Electrical Assets Research Articles

PD-Free Design of Insulation Systems: An Application to Laminated Busbars

The reliability of components of industrial electrical assets fed by power electronics might be at risk due to the type and extent of electrothermal stresses. The move of power electronics toward higher levels of voltage, switching frequency, slew rate, and specific power increases the risk of partial discharge inception and thus of accelerated extrinsic aging and premature failure. The reaction to this challenge is to embrace the concept of partial discharge-free (PD-free) design and operation. This paper presents a PD-free approach to the design of laminated busbars, considering both AC and DC insulation subsystems, and focusing on surface insulation. The availability of a recently proposed model to estimate the inception field is a key tool. The model is validated through PD measurements performed on a laminated busbar, using new automatic software that can identify the type of source generating PD. Combined with electric field calculations, the model provides estimates of the PD inception voltage which are almost coincident with the measurement results. Inception voltages in the order of 10 kV and 20 kV have been observed for AC and DC excitation, respectively. In the case of DC supply, tests at different ambient temperatures, 25 °C and 60 °C, indicate that the inception voltage does not change significantly with temperature. Disposability, scalability to any voltage/power, and capability to work, potentially, for any other type of insulation system, are interesting features of the proposed approach, which are discussed in the paper.

Estimation of the Partial Discharge Inception Voltage of Electrical Asset Components at Variable Environmental Pressure: A Modelling Approach

Since partial discharges, PD, are a major accelerated degradation mechanism of organic electrical insulation systems, measuring partial discharge inception voltage, PDIV, of electrical asset components in aviation and aerospace is a fundamental tool to cope with life, safety, and reliability requirements. Partial discharge phenomenology and inception voltage depend on pressure, specifically, PDIV decreases with pressure. To avoid PD inception during aircraft or aerospace vehicle operation, the value of PDIV must be known at any pressure that electrical asset components will experience. However, a lack of experimental facilities adequate to test PD on real-size asset components might prevent from having PD-related information at pressures lower (or higher) than standard atmospheric pressure, SAP. This paper presents a heuristic approach, based on physics-derived PD field inception models, that allows the estimation of PDIV at low pressure to be carried out based on measurements made at SAP, when the typology of the defect causing partial discharge is known (from SAP PD measurements), but the precise type, size, and location of the PD-generating defect is unknown. It is shown that PDIV estimates obtained by the proposed models for internal and surface discharges are in good agreement with measured values in a range from SAP to 0.05 bar, testing simple insulation geometries but also real asset components, such as motors.

Dry Ice Cleaning of Electrical Equipment: Revitalize Electrical Assets with Precision Cleaning

Dry Ice Cleaning of Electrical Equipment: Revitalize Electrical Assets with Precision Cleaning

AC ripple on DC voltage: Experimental and theoretical investigation of the impact on accelerated ageing in electrical insulation

AbstractWith the increasing penetration of DC systems into the high voltage and medium voltage power industry, DC voltage is becoming common for distribution/transmission and to supply different typologies of loads. The allowable extent of AC ripple superimposed to DC, and its effect on insulation ageing, is a long‐term discussed topic. The most harmful phenomenon causing extrinsic ageing acceleration and insulation system premature failure is partial discharges (PD); thus, the risk of incepting PD due to AC ripple could become a primary issue for electrical asset equipment reliability. In this work, the impact of AC sinusoidal ripple on insulation system life and reliability is dealt with, considering both intrinsic and extrinsic ageing but focusing on the latter, that is, the PD aspect. Experiments are performed to assess how the jump voltage (due to AC ripple) and the DC component impact on PD activity in terms of amplitude and repetition rate. For the first time, the correlation between the magnitude of jump voltage associated with ripple and PD inception is established, shedding a light on the allowable ripple extent which does not impact significantly on ageing and premature insulation failure. This approach can provide straightforward tools for design specification and ageing inference of insulation systems.

