Search

Routine visual inspection is fundamental to the preventive maintenance of power equipment. Convolutional neural networks (CNNs) substantially reduce the number of parameters and efficiently extract image features for classification tasks. In the actual production and operation process of substations, due to the limitation of safety distance, camera monitoring, inspection robots, etc., cannot be very close to the target. The operational environment of power equipment leads to scale variations in the main target and thus compromises the performance of conventional models. To address the challenges posed by scale fluctuations in power equipment image datasets, while adhering to the requirements for model efficiency and enhanced inter-channel communication, this paper proposed the ResNet Cross-Layer Parameter Sharing (ResNetCPS) framework. The core idea is that the network output should remain consistent for the same object at different scales. The proposed framework facilitates weight sharing across different layers within the convolutional network, establishing connections between pertinent channels across layers and leveraging the scale invariance inherent in image datasets. Additionally, for substation image processing mainly based on edge devices, smaller models must be used to reduce the expenditure of computing power. The Cross-Layer Parameter Sharing framework not only reduces the overall number of model parameters but also decreases training time. To further enhance the representation of critical features while suppressing less important or redundant ones, an Inserting and Adjacency Attention (IAA) module is designed. This mechanism improves the model’s overall performance by dynamically adjusting the importance of different channels. Experimental results demonstrate that the proposed method significantly enhances network efficiency, reduces the total parameter storage space, and improves training efficiency without sacrificing accuracy. Specifically, models incorporating the Cross-Layer Parameter Sharing module achieved a reduction in the number of parameters and model size by 10% to 30% compared to the baseline models.

The Smart Grid is a cyber-integrated power grid that manages electricity generation, transmission, and distribution to consumers and central to its functioning is the substation. However, integrating cyber-infrastructure into the substation has increased its attack surface. Notably, sophisticated attacks such as the PipeDream APT exploit multiple device protocols, such as Modbus, DNP3, and IEC61850. The substation’s constraints pose challenges for implementing security measures such as encryption and intrusion detection systems. To address this, we propose a comprehensive trust-based framework aimed at enhancing substation security. The framework comprises a trust model, a risk posture model, and a trust transferability model. The trust model detects protocol-based attacks on Intelligent Electronic Devices and SCADA HMI systems, while the risk posture model dynamically assesses the substation’s risk posture. The trust transferability model evaluates the feasibility of transferring and integrating a device and its trust capabilities into a different substation. The practical substation emulation involves a Docker-based testbed, employing a multi-agent architecture with a real-time Security Operations Center-influenced dashboard. Assessment involves testing against attacks guided by the MITRE ICS ATT&CK framework. Our framework displays resilience against diverse attacks, identifies malicious behavior, and rewards trustworthy devices.

The basic requirements for the design of a switchgear for main 35–220 kV step-down substations are reliability and efficiency. Switchgear circuits are chosen depending on the number of supply and transit lines and transformers, the substation’s place in the power supply system, and the area that can be allocated under the substation construction. The substation switchgear’s reliability depends on the circuit type and the equipment to be installed. When designing, as a rule, standard substation switchgear circuit solutions are chosen with often unreasonably overstated reliability indicators and, as a consequence, capital costs. This paper explores the issues of automated choice of the best option for the 35–220 kV substation switchgear circuit, considering its structural reliability and additional costs for the area allocated under the electrical unit. A distinctive feature of the work is a comprehensive accounting of the reliability indicators of the substation and the influence of the layout of switchgear circuits as a whole on the performance indicators of future electrical installations. The developed technique is used at the pre-design stages and allows for reducing further capital, maintenance, and repair costs for electrical units by up to 14.5%. The developed approach is implemented in the original TER CAD software product.

Carbon emission calculation during power transmission and substation construction provides valuable insights into the trend of carbon emissions and the development of low-carbon power grids. In this regard, this study divides the power transmission and substation construction process into production, transportation, and construction stages based on the sources of carbon emissions and employs a life cycle assessment to calculate the total carbon emissions using the carbon emission factor method for typical 500 kV projects. The results show that in the construction process the production stage contributes the most carbon emissions, with material and equipment production for power transmission accounting for 78% and 14% of the total emissions, respectively. The transportation and construction stage contribute 1% and 7% of the total emissions, respectively. For substations, material and equipment production contribute 67% and 30% of the total emissions, respectively. The transportation and construction phases contribute 1% and 2% of the total emissions. Through the qualitative and quantitative analysis of the carbon emission results, the construction scale and the topography and geology have significant impacts on carbon emissions from power transmission and substation projects. Finally, some targeted recommendations for carbon emission reduction for power transmissions and substations are proposed based on the influencing factors of each stage of the construction.

