Reliability Of Power Transmission System Research Articles

A novel application of artificial intelligence technology for outdoor high-voltage composite insulator

The distribution of the electric field plays a crucial role in evaluating the effectiveness of composite insulators. This research presents an innovative approach for optimizing the design of corona rings, aiming to decrease the electric field intensity in critical areas to satisfactory levels. The investigation examined the correlation among corona ring design variables and the intensity of the electric field close to the energized-end fitting in a 220 kV composite insulator equipped with a corona ring. Using design of experiment methods, the impact of three corona ring design parameters – corona ring diameter (R), ring tube diameter (Dr), and corona ring height (H) – was assessed. A novel nonlinear mathematical objective function was formulated, connecting the electric field magnitude to the structural parameters of the corona ring. Subsequently, the Bat algorithm, a bio-inspired optimization technique, was employed to enhance the initial corona ring design and mitigate the electric field intensity. Finally, the Finite Element Method (FEM) was utilized to simulate and evaluate the voltage distribution and electric field stress. The optimization process resulted in a substantial decrease in the highest electric field magnitude, by 58.6 % compared to the insulator with the threshold value, and 75 % when devoid of a corona ring. Additionally, the research highlighted the significant influence of ring tube thickness on the distribution of the electric field. The combination of experimental design and the Bat algorithm proved to be a powerful tool for optimizing the design of corona rings on transmission line composite insulators, providing precise solutions for optimizing corona discharge problems and enhancing the reliability of power transmission systems.

SmartConnector: A Self-Powered IoT Solution to Ease Predictive Maintenance in Substations

The increased dependency on electricity of modern society makes reliability of power transmission systems a key point. This goal can be achieved by continuously monitoring power grid parameters, so possible failure modes can be predicted beforehand. The deployment of Internet of Things (IoT) solutions and new low-cost sensors eases this task. This paper presents a self-powered IoT solution for real-time monitoring of different parameters of a high-voltage substation connector. This new family of power connectors is called SmartConnector, which incorporates a thermal energy harvesting system powering a microcontroller that controls a transmitter, and several electronic sensors to measure the temperature, current and voltage drop across the connector to estimate the electrical contact resistance (ECR) of the connector. These measurements are sent remotely via a Bluetooth 5 wireless communication module to a local gateway, which transfers the measured data to a database server for storage and further analysis and visualization. Different experiments are presented to validate the feasibility of the SmartConnector in terms of measurement accuracy in comparison with a wired system. The proposed thermal energy harvesting is tested to calculate the optimum data transfer rate needed for extending the lifetime of the SmartConnector . A shielding solution for the electronics operating under this high voltage environment is also proposed.

Latitudinal dependence of geomagnetically induced currents during geomagnetic storms

Major geomagnetic storms drive rapid intensification and variability of magnetospheric and iono- spheric current systems that give rise to large ground-induced currents (GIC). Space weather as- sociated GIC pose a serious threat to the reliability of power-transmission systems and other elec- trically conducting infrastructure such as oil and gas pipelines. The most severe effects are ob- served at high latitudes due to ionospheric currents associated with the aurora. However, as power transmission grid and pipeline infrastructure continues to grow at middle and low-latitudes, GIC hazards are no longer just concerns of high-latitude regions. We investigate how GIC amplitude varies in latitude during six major geomagnetic storms that occurred between 1989 and 2004. Due to limited direct GIC measurements, a proxy of the geoelectric field is used, i.e. the GIC index. This is calculated for the selected geomagnetic storms using 25 magnetic observatories relatively uniformly distributed in geomagnetic latitude, 14 magnetic observatories with longitudes varying within a range of 45 degrees as well as for the 7 November 2004 storm using 104 observatories. In addition, we suggest a possible way to follow the latitudinal displacement of the auroral oval dur- ing geomagnetic storms through the maximum value of GIC index, estimated over 2-hour inter- vals on a wide number of magnetic observatories.

Probabilistic evaluation and planning of power transmission system reliability

Modern power systems are designed prudently and then operated according to the permitted equipment limits set out in standards, policies, and procedures. To meet the growing demand, utilities apply transmission expansion tools for planning and updating their transmission assets. However, due to their unpredictable nature, transmission contingencies cannot be easily integrated during the planning stage. Although computationally cumbersome, probabilistic planning is an approach that could enable an objective comparison of the economic risk associated with a contingency event versus the cost of upgrades. In the context of the development of a generic assessment tool for such a process that could be employed by utilities, this study presents a systematic approach for transmission system expansion planning that includes consideration of an N − 1 contingency. The proposed method provides an estimate of the potential economic losses that could occur due to contingencies related to transmission, which are quantified as the cost of expected energy not supplied. The study then introduces a proposed formulation that computes an optimal plan for transmission system reinforcement that will eliminate the economic losses associated with N − 1 contingencies. The results reveal that in specific cases, upgrading the system has economic merit as well as offering the benefits to be derived from a robust transmission system.