Partial Discharge Pattern Recognition Based on an Ensembled Simple Convolutional Neural Network and a Quadratic Support Vector Machine

Partial discharge (PD) is a crucial and intricate electrical occurrence observed in various types of electrical equipment. Identifying and characterizing PDs is essential for upholding the integrity and reliability of electrical assets. This paper proposes an ensemble methodology aiming to strike a balance between the model complexity and the predictive performance in PD pattern recognition. A simple convolutional neural network (SCNN) was constructed to efficiently decrease the model parameters (quantities). A quadratic support vector machine (QSVM) was established and ensembled with the SCNN model to effectively improve the PD recognition accuracy. The input for QSVM consisted of the circular local binary pattern (CLBP) extracted from the enhanced image. A testing prototype with three types of PD was constructed and 3D phase-resolved pulse sequence (PRPS) spectrograms were measured and recorded by ultra-high frequency (UHF) sensors. The proposed methodology was compared with three existing lightweight CNNs. The experiment results from the collected dataset emphasize the benefits of the proposed method, showcasing its advantages in high recognition accuracy and relatively few mode parameters, thereby rendering it more suitable for PD pattern recognition on resource-constrained devices.

ЭКОНОМИЧЕСКАЯ ЦЕЛЕСООБРАЗНОСТЬ ПРИМЕНЕНИЯ СОЛНЕЧНЫХ ФОТОЭЛЕКТРИЧЕСКИХ МОДУЛЕЙ

The Annotation. The article is devoted to the technical, economic and psychological aspects of the development of solar energy in Russia. In today’s world, the dynamic business environment requires organizations and individuals to timely and regularly adapt and effectively manage their electrical assets to achieve sustainability and economic growth. Managers and private owners are increasingly resorting to the use of flexible housekeeping methods in terms of energy efficiency, which allow them to adapt to conditions and processes in the world. There is an opinion that solar energy in Russia is not enough for the widespread use of solar energy products, which is far from the truth. In certain regions of the Russian Federation, the installation and industrial use of solar photovoltaic modules is economically justified. The article provides an overview of modern approaches to solving solar energy problems. The experience of creating and using solar power plants in the context of economic efficiency is considered. Dependencies, cause-and-effect relationships, advantages and disadvantages of solar energy for private electricity consumers and businesses are identified, and examples of its successful application in various industries are given.

Grid-aware Stochastic Game modeling of residential electric flexibility under incentives

We consider a community of households owning electrical assets that can be operated as flexible loads, such as an electric vehicle, a heat pump with thermal storage and a stationary battery. Automated agents are tasked with the management of flexibility under a variable time-of-use tariff with the goal of maximizing final user utility. A population of homogeneous automated agents with similar interests, managing flexibilities of the same nature, runs the risk of stressing the grid through excessively synchronized actions, and this interaction among the agents has to be taken into account. We model this environment as a Stochastic Game, developing a formulation of the state and action spaces and obtaining the transition probability matrix. The probabilities involved are fitted on real or realistic synthetic data. Leveraging the particular structure of the problem, we propose a two-step solution method similar to policy iteration, that proves capable of producing sensible solutions. Finally, we provide an example of flexibility steering through the modulation of the time-of-use tariff, investigating the effectiveness of the incentive depending on its entity and the model parameters that characterize punishment for overcoordination and user satisfaction, and we illustrate how the tool could be employed in a real Energy Community.

Simplifying Rogowski Coil Modeling: Simulation and Experimental Verification.

The integration of renewable energy sources, electric vehicles, and other electrical assets has introduced complexities in monitoring and controlling power networks. Consequently, numerous grid nodes have been equipped with sensors and complex measurement systems to enhance network observability. Additionally, real-time power network simulators have become crucial tools for predicting and estimating the behavior of electrical quantities at different network components, such as nodes, branches, and assets. In this paper, a new user-friendly model for Rogowski coils is presented and validated. The model's simplicity stems from utilizing information solely from the Rogowski coil datasheet. By establishing the input/output relationship, the output of the Rogowski coil is obtained. The effectiveness and accuracy of the proposed model are tested using both simulations and commercially available Rogowski coils. The results confirm that the model is simple, accurate, and easily implementable in various simulation environments for a wide range of applications and purposes.