The use of information technology and the automation of control systems in the energy sector enables a more efficient transmission and distribution of electricity. However, in addition to the many benefits that the deployment of intelligent and largely autonomous systems brings, it also carries risks associated with information and cyber security breaches. Technology systems form a specific and critical communication infrastructure, in which powerful control elements integrating IoT principles and IED devices are present. It also contains intelligent access control systems such as RTU, IDE, HMI, and SCADA systems that provide communication with the data and control center on the outer perimeter. Therefore, the key question is how to comprehensively protect these specialized systems and how to approach security implementation projects in this area. To establish rules, procedures, and techniques to ensure the cyber security of smart grid control systems in the energy sector, it is necessary to understand the security threats and bring appropriate measures to ensure the security of energy distribution. Given the use of a wide range of information and industrial technologies, it is difficult to protect energy distribution systems using standard constraints to protect common IT technologies and business processes. Therefore, as part of a comprehensive approach to cyber security, specifics such as legislative framework, technological constraints, international standards, specialized protocols or company processes, and many others need to be considered. Therefore, the key question is how to comprehensively protect these specialized systems and how to approach security implementation projects in this area. In this article, a basic security concept for control systems of power stations, which are part of the power transmission and distribution system, is presented based on the Smart Grid domain model with emphasis on substation intelligence, according to the Purdue model. The main contribution of the paper is the comprehensive design of mitigation measures divided into mandatory and recommended implementation based on the standards defined within the MITRE ATT&CK matrix specified, concerning the specifications of intelligent distribution substations. The proposed and industry-tested solution is mapped to meet the international security standards ISO 27001 and national legislation reflecting the requirements of NIS2. This ensures that the security requirements will be met when implementing the proposed Security Baseline.

Electric substations (ESS) are important facilities that must operate even under contingency to guarantee the electrical system’s performance. To achieve this goal, the Brazilian national electricity system operator establishes that alternating current (AC) auxiliary systems of ESS must have, at least, two power supplies, and in the case of failure of these sources, an emergency generator (EG) must at least supply energy to the essential loads. In order to improve the availability of auxiliary systems, a microgrid with other sources, such as photovoltaic (PV) systems and Battery Energy Storage Systems (BESS), can be an alternative. In this case, an economical optimization of the PV/BESS system must be addressed considering the costs associated with the installation and maintenance of equipment, and the gains from the credits generated by the photovoltaic system in the net metering scheme. In this paper, the size of the BESS system was determined to supply energy to the load of auxiliary systems of an ESS, as well as a PV system to achieve a null total cost. Furthermore, multi-objective optimization using the genetic algorithm technique was employed to optimize the size of the hybrid PV/BESS to minimize the investment cost and time when the demand was not met. Simulations under different scenarios of contingency were allowed to obtain the Pareto frontier for the optimal sizing of a PV/BESS system to supply energy to AC auxiliary systems in an ESS under contingency.

This paper presents case studies for replacing diesel generators (DGs) that are used as the main and emergency power sources for alternating current (AC) auxiliary services in substations (SS) within the transmission network (voltage greater than or equal to 230 kV). The objective of this research is to present a solution that is more reliable, environmentally friendly, and financially viable than DGs. To achieve this, the proposed solutions incorporate Battery Energy Storage Systems (BESSs) with or without the integration of Photovoltaic (PV) Systems. These solutions were simulated using the HOMER PRO Version 3.14.5 software for the Messias SS /AL, and the results were analyzed and compared to the DG in terms of reliability, financial viability, and environmental impact. Based on the conducted analyses, the BESS solution with the PV system was found to be the most suitable for the main source. However, in the case of the emergency source, if one of the main sources is a DG/BESS, maintaining the emergency DG is the preferable option. If both main sources are independent, the BESS solution with the PV system is a suitable solution.

At present, substation operation ticket system is developed based on an expert system, which has some problems such as knowledge base redundancy, intelligence deficiency and automatic learning ability. To solve this problem, this paper proposes an operation sequence reasoning model based on the knowledge base of the Neo4j knowledge graph and DuelingDQN (Dueling Deep Q Network) algorithm. Firstly, the diagram structure model of substation main wiring was established using the Neo4j knowledge graph. Based on the diagram structure model, the operable equipment set of the operation task was searched to form the task space, action space and action selection model of DuelingDQN. The reward and punishment function was designed based on the “five defense” rules and the state change of equipment. Make DuelingDQN model and Neo4j model interact in real time, and automatically learn the operation sequence. The test results show that the method proposed in this paper can automatically deduce the correct operation steps under different wiring modes and realize the transfer within the station, which is of great significance to the intellectualization of the operation ticket system.

