Line Tripping Research Articles

A general PMU placement approach considering both topology and system aspects of contingencies

In a wide area measurement system, line tripping as well as the following transient and dynamic post-contingency conditions affect the full observability of power systems and possibly the accuracy of the wide area monitoring system. In this paper, a general methodology is presented to solve the phasor measurement unit (PMU) placement problem considering both the system and the topology aspects of disturbances. To do that, the connectivity matrix-based PMU placement problem is firstly formulated in its basic binary integer form to meet the full observability of power systems. Next, the post-disturbance variations in power systems, as the system aspect, are integrated with the conventional placement problem to ensure the more accurate pre- and post-disturbance monitoring of power systems. In addition, the algorithm is developed to achieve the highest possible reliability for single transmission line outages, i.e. N – 1 contingencies, as the topology aspect. Other topology-related issues, including zero injections, PMU channel limitations, and pre-existing measurements are included in the new formulation as well. Since the effects of the two aspects of disturbances on the placement solution are conflicting, and as the magnitude of the system aspect is much stronger than that of topology aspects, compensations are added to balance the conflicting effects by mitigating the strong effect of the system aspect on the overall formulation. Therefore, the proposed methodology will lead to a placement scheme, by which providing the full observability of the system under a high number of single line outages as well as obtaining the more accurate post-disturbance monitoring of power systems are assured. The performance and effectiveness of the proposed methodology are demonstrated in two medium and large test systems.

Cyber-Attack Recovery Strategy for Smart Grid Based on Deep Reinforcement Learning

The integration of cyber-physical system increases the vulnerabilities of critical power infrastructures. Once the malicious attackers take the substation control authorities, they can trip all the transmission lines to block the power transfer. As a consequence, asynchrony will emerge between the separated regions which had been interconnected by these transmission lines. In order to recover from the attack, a straightforward way is to reclose these transmission lines once we detect the attack. However, this may cause severe impacts on the power system, such as current inrush and power swing. Therefore, it is critical to properly choose the reclosing time to mitigate these impacts. In this paper, we propose a recovery strategy to reclose the tripped transmission lines at the optimal reclosing time. In particular, a deep reinforcement learning (RL) framework is adopted to endow the strategy with the adaptability of uncertain cyber-attack scenarios and the ability of real-time decision-making. In this framework, an environment is established to simulate the power system dynamics during the attack-recovery process and generate the training data. With these data, the deep RL based strategy can be trained to determine the optimal reclosing time. Numerical results show that the proposed strategy can minimize the cyber-attack impacts under different scenarios.

Design of a Weixin Service Platform for Bird Damage Early Warning in Power Grid

With the improvement of ecological environment and the expansion of the scale of power grid construction, “bird damage” has brought great hidden dangers to the safe and stable operation of power grid. On the one hand, human awareness of natural protection has been enhanced, the speed of bird reproduction has been accelerated, and the threat of birds to the line has gradually increased. On the other hand, bird damage prevention measures were not considered in the early design of power grid. Bird damage was prevalent in operation. After bird damage, the response measures were not timely, the treatment efficiency was low, and the number of line trips and non-outages increased. Especially in some backward areas, once the power grid loses contact with the provincial network, it will cause large-scale blackouts in the county (township) often occur, which directly affects the safe, stable and reliable operation of the power grid. It is urgent to prevent bird damage on the line.

Risk Analysis for Evolution of Transmission Lines Tripping Fault Induced by Wildfires located in Xiangxi, China

The serious consequences of transmission lines tripping fault induced by wildfires (TLTFIW) urges scholars to pay more attention to the safe operation of transmission lines. To illustrate the evolution process of TLTFIW and quantitatively evaluate the occurrence probability of subsequent events, an algorithm used for TLTFIW is proposed by using ETA, FTA and fuzzy number theory in this paper. The evolution process of TLTFIW is simulated according to ETA, which is divided into six stage including wildfires occurring, early wildfires early-monitoring, Wildfires extinguishing, Wildfires spreading, transmission lines tripping, and re-closing failure. In addition, the reason of the subsequent events in the evolution process are analysed by FTA, and the trapezoidal fuzzy theory is employed to calculate the probability of each events. Finally, based on the evaluation results, suggestions are provided for the evolution links with greater risks. Furthermore, transmission lines located in Xiangxi is introduced to present an application of the algorithm.