Fault Prediction in Electrical Assets Using Infrared Thermography

An infrared thermography technique is discussed in this paper to locate and diagnose the electrical equipment issue. Overheating is among major problems for an electrical device and entire power system. These overheated hotspots must be detected so that the fault can be predicted before it occurs. We used a thermal image of an electrical device taken from a infrared camera to apply our method to detect the hot region and find the maximum temperature and minimum temperature in the image. Image de-noising is done with the help of morphological reconstruction followed by Watershed transformation for image segmentation to identify and separate the region having high pixel intensity as we know that area with high pixel intensity will also have high temperature. Our method achieved near to exact maximum and minimum temperature of electrical device.

FEA-Based Simulation of Accelerated Ageing in a Power Cable Due to Sustained Partial Discharge Activities in a Spherical Cavity

The reliability of electrical assets is greatly influenced by the quality of their insulations. Key power installations such as power cables are manufactured with polymer-based materials as part of their insulation system. However, accelerated ageing of equipment insulations due to manifestation of defect(s), and partial discharges (PDs) can offset the operation of these systems or even lead to breakdowns. In this study, a non-deterministic model to simulate the phenomenon of repetitive discharges in a spherical air-filled cavity within a practical power cable has been investigated. In addition, the work contributes to the understanding of PD behaviour and field distribution under different ageing conditions considering changes in cavity surface conductivity. First, a section of the practical XLPE cable containing the cavity is developed in 2D using COMSOL software, and a finite element analysis (FEA) of the electric field distribution within the cable insulation is performed. The magnitude of the cavity local field, that is enough to ignite a PD, is investigated. Alongside the COMSOL model, the activity of sustained internal PD is simulated in MATLAB by introducing a random sample generating factor and adjusting the model’s parameters to obtain something close to the practical results. Furthermore, the impact of continuous PD in the power cable under different cavity dimensions and surface conductivity is likewise investigated, and a phase resolved PD (PRPD) pattern is established. The result shows that the magnitude and number of PDs per cycle increase as the cavity size and its surface conductivity increase. Finally, when the cavity surface conductivity rises, the amplitude of the electric field generated by the surface charge distribution and the number of PDs per cycle approach their maximum values.

Developing an IEEE Continuous Thermal Monitoring Standard and a Major Company’s Protection of Their Electrical Assets: Exploring Continuous Thermal Monitoring for Electrical Connections and Components

The process of initiating an IEEE standard is not well understood by many. The objective of this paper is to follow the development of an IEEE Standard Working Group (WG) and the initial efforts to develop an IEEE Standard for continuous thermal monitoring (CTM). This also investigates methods to monitor the operating condition of equipment connections as an alternative to infrared (IR) thermography surveys. It includes a review of methods that can capture data for analysis, trending, and predictive maintenance for personnel safety and extended equipment reliability. Maintenance of electrical switchgear and motor control centers (MCCs) is critical to elevating safety and assuring facilities’ uptime in all industries. Key concerns in every company’s electrical distribution system include the connections and terminations of electrical equipment.

Reverse Blocking Over Current Busbar Protection Scheme Based on IEC 61850 Architecture

Substation Automation System (SAS) is currently in a matured state of technology that shall facilitate transformational changes from conventional protection scheme. IEC 61850 protocol is considered as the crux of digital SAS due to its multifunction features that include seamless communication, ability to integrate various intelligent electronic devices, potential for improved real-time condition monitoring, reliable protection, and control of critical electrical assets. Because the application of IEC 61850 in SAS is relatively new and has not fully implemented in many substations yet, further feasibility studies using multivendor equipment to assess its performance under different operating conditions is imperative. In this article, a practical reliable and efficient reverse blocking over current bus bar protection scheme based on IEC 61850 is implemented and tested. Also, a comparison of digital SAS and conventional protection scheme is presented to highlight the superiority of the former one. Experimental results attest the reliability and effectiveness of the proposed digital protection scheme along with the accuracy and security of transmitting data packets using sampled values and generic objective-oriented substation event communication protocols adopted by IEC 61850.