Maximizing the carbon reduction in substations with minimum cost investments can be achieved by taking advantage of the potential of substations in terms of the envelope and renewable energy, which is significant in promoting carbon reduction in substations. Therefore, firstly, the relationship between building cost–energy consumption–carbon emissions is explored, and then the global optimal calculation model of substation envelope–renewable energy is established, with the lowest life-cycle carbon emission of the substation as the optimization goal. Finally, the validity of the model is verified based on a case study of a typical 110 kV outdoor substation. The model calculation results show that, without considering the cost constraint, Harbin has the highest maximum carbon reduction of 180,350 kg, which is 25.15% and 13.74% higher than the maximum carbon reduction in Shanghai and Haikou, respectively. Furthermore, based on the comparison of the cost and benefits of each carbon reduction technology, a prioritization of various carbon reduction technologies is given for each climate zone. The model established in this paper can provide the optimal configuration of substation carbon reduction technologies with different incremental cost constraints, and provide a reference for the low-carbon design of substations.

The residual magnetic field in a magnetic shielding device with a multilayer high permeability material (permalloy) structure can be obtained at the nanotesla (nT) level or even lower. At present, in the process of designing a magnetic shielding device, most of the external environmental magnetic field settings are set at the size of the Earth’s environmental magnetic field, but the instruments inside the magnetic shielding device need to be powered, the active compensation coil needs to be powered, and the degaussing coil of passive shielding layer needs to be powered, so substations need to be used around magnetic shielding devices. The magnetic field generated by the substation will affect the magnetic shielding device, so this paper analyzes and measures the magnetic field generated by the substation. Firstly, the finite element model of a substation is established, and the influence of different substations on the environmental magnetic field is analyzed by changing the power. Secondly, the test method of a substation environment magnetic field is determined. Finally, the site test was carried out to measure the influence of different power substations and different distances on the magnetic field, and its influence on the magnetic shielding device was analyzed, which provided an important basis for the construction of the magnetic shielding device.

Substation (SS) auxiliary systems (SAux) are facilities responsible for hosting the alternating (AC) and direct current (DC) busbar to serve the equipment and systems that perform the substation’s protection, control, and supervision. External and internal power supplies typically ensure the continuity of such a facility. The electricity support will be restricted to diesel emergency generators (DG) if the external power supply is unavailable due to a contingency. The DG present a slower response time and are susceptible to starting failures. Microgrids with Battery Energy Storage Systems (BESS) paired with photovoltaic systems (PV) are presented as an innovative and reliable solution for powering the SAux. In this article, tests were carried out on the microgrid of the Edson Mororó Moura Institute of Technology (ITEMM) in Brazil to support the use of microgrids BESS/PV in the SAux of a transmission SS of the São Francisco Hydroelectric Company (Chesf). Without an external power supply, BESS commands the action of islanded operation, maintaining both voltage and frequency requirements of the microgrid without load shedding. It was possible to observe all operations of the microgrid. The experimental results showed that the solution proposed in the paper implements a dependable self-dispatchable autonomous power supply.

Liberalization of the electricity market has forced the use of economic and efficient maintenance techniques. Thus, it is necessary to extend the useful life of the facilities in a perfect state of service, and with quality supply for customers. Furthermore, thermography is a maintenance technique that can be implemented quickly, has low cost, and is very effective in terms of the results provided. For this reason, it is very widespread within the electricity sector. As substations are critical facilities within the electrical supply, thermographic inspections are carried out on them very frequently. However, to ensure that the results obtained are reliable, a series of requirements must be met. A compilation of the complete process of the performance of a correct thermography in substations is shown. The factors that affect performing a correct thermographic inspection are indicated. These can be procedural, technical, and environmental. In addition, conditions for conducting thermographic inspections and the action to performed on a hot spot are indicated. The hot spot is usually identified with a current and wind speed other than nominal; these two variables can mask the true severity of the hot spot. For this reason, the extrapolation of the detected temperature to the nominal current conditions and in the absence of wind is carried out using a proposed formula. Finally, two examples of application of the proposed formula and the recommended action on them are exposed.