Fast Detection of Hidden Dangers in Transmission Line Corridors Based on Region Partitioning and Feature Extraction

Hidden dangers like large-scale construction machinery are the main causes of line trips. In this paper, we propose a fast detection algorithm for hidden dangers in transmission line corridors based on region partitioning and feature extraction. Since the scenes in the sky are simple and stable compared with the scenes on the ground, we detect hidden dangers in the sky and those on the ground separately. For hidden dangers in the sky, we firstly designed an algorithm to calculate the mask image for sky area. After dividing the sky area, we extracted features including colors and shapes of the difference areas in order to eliminate the interference factors. The targets left are the hidden dangers we truly cared about. For hidden dangers on the ground, firstly we design a pre-processing algorithm to eliminate the influence of uneven illumination on subsequent matching. Secondly, we propose a multi-scale gray-weighted average method to fuse multiple channels of multiple color spaces, by which we can effectively suppress noise caused by camera shake and maximize the area that cannot be matched. Thirdly, we use the Haar feature density map to filter the photo to remove discrete pixel points caused by small disturbances. Finally, we extract multiple features and fuse those features on decision level to obtain the final matching result. When deployed on intelligent monitoring devices and tested with massive scene photos, our algorithm has achieved the expected running efficiency and detection accuracy.

Investigation on characteristics of arc extinguishing time of a new lighting protection gap for transmission lines

The present research envisages the development of a novel arc extinguishing lightning protection gap in pursuit of reducing the lightning trip-out rate and accident rate. In the developed setup, the jetting stream arc extinction lightning protection gap device was used for transmission line. When this transmission line was struck by lightning and the lightning surge was going to break down the gap, the arc extinguishing lightning protection gap immediately jetted out sufficient electronegative gas flow that quickly cut off the arc and effectively prevented the insulator from being damaged by the arc. Furthermore, when the line was attacked by lightning, the generated overvoltage instantaneously broke the gap that was parallel to the insulator string, so that the lightning current was oriented to the earth from the gap. Simultaneously, it triggered the gas generator and generated a high speed stream, then extinguished the frequency continuous current arc rapidly, thus effectively reducing the rate of line trip to ensure the reliability of power supply. We used a high-speed camera and ordinary camera that automatically captured the process of the jetting stream arc in the extinction lightning protection gap device, while extinguishing the 1kA power frequency arc. The image of the high-speed camera indicated that the power frequency arc of 1kA was quenched in 10 ms before the relay protection action of the test loop, which made that the overhead line lightning flashover but the circuit breaker did not trip. Thus, a reduction in the rate of lightning trip was observed by the developed setup, and it has an immense potential for application at the transmission lines of China.

Data-driven failure diagnosis in transmission protection system with multiple events and data anomalies

To guarantee the reliable power supply, the expected operation of all the components in the power system is critical. Distance protection system is primarily responsible of isolating the faulty section from the healthy part of the grid. Failure in protection devices can result in multiple conflicting alarms at the power grid operation center and complex events analysis to manually find the root cause of the observed system state. If not handled in time, it may lead to the propagation of the faults/failures to the adjacent transmission lines and components. With availability of the synchronized measurements from phasor measurement units (PMUs), real-time system monitoring and automated failure diagnosis is feasible. With multiple adverse events and possible data anomalies, the complexity of the problem will be escalated. In this paper, a PMU based algorithm is presented and discussed to detect the root cause of the failure in transmission protection system based on the observed state, e.g. multiple line tripping, breaker failures. The failure diagnosis algorithm is further enhanced to come up with the fully functional version of the failure diagnosis tool, which is tailored for the cases in which the PMU anomalies are present. In the developed algorithm the validity of the PMU data is critical; however, such causes as communication errors or cyber-attacks might lead to the PMU data anomalies. This issue is well-addressed in this paper and some major types of anomaly detection methods suitable for PMU data are discussed. Results show that the ensemble approach has some distinct advantages in data anomaly detection compared to the previously used standalone algorithms. Additionally, the enhanced failure diagnosis method is developed to clean the inaccurate data in case of the anomaly in measured voltage magnitudes. Finally, both original and enhanced versions of the tool are tested on 96-bus test system using the real-time OPAL-RT simulator. The results show the accuracy of the enhanced tool and its advantages over the primary version of the tool.

Research on Overvoltage Monitoring Technology for Transmission Lines

Overvoltage is one of the important factors that cause line tripping and equipment damage. Accurate monitoring of transmission line overvoltage is of great significance for safe operation of power grid. In this paper, a transmission line overvoltage sensor based on the principle of coupled capacitance partial voltage is designed. The high voltage arm capacitance of the sensor is the stray capacitance between the sensor metal sheet and the earth, and the low pressure arm capacitance is the coupling capacitance between the sensor metal sheet and the wire. At first, the structure characteristics and sensor principle of the sensor are described, and the parameters of the sensor are calculated. The results show that the sensor has high detection accuracy and can realize overvoltage monitoring of transmission lines.