A Global Approach to the Design of Insulation Systems for Aerospace Electrical Assets: Focus on Printed Circuit Board

The evolution of power electronics in aerospace and, in general, electrified transportation assets, is centered on the development of MV power electronics converters, which maximizes power density and efficiency. This turns into high-field and temperature design, ultra-fast switching, and high frequency modulation. Such conditions may pose significant and unpreceded electrothermal stresses on insulation systems of electrical asset components, such as printed circuit boards. Magnitude, profile and time behavior of stresses, as well as their effect on intrinsic and extrinsic aging mechanisms, have to be known, being the basis of a highly-reliable electrothermal insulation design able to provide a specified life at specified failure probability. This paper introduces innovative criteria to optimize the design of insulation system of MV PCB, according to the new “three-leg” approach that consists of interlacing electric field simulation, life and discharge modelling, and partial discharge testing. The essence of such an approach is to design an insulation system, as regards bulk and surface sub-components, by a global view, where aging processes rule design rather than macroscopic failure risk. Accordingly, life and reliability are determined by appropriate models, accounting for intrinsic aging and, in addition, design ensures that operation stresses do not trigger extrinsic accelerated aging mechanisms, as those associated to partial discharges. It is shown in the paper that the proposed approach can lead to an innovative and effective design, delivering the specified life and ensuring that the electrical field on the surface (and in the bulk) is limited to values below the threshold for partial discharge inception. This can question, in principle, the use of creepage and clearance tools, since the new design procedure will be related to the minimization of likelihood of partial discharge inception, rather than to avoid the risk of macroscopic surface discharges.

Federated learning for 5G-enabled infrastructure inspection with UAVs

Electricity infrastructures include assets that require frequent maintenance, as they are exposed into heavy use, in order to produce energy that satisfies customer demands. Such maintenance is currently performed by specialized personnel that is scaffolding to spot damages or malfunctioning equipment. Scaffolding is time-consuming and incurs accident risks. To tackle this challenges, grid operators are gradually using Unmanned Aerial Vehicles (UAVs). UAV trajectories are observed by a centralized operation center engineers for identifying electrical assets. Moreover, asset identification can be further automated through the use of Artificial Intelligence (AI) models. However, centralized training of AI models with UAV images may cause inspection delays when the network is overloaded and requires Cloud environments with enough processing power for model training on the operation center. This imposes privacy concerns as sensitive data is stored and processed externally from the infrastructure facility. This article proposes a federated learning method for UAV-based inspection that leverages a Multi-access Edge Computing platform installed in edge nodes to train UAV data and improve the overall inspection autonomy. The method is applied for the inspection of the Public Power Corporation’s Innovation Hub. Experiments are performed with the proposed method as well as with a centralized AI inspection method and demonstrate the federated learning benefits in reliability, AI model processing time and privacy conservation.

Aerospace Environmental Challenges for Electrical Insulation and Recent Developments for Electrified Aircraft.

The growing trend towards high voltage electrical assets and propulsion in the aeronautics and space industry pose new challenges in electrical insulation materials that cannot be overlooked. Transition to new high voltage electrified systems with unprecedented high levels of voltage, power, and efficiency must be safe and reliable. Improvements in both performance and safety of megawatt power systems is complicated because of the need for additional power transmission wiring and cabling and new safety requirements that have the potential of making the resulting systems heavier. To mitigate this issue, novel lightweight materials and system solutions are required that would result in lower specific weights in the insulator and conductor. Although reduced size and weight of system components can be achieved with new concepts, designs, and technologies, the high voltage (≥300 V) operation presents a significant challenge. This challenge is further complicated when considering the extreme operating environment that is experienced in aircraft, spacecraft, and targeted human exploration destinations. This paper reviews the extreme environmental challenges for aerospace electrical insulation and the needs associated with operating under high voltage and extreme environments. It also examines several recently developed robust lightweight electrical insulation materials that could enhance insulation performance and life. In aerospace, research must consider mass when developing new technologies. The impact of these recent developments provides a pathway which could enable next generation high altitude all electric aircraft, lightweight power transmission cables for a future sustained presence on the Moon and missions to Mars using HV propulsion, such as spacecraft with Nuclear Electric Propulsion systems.

Insulating Material Development for the Design of Standoff Insulators Fed by Hybrid Voltage.