A compromised Smart Grid, or its components, can have cascading effects that can affect lives. This has led to numerous cybersecurity-centric studies focusing on the Smart Grid in research areas such as encryption, intrusion detection and prevention, privacy and trust. Even though trust is an essential component of cybersecurity research; it has not received considerable attention compared to the other areas within the context of Smart Grid. As of the time of this study, we observed that there has neither been a study assessing trust within the Smart Grid nor were there trust models that could detect malicious attacks within the substation. With these two gaps as our objectives, we began by presenting a mathematical formalization of trust within the context of Smart Grid devices. We then categorized the existing trust-based literature within the Smart Grid under the NIST conceptual domains and priority areas, multi-agent systems and the derived trust formalization. We then proposed a novel substation-based trust model and implemented a Modbus variation to detect final-phase attacks. The variation was tested against two publicly available Modbus datasets (EPM and ATENA H2020) under three kinds of tests, namely external, internal, and internal with IP-MAC blocking. The first test assumes that external substation adversaries remain so and the second test assumes all adversaries within the substation. The third test assumes the second test but blacklists any device that sends malicious requests. The tests were performed from a Modbus server’s point of view and a Modbus client’s point of view. Aside from detecting the attacks within the dataset, our model also revealed the behaviour of the attack datasets and their influence on the trust model components. Being able to detect all labelled attacks in one of the datasets also increased our confidence in the model in the detection of attacks in the other dataset. We also believe that variations of the model can be created for other OT-based protocols as well as extended to other critical infrastructures.

A time-sensitive network (TSN) extends the conventional Ethernet to support time-sensitive data flow. Thus, it enables simultaneous transmission of high reliability (HR) flow, medium reliability (MR) flow, and low reliability (LR) flow on the same network, thereby improving the reliability of data transmission. A TSN is a symmetric network that connects sensors and other facilities. As a backbone network, it can efficiently connect the underlying sensors and other levels of facilities, as well as ensure the quality of service of the network. For modern supervisory control and data acquisition (SCADA) systems, several types of sensors are widely used. The acquisition cycle of sensors for different purposes varies significantly from milliseconds to seconds. Moreover, these data also have different real-time requirements. Based on satisfiability modulo theories (SMT), this study proposes a TSN routing and scheduling method by adding related scheduling constraints. Compared with other methods, the proposed method can realize the routing and scheduling of hybrid flow in a hyper period and consider MR flow and LR flow, which improves the feasibility and certainty of data flow interaction between substations.

The accurate and timely detection of irregular behavior of substation personnel plays an important role in maintaining personal safety and preventing power outage accidents. This paper proposes a method for irregular behaviors detection (IBD) of substation personnel based on an improved YOLOv4 which uses MobileNetV3 to replace the CSPDarkNet53 feature extraction network, depthwise separable convolution and efficient channel attention (ECA) to optimize the SPP and PANet networks, and four scales of feature maps to fuse to improve the detection accuracy. First, an image dataset was constructed using video data and still photographs preprocessed by the gamma correction method. Then, the improved YOLOv4 model was trained by combining Mosaic data enhancement, cosine annealing, and label smoothing skills. Several detection cases were carried out, and the experimental results showed that the proposed improved YOLOv4 model has high accuracy, with a mean average precision (mAP) of 83.51%, as well as a fast detection speed, with a frames per second (FPS) of 38.06 pictures/s. This represents better performance than other object detection methods, including Faster RCNN, SSD, YOLOv3, and YOLOv4. This study offers a reference for the IBD of substation personnel and provides an automated intelligent monitoring method.

This paper is a research article for finding the optimal control of smart power substations for improving the network parameters and reliability. The included papers are the most essential and main studies in the field, which propose a different approach to reach the best performance in electrical power systems. The parameters for improvement are the ability for tracking of the reference signal, stabilizing the system, reducing the error in steady state and controlling the behavior in transient state. The research focuses with the reaching a better transient stability considering voltage and frequency dynamic parameters. The optimal model for the control is focused on minimizing energy consumption but maintaining the controllable parameters, exploring some optimization techniques to find the optimal control, with of aim of minimizing the response time, the energy consumption, and maximizing the reliability by means of improving the controller to be more robust.

Renewable generation in power systems has proved to be challenging for system operators owing to the increasing levels of penetration. The operation of power systems currently requires additional flexibility and reserves due to the intermittency and unpredictability of renewable generators. However, it is difficult to precisely predict and control the stochastic nature of renewable sources; nevertheless, its capacity continues to increase. To monitor and control renewable generators efficiently, the entire system needs to be established in a hierarchical order. This study proposed the concept of a substation that is uniquely designed for renewable interconnection. The purpose of this substation is simple: to make the renewable generators dispatchable to operators such that each group of renewable generators is sufficiently stable to be considered as conventional generators. For this purpose, methods for sizing and controlling energy storage system are proposed based on forecasts and error distributions.