A Reliability Prediction Method for HVDC Power Transmission Systems

本文提出了超高压直流输电系统可靠性预测的数学模型及工程方法。采用能量可用率评价超高压直流输电系统的可靠性，使用从统计期间扣除计划停运小时的能量可用率与检修系数评价超高压直流输电系统的固有可靠性，采用幂函数表示检修系数的数学模型。在统计超高压直流输电系统可靠性历史数据的基础上，确定检修系数的统计值与幂函数的待定参数。根据超高压直流输电系统的计划检修天数、降额系数与检修系数的数学模型，提前两年预测超高压直流输电系统的能量可用率。给出了超高压直流输电系统可靠性预测结果的验证方法以及天广、高肈与江城等三个超高压直流输电工程的可靠性预测实例。应用超高压直流输电系统的可靠性预测方法，可以提前两年确定超高压直流输电系统能量可用率的预测值，为超高压直流输电系统的可靠性目标管理提供了依据。 A mathematical model and engineering methods for the reliability prediction of HVDC power transmission systems are presented. The energy availability is used to evaluate HVDC power transmission system reliability, making use of the energy availability deducted scheduled outage hours from period hours and the maintenance factor to evaluate HVDC power transmission sys-tem inherent reliability, and a mathematical model for the maintenance factor is shown by the power function. Based on statistical historical reliability data of HVDC power transmission sys-tems, statistical values of the maintenance factor and undetermined parameters of the power function are determined. According to scheduled outage days, the outage derating factor and a mathematical model of the maintenance factor of HVDC power transmission systems, the energy availability of HVDC power transmission systems can be predicted in the next two years. The re-liability verification method for prediction results of HVDC power transmission systems is given, together with reliability prediction examples of three HVDC power transmission projects, such as Tianshengqiao to Guangzhou, Gaopo to Zhaoqing and Jiangling to Echeng HVDC power transmission projects. By using reliability the prediction method for HVDC power transmission systems, predictive values of the energy availability of HVDC power transmission systems can be determined in the next two years, which provide the basis for the reliability target management of HVDC power transmission systems.

Determination of the corona inception voltage in an extra high voltage substation connector

Substation connectors play a key role in the reliability of power transmission systems. Despite this fact, their behavior has been rarely studied, especially in regard to electric stress. In this study the corona inception voltage of a complex-shaped 765 kV substation connector is calculated by using a three-dimensional finite-element approach combined with the semi-empirical Pedersen approach. The method proposed was previously validated by using available experimental data obtained from sphere-to-plane, concentric cylinders and point-to-plane non-uniform air gaps. To further validate the accuracy of this method, the corona inception voltage of the analyzed substation connector was obtained by making comparisons with experimental tests conducted in a high voltage laboratory. Results show the need to calculate the corona inception voltage for complex geometries and large air gaps. Using this proposed approach allows us to identify peak or stress points of the connector surface. Hence, this system strongly appears to be a valuable tool to assist the design process of substation connectors and other high voltage devices for minimizing corona activity.

A study of correlated failures on the network reliability of power transmission systems

This paper studies the performance evaluation of a power transmission system in terms of its network topology, where edges represent transmission lines and nodes represent subsidiary stations. The power transmission network is modeled as a stochastic-flow network (SFN) due to the possibility of failure, partial failure, and maintenance of edges (transmission lines). Furthermore, correlation poses a particular concern for such an SFN because the simultaneous failure of multiple components can dangerously degrade performance. We develop a method to measure the impact of correlated failures on network reliability, which is defined as the probability of demand satisfaction. Experimental results show that correlation may produce a significantly negative impact on network reliability, especially when there is a high level of network demand. Thus, the proposed approach captures the influence of correlation on network reliability and offers a method to quantify the utility of reducing correlation.

Vulnerabilities and Countermeasures – A Survey on the Cyber Security Issues in the Transmission Subsystem of a Smart Grid

With the increased investment and deployment of embedded computing and communication technologies in the power system – the smart grid vision is shaping up into a reality. The future power grid is a large cyber physical system (CPS) which is vulnerable to cyber security threats. Among the three major subsystems of a power grid – generation, transmission and distribution – this survey focuses on the transmission subsystem because most of the cyberization of the grid has been happening in this subsystem. This is due to the need for distributed measurement, monitoring and control to retain the stability, security, and reliability of power transmission system. Given the geographically dispersed generation facilities, substations, control centers, data concentrators etc., efficient data communication is required, and therefore large scale networking – either proprietary or leased – is happening. The goal of this paper is not to be comprehensive to include all efforts of securing the transmission system from cyber borne threats, but to provide a survey of various vulnerabilities, and countermeasures proposed by various research efforts. One of the focus area in this survey is the Phasor Measurement Units (PMUs) and Wide Area Measurement System (WAMS) technology – mostly due to our familiarity with the issues for this specific technology deployment – rather than any attempt to indicate that this is the most vulnerable technology in the transmission subsystem. Our hope is that this survey will familiarize any uninitiated reader with the issues and provide incentive to undertake systematic research programs to thwart cyber attacks on our national power delivery infrastructure.

Models for probabilistic power transmission system reliability calculation

In Denmark, many independent power producers such as windmills and small gas- or oil fuelled combined heat and power plants (below 50 MW) have been set up in the last few years. Further, the larger power plants in Denmark are combined power plants with heat production to district heating. Understanding of this complex utility system with regard to cost and reliability are to be examined by a probabilistic network planning program, which can take into account all these specialities for the Danish network and include probabilistic models for the load and for the transmission system as well. Such a program has been set up with stochastic models of the windmills, the loads, the small combined heat and power plants and the heat production from the larger power plants. The models are used on a realistic network grid, and Monte-Carlo simulations are used in the final simulation program.

A Fast Automatic Contingency Selection Algorithm with Bus Voltage Criteria

Automatic contingency selection, which is used in power transmission system reliability evaluation is discussed. The paper presents a new method in which the post-contingency volt age is analytically evaluated in terms of the pre-contingency voltage and the parameters of an outage line or transformer. The new method is compared with the linear method, the local method and the curtailment method. The results of computation done on three test systems demonstrated that the new method gives almost the same precision as the results of the other three methods, but with significant superiority in computing time.