propagation path are revealed with a multi-stage optimization problem. The objective function is to maximize the probability of the propagation path of cascading overload failures. Several linearization techniques are proposed to convert the nonlinear evaluation model to mixed-integer linear programming. A rolling search algorithm is adopted to improve the capability of the proposed model to evaluate high-order contingencies. The case studies on the IEEE 118-bus systems show that the proposed model enables the identification of critical propagation paths with probabilities that are a few orders of magnitude larger than those with the traditional method.

A Criterion and Stochastic Unit Commitment Towards Frequency Resilience of Power Systems

High-capacity long-distance transmission lines, such as high-voltage direct-current (HVDC) lines, are vulnerable to extreme weather. Their failures may cause significant power loss and frequency drop in the receiving-end power systems, which should be considered in the power system scheduling. In this paper, the failure rates of transmission lines subject to extreme weather conditions are firstly modeled to obtain the probability of failure events. Then, a novel criterion defined by the integration of abnormal frequency during the primary and secondary frequency regulation process is proposed to measure frequency security. This criterion is capable to reflect the cumulative frequency deviation effect and distinguish the contributions of different frequency regulation reserve providers, e.g., generators and flexible loads. Moreover, the linearity of the criterion makes it easy to be incorporated into optimization problems. Finally, a two-stage stochastic frequency constrained unit commitment (FCUC) model is developed to optimally schedule generators and flexible loads while satisfying the frequency security constraints under transmission line failure events. The proposed FCUC model is efficiently solved by a regularized L-shape algorithm. The proposed model and techniques are validated based on the modified IEEE 118 and 300 bus systems with realistic meteorological data.

Mitigating Faults and Revenue Losses Using Fault Detectors at Trans Amadi Industrial Layout, Port Harcourt Rivers State

Abstract: Transmission line fault detection is an important aspect of monitoring the health of a power plant since it indicates when suspected faults could lead to catastrophic equipment failure. This research looks at how to detect generator and transmission line failures early and investigates fault detection methods using Artificial Neural Network approaches. Monitoring generator voltages and currents, as well as transmission line performance metrics, is a key monitoring criterion in big power systems. Failures result in system downtime, equipment damage, and a high danger to the power system's integrity, as well as a negative impact on the network's operability and dependability. As a result, from a simulation standpoint, this study looks at fault detection on the Trans Amadi Industrial Layout lines. In the proposed approach, one end's three phase currents and voltages are used as inputs. For the examination of each of the three stages involved in the process, a feed forward neural network with a back propagation algorithm has been used for defect detection and classification. To validate the neural network selection, a detailed analysis with varied numbers of hidden layers was carried out. Between transmission lines and power customers, electrical breakdowns have always been a source of contention. This dissertation discusses the use of Artificial Neural Networks to detect defects in transmission lines. The ANN is used to model and anticipate the occurrence of transmission line faults, as well as classify them based on their transient characteristics. The results revealed that, with proper issue setup and training, the ANN can properly discover and classify defects. The method's adaptability is tested by simulating various defects with various parameters. The proposed method can be applied to the power system's transmission and distribution networks. The MATLAB environment is used for numerous simulations and signal analysis. The study's main contribution is the use of artificial neural networks to detect transmission line faults. Keywords: Faults and Revenue Losses

Line Failure Localization of Power Networks Part II: Cut Set Outages

Transmission line failure in power systems prop-agate non-locally, making the control of the resulting outages extremely difficult. In Part II of this paper, we continue the study of line failure localizability in transmission networks and characterize the impact of cut set outages. We establish a Simple Path Criterion, showing that the propagation pattern due to bridge outages, a special case of cut set failures, are fully determined by the positions in the network of the buses that participate in load balancing. We then extend our results to general cut set outages. In contrast to non-cut outages discussed in Part I whose subsequent line failures are contained within the original blocks, cut set outages typically impact the whole network, affecting the power flows on all remaining lines. We corroborate our analytical results in both parts using the IEEE 118-bus test system, in which the failure propagation patterns exhibit a clear block-diagonal structure predicted by our theory, even when using full AC power flow equations.

Line Failure Localization of Power Networks Part I: Non-Cut Outages

Transmission line failures in power systems propagate non-locally, making the control of the resulting outages extremely difficult. In this work, we establish a mathematical theory that characterizes the patterns of line failure propagation and localization in terms of network graph structure. It provides a novel perspective on distribution factors that precisely captures Kirchhoff's Law in terms of topological structures. Our results show that the distribution of specific collections of subtrees of the transmission network plays a critical role on the patterns of power redistribution, and motivates the block decomposition of the transmission network as a structure to understand long-distance propagation of disturbances. In Part I of this paper, we present the case when the post-contingency network remains connected after an initial set of lines are disconnected simultaneously. In Part II, we present the case when an outage separates the network into multiple islands.