Asset-management accounts for a significant share of grid operators’ influenceable costs, which are under high economic pressure due to deregulation. In asset-management, visual inspections are the main measure to determine asset conditions. In the context of digitalization, we propose a concept to acquire additional information about the condition of distribution substations and to derive flexible inspection intervals from this information, in contrast to fixed intervals that are common in scientific literature and practice. Thus, knowledge about the substations increases, inspection intervals can be expanded dynamically, and significant cost savings are possible, which we demonstrate by the example of a German distribution grid operator.

A method for separating multisource partial discharges (PDs) in a substation is proposed based on selected bispectra of ultrahigh frequency (UHF) electromagnetic waves. Bispectra are sensitive to Gaussian noises and processes of symmetrical distribution. The phase information contained in bispectra can be useful and important for further signal processing. Bifrequencies where Fisher-like class separability measures between signals’ bispectra achieve their maximums are selected as characteristic parameters of the signals. Then, the selected bispectra are utilized for training the radial basis neural network to separate PD UHF signals in a substation. The method is used to analyze simulated UHF signals mixed with Gaussian white noise and frequency-fixed interference, and to separate PD UHF signals that are collected in a 500 kV substation. In order to prove the validity of the proposed separation method, the localization results are compared with the results calculated by time delay sequence, and the proposed separating algorithm is verified in the interference circumstances of a substation. However, the exact location of PD sources cannot be calculated according to the time delay sequence when the PD sources in a substation are close to each other or there are fewer than four antennas for receiving signals.

The advanced traction power supply system (ATPSS) is a new directional development for traction power supply systems, which can totally remove the neutral sections and effectively promote power quality. However, the existing converters suffer from small substation capacity. In this paper, a new configuration based on a three-level neutral point clamped (3L-NPC) three-phase to single-phase cascade converter in a substation is proposed for ATPSS, which can be used to match the capacity of the converter for high voltage and large power applications. The control strategy of the proposed converter is analyzed in depth, and the phase disposition sinusoidal pulse width modulation (PD-SPWM) with phase shift carrier SPWM (PSC-SPWM) is employed in the inverters. Then, the inductance equalizing circuit is applied for the voltage balance on the DC-link. Besides, a LC filter circuit is designed to eliminate the double line-frequency ripple of DC voltage. Afterwards, a simulation model and an experimental prototype are developed, respectively. The simulation results show that the proposed converter in this paper can not only meet the requirements of voltage and capacity for the traction network, but also improve power quality. Finally, the experimental results verify the correctness and feasibility of the proposed control strategy.

Hardwired sensor installations using proprietary protocols found in today’s district heating substations limit the potential usability of the sensors in and around the substations. If sensor resources can be shared and re-used in a variety of applications, the cost of sensors and installation can be reduced, and their functionality and operability can be increased. In this paper, we present a new concept of district heating substation control and monitoring, where a service oriented architecture (SOA) is deployed in a wireless sensor network (WSN), which is integrated with the substation. IP-networking is exclusively used from sensor to server; hence, no middleware is needed for Internet integration. Further, by enabling thousands of sensors with SOA capabilities, a System of Systems approach can be applied. The results of this paper show that it is possible to utilize SOA solutions with heavily resource-constrained embedded devices in contexts where the real-time constrains are limited, such as in a district heating substation.

Lead-acid batteries are the most frequently used energy storage facilities for the provision of a backup supply of DC auxiliary systems in substations and power plants due to their long service life and high reliability. It is possible to define the load in these systems, therefore the IEEE 485 Standard can be used for the selection of batteries according to the conventional method of selection. Special attention is paid in the paper to the technical selection of a lead-acid battery, which depends on its operational reliability that decreases with battery aging. It is defined by the extent of maintenance during its service life. A cost analysis was also carried out, which took into consideration maintenance and procurement costs, as well as the costs of the related air conditioning that keeps the prescribed temperature and ventilates the battery room. The impact is shown of selecting a lead-acid battery on the battery room’s operating safety when charging. The final selection of lead-acid battery is performed using an optimization algorithm of differential evolution. Using the optimization process, the new battery selection method includes the technical sizing criteria of the lead-acid battery, reliability of operation with maintenance, operational safety, and cost analysis. Two cases of selection of lead-acid batteries for the backup supply of a DC auxiliary system in a transmission substation are presented in the paper, where the input data were determined based on measurements in an existing substation. A comparison is made between the existing conventional and new lead-acid battery selection method based on optimization.