Study on Grid-Connected Strategy of Distribution Network with High Hydropower Penetration Rate in Isolated Operation

As the largest global renewable source, hydropower is a useful supplement to mountainous distribution networks with abundant water resources, and shoulders a large portion of the regulation duty in many power systems. In particular, in the form of decentralized energy sources located to their customers, small hydropower (SHP) improve grid stability by diversifying the electricity system and reducing power loss. The mountainous distribution networks supplied by small hydropower are closed-loop design but open-loop operation, which easily causes the tripping of tie line even further the off-grid operation of small hydropower system. Once the tie line trips, the current countermeasures—such as hydropower shutdown and load shedding—do not fully guarantee the reliability of power supply and the utilization efficiency of hydropower. This paper studies the amplitude-frequency characteristics of SHP off-grid, according to the typical integration of hydropower in South China, a SHP on-grid/off-grid model is established based on the Power Systems Computer Aided Design (PSCAD) platform. It is found that due to the inertia of SHP, the amplitude-frequency characteristics of SHP island system are relatively slow, and the process of non-synchronization with the main grid is gradually expanded. The characteristic of SHP has a certain degree of synchronization with the main grid in the initial island operates stage, which helps to find a novel grid connection method. This paper further proposes the strategy of using fast busbar automatic transfer switch (BATS), which quickly connect the trip-off SHP to the distribution network under the condition of permitting distributed energy grid-connected. The PSCAD simulation results show that proposed strategy has a limited impact on the power grid and prove the effectiveness of the method.

Analysis of discharge energy on surge arrester configurations in 132 kV double circuit transmission lines

Surge arrester has been proven to be the most effective application to provide optimum lightning protection for the transmission line. Thus, many works on optimizing lightning protection for transmission line have been conducted since the past. However, works on minimizing double circuit outages and surge arrester physical properties during transient overvoltages are less likely to be found. Therefore, in this work, several surge arrester configurations installed on a 132 kV double circuit transmission line were modelled using EMTP-RV to investigate their capability to withstand current and energy discharged by lightning strokes during back flashover phenomena. These configurations were then compared to determine the most effective protection design based on the actual tripping pattern recorded by the lightning detection system (LDS) in Malaysia. The selection was made by considering arresters’ discharge energy due to variation in tower footing resistance, current magnitude, power frequency voltage, lightning tail time and front time, number of towers and span length. It was found that double circuit transmission line tripping can be completely eliminated by installing surge arresters at each phase conductor of one circuit. The selected arresters configuration provides sufficient lightning protection to the transmission line and complies with the discharge energy capability requirement specified by the utility company in Malaysia, of 5.1 kJ/kV for maximum continuous operating voltage (MCOV).

Study on DC flashover characteristics of plastic sheds in small scale

The statistics of tripping data of transmission lines show that external damage has become the main cause of transmission lines tripping. The foreign object cutting-out, which accounted for 61.8% of the total, was the most common external damage in transmission line. This paper focuses on the DC flashover characteristics of small-scale plastic sheds of greenhouses with distances of 1m and 2m. The results of the study showed that the surface of plastic sheds was less dirty and the average surface conductivity was lower. In the dry condition, it can be regarded as an insulator, and in the case of moisture, however, its insulation resistance is reduced to a megohm level. Under the electric field of 70 kV/m, no flashover occurred in both the wrinkled and the tiled plastic sheds. The flashover voltage per unit length of the wrinkled is about 15%-21% lower than that of the tiled, and wrinkled plastic sheds flash over more easily. As the pole pitch increases, the flashover voltage per unit length decreases, and the flashover voltage per unit length of both the wrinkled and the tiled is reduced by about 30%.

Control strategy of UPFC based on power transfer distribution factor

In practical engineering application, trial method is widely used to determine the control value of unified power flow controller (UPFC in short). Since the calculation is based on offline typical data, the trial method is inefficient and less accurate, which could not adjust to the changing operating conditions. In order to make up for the deficiency, this paper proposes a novel UPFC control strategy based on power transfer distribution factors. First, the anticipated line tripping fault throughout the grid is scanned and the N − 1 overload lines are marked. Then, in regard to each overload condition, a certain UPFC control value is calculated based on power transfer distribution factors. The anticipated control list could be formed and updated according to online EMS data. When a line tripping fault is detected, simply by searching the control list, a condition could be matched and the UPFC could immediately be activated to eliminate the line overload. This method mentioned above could provide decision-making support to power-grid dispatching institutions. The results of a simulation example shows that the method is efficient and utilisable.

A Post-Contingency Power Flow Control Strategy for AC/DC Hybrid Power Grid Considering the Dynamic Electrothermal Effects of Transmission Lines

The blocking of large-capacity HVDC or the tripping of AC transmission lines by accident will cause power flow transfer sharply and increase the risk of cascading faults in AC/DC hybrid power grid. Therefore, it is needed to take reasonable safety control measures in time to interdict the spreading of the accident. In this paper, a post-contingency power flow control (PPFC) strategy for AC/DC hybrid power grid was proposed. This strategy brings the dynamic electrothermal effects of the conductor into the safety constraints to fully excavate the short-time overload endurance capability of transmission lines, and coordinates the active power adjustment of generators, power transmission adjustment of HVDC, and load shedding measures, to realize the dynamic optimal power flow control in multiple time sections. The proposed optimization control model takes minimum total cost as the objective function, and accounts for the influence of different weather conditions along the transmission lines and load fluctuations after the accident on the electrothermal safety of transmission lines, which can quickly provide the economical and reasonable power flow control scheme, to prevent the AC/DC hybrid power grid from unexpected cascading tripping effectively. Finally, the effectiveness and superiority of the proposed strategy were verified through case studies on the modified IEEE 10-machine 39-node power systems.

Fault Overload Control Method for High-Proportion Wind Power Transmission Systems Based on Emergency Acceleration of Doubly-Fed Induction Generator

With a high proportion of wind power being transmitted through ac and dc lines, a new power grid pattern has gradually emerged. A dc inverter is prone to commutation failure, which may lead to cascading trip of ac lines for overload, resulting in serious consequences. However, existing control methods have problems of over- or under-shedding and are unsuitable for high-proportion wind power transmission systems. Accordingly, a new fault overload control method based on emergency acceleration of doubly fed induction generator (DFIG) is proposed. The fast power control capability of DFIG is fully utilized; the active power of power grid could be rapidly balanced. First, the fault characteristics of a wind power ac/dc transmission system under the fault of dc receiving-end grid are analyzed, and the power flow transfer after self-recovery from the dc commutation failure is derived. Second, by analyzing the power characteristics of DFIG, a fault overload control idea of the wind power transmission system is proposed based on emergency acceleration of DFIG. At last, the maximum controllable capacity of a wind farm is analyzed, and a fault overload control strategy of the wind power transmission system is proposed. The simulation results prove that the proposed method can rapidly reduce the output of wind farms and prevent the overload of ac lines.

Development of a Cyber-Resilient Line Current Differential Relay

The application of line current differential relays (LCDRs) to protect transmission lines has recently proliferated. However, the reliance of LCDRs on digital communication channels has raised growing cyber-security concerns. This paper investigates the impacts of false data injection attacks (FDIAs) on the performance of LCDRs. It also develops coordinated attacks that involve multiple components, including LCDRs, and can cause false line tripping. Additionally, this paper proposes a technique for detecting FDIAs against LCDRs and differentiating them from actual faults in two-terminal lines. In this method, when an LCDR detects a fault, instead of immediately tripping the line, it calculates and measures the superimposed voltage at its local terminal, using the proposed positive-sequence (PS) and negative-sequence (NS) submodules. To calculate this voltage, the LCDR models the protected line in detail and replaces the rest of the system with a Thevenin equivalent that produces accurate responses at the line terminals. Afterwards, remote current measurement is utilized by the PS and NS submodules to compute each sequence's superimposed voltage. A difference between the calculated and the measured superimposed voltages in any sequence reveals that the remote current measurements are not authentic. Thus, the LCDR's trip command is blocked. The effectiveness of the proposed method is corroborated using simulation results for the IEEE 39-bus test system. The performance of the proposed method is also tested using an OPAL real-time simulator.

Packet-data anomaly detection in PMU-based state estimator using convolutional neural network

With more phasor measurement units (PMU) being deployed by utilities for reliable monitoring of power systems, there grows an increasing risk of vulnerability to various cyber-attacks. This paper is concerned with a class of false data injection attacks (FDIA) which aim to modify PMU measurements resulting in incorrect state estimation solutions. We extract multi-variate time-series signals from PMU data packets aggregated in phasor data concentrators (PDC) corresponding to different events such as line faults and trips, generation and load fluctuations, shunt disconnections and FDIA prior to every cycle of state estimation (SE). A Convolutional Neural Network (CNN) data filter with Nesterov Adam gradient descent and categorical cross entropy loss is proposed to validate the PMU data. This filter extracts inter time-series relationships to classify different power system events by comparing the temporal structure of PMU packet data. The performance of the filter is then compared with (a) deep learning algorithms such as Recurrent Neural Networks (RNN) and Long Short Term Memory (LSTM) and (b) traditional classifiers such as SVM and ensemble methods. It is seen that the proposed CNN-based filter results in higher classification accuracies among all classifiers. This makes the CNN classifier suitable to serve as an independent data filter to identify falsified data streams targeted to alter SE. In order to verify the accuracy of the proposed filter, a hybrid state estimator (HSE) has been used in this study which obtains measurements from both PMU and traditional meters. All simulations are carried out on IEEE-30 bus and IEEE-118 bus systems.

Study on risk assessment of trans-regional transmission lines tripping disaster induced by wildfire

In recent years, there are more and more incidents of trans-regional transmission line tripping caused by wildfire. How to reduce the occurrence of such incidents has become a hot topic in domestic academic research. Hence, the associated risk factors of trans-regional transmission lines tripping disaster induced by wildfire is quantified based on system engineering theory of “human - machine - environment”. A risk assessment index system is established by the application of analytic hierarchy process (AHP), and a certain transmission line in Hunan Province is taken as an example to conduct risk assessment analysis in this paper. The results indicate that the regional geographic location factors, the frequent meteorological disaster factors and the sacrifice festival burning situation exist relatively serious security risks. Increasing the coniferous trees planting area and enhancing the summer and the force of fall fire supervision are expected to be carried out for reducing security risks.

Mathematical Analysis and an Exact Solution Combined with Preprocessing Method for Resynchronizing of Bus Timetable Problem

Bus timetabling is a subproblem of bus network planning, and it determines departure time of each trip of lines to make vehicles from different lines synchronously arrive at transfer stations. Due to the well-designed coordination of bus timetables, passengers can make a smooth transfer without waiting a long time for connecting buses. This paper addresses the planning level of resynchronizing of bus timetable problem allowing modifications to initial timetable. Timetable modifications consist of shifts in the departure times and headways. A single-objective mixed-integer programming model is proposed for this problem to maximize the number of total transferring passengers benefiting from smooth transfers. We analyze the mathematical properties of this model, and then a preprocessing method is designed to reduce the solution space of the proposed model. The numerical results show that the reduced model is effectively solved by branch and bound algorithm, and the preprocessing method has the potential to be applied for large-scale bus networks.

Complex Power System Status Monitoring and Evaluation Using Big Data Platform and Machine Learning Algorithms: A Review and a Case Study

Efficient and valuable strategies provided by large amount of available data are urgently needed for a sustainable electricity system that includes smart grid technologies and very complex power system situations. Big Data technologies including Big Data management and utilization based on increasingly collected data from every component of the power grid are crucial for the successful deployment and monitoring of the system. This paper reviews the key technologies of Big Data management and intelligent machine learning methods for complex power systems. Based on a comprehensive study of power system and Big Data, several challenges are summarized to unlock the potential of Big Data technology in the application of smart grid. This paper proposed a modified and optimized structure of the Big Data processing platform according to the power data sources and different structures. Numerous open-sourced Big Data analytical tools and software are integrated as modules of the analytic engine, and self-developed advanced algorithms are also designed. The proposed framework comprises a data interface, a Big Data management, analytic engine as well as the applications, and display module. To fully investigate the proposed structure, three major applications are introduced: development of power grid topology and parallel computing using CIM files, high-efficiency load-shedding calculation, and power system transmission line tripping analysis using 3D visualization. The real-system cases demonstrate the effectiveness and great potential of the Big Data platform; therefore, data resources can achieve their full potential value for strategies and decision-making for smart grid. The proposed platform can provide a technical solution to the multidisciplinary cooperation of Big Data technology and smart grid monitoring.

Real-Time Analysis of Power System Protection Schemes Using Synchronized Data

An error in a power system protection scheme can result in unwanted tripping of healthy lines or delay in the removal of a fault from the network, thus affecting the power system stability. Online identification of such an error provides scope to initiate remedial measures, thereby preventing possible cascade tripping situations. In this paper, a method for real-time analysis of protection decision in a power system is proposed. This method identifies the relay, which has maloperated for an event in the network. For analysis of a relay operation, synchrophasor data from selected locations are obtained depending on the network topology. A function is developed utilizing indices calculated from the synchronized data. Based on the calculated value of the function during an event, the correctness of the protection decision is validated. Results obtained from PSCAD/EMTDC simulations for the New England 39-bus system demonstrate the performance of the proposed method.