A new approach to lightning transient studies including complex grounding grids is presented in this paper. The grounding system is modeled in Matlab/Simulink based on the transmission line theory. Using a bottom-up approach and considering the properties of the fundamental elements, a detailed view of measurement values will be presented and analyzed. The Matlab/Simulink grounding system models are interfaced for co-simulation with EMTP-RV trough Functional Mock-up Interface (FMI) 2.0. This modeling approach allows the use of the full component library and network design by EMTP-RV to evaluate and analyze the effects of the grounding system and transmission network simultaneously in Matlab/Simulink. The results present a simplified transmission system where a surge is injected, Conseil International des Grands Réseaux Électriques (CIGRE) 1 kA 1.2/50, in far-end of a transmission line. When reaching a substation, the surge is injected into the grounding system through a surge arrester.

Low-Energy District Heating (DH) systems, providing great energy savings by means of very low operating temperatures of 55 °C and 25 °C for supply and return respectively, were considered to be the 4th generation of the DH systems for a low-energy future. Low-temperature operation is considered to be used in a low-energy DH network to carry the heat produced by renewable and/or low grade energy sources to low-energy Danish buildings. In this study, a comparison of various design considerations with different levels of maximum design static pressures was performed, and their results evaluated in terms of energetic, exergetic, economic, and environmental perspectives.

A radio frequency antenna array was adopted to localize partial discharge (PD) sources in an entire substation. The deployment of an antenna array is a significant factor affecting the localization accuracy, and the array needs to be carefully selected. In this work, a hybrid method of particle swarm optimization (PSO) and a genetic algorithm (GA) is proposed to optimize the array deployment. A direction-of-arrival (DOA) estimation algorithm applicable to arbitrary array configurations is firstly presented. The Cramér-Rao lower bound (CRLB) was employed to evaluate the localization accuracy of different arrays, and two objective functions characterizing the estimation errors of coordinates and the DOA are proposed. With the goal of minimizing the objective functions, the array deployments for the coordinate and DOA localizations were optimized by using the hybrid PSO/GA algorithm. Using the developed method, optimal antenna configurations for different constraint areas, aspect ratios, and numbers of sensors were investigated. The results indicate that the optimal deployments for coordinate and DOA estimations are different; specifically speaking, superior DOA performance is achieved when all antennas are placed on the outer boundary of the constraint area while part of the antennas in the optimal coordinate array are placed in the middle position.

To separate and locate multi-partial discharge (PD) sources in a substation, the use of spectrum differences of ultra-high frequency signals radiated from various sources as characteristic parameters has been previously reported. However, the separation success rate was poor when signal-to-noise ratio was low, and the localization result was a coordinate on two-dimensional plane. In this paper, a novel method is proposed to improve the separation rate and the localization accuracy. A directional measuring platform is built using two directional antennas. The time delay (TD) of the signals captured by the antennas is calculated, and TD sequences are obtained by rotating the platform at different angles. The sequences are separated with the TD distribution feature, and the directions of the multi-PD sources are calculated. The PD sources are located by directions using the error probability method. To verify the method, a simulated model with three PD sources was established by XFdtd. Simulation results show that the separation rate is increased from 71% to 95% compared with the previous method, and an accurate three-dimensional localization result was obtained. A field test with two PD sources was carried out, and the sources were separated and located accurately by the proposed method.

Power devices intended for high-voltage systems must be tested according to international standards, which includes the short-time withstand current test and peak withstand current test. However, these tests require very special facilities which consume huge amounts of electrical power. Therefore, mathematical tools to simulate such tests are highly appealing since they allow reproducing the electromagnetic and thermal behavior of the test object in a fast and economical manner. In this paper, a three-dimensional finite element method (3D-FEM) approach to simulate the transient thermal behavior of substation connectors is presented and validated against experimental data. To this end, a multiphysics 3D-FEM method is proposed, which considers both the connector and the reference power conductors. The transient and steady-state temperature profiles of both the conductors and connector provided by the 3D-FEM method prove its suitability and accuracy as compared to experimental data provided by short-circuit tests conducted in two high-current laboratories. The proposed simulation tool, which was proven to be accurate and realistic, may be particularly useful during the design and optimization phases of substation connectors since it allows anticipating the results of mandatory laboratory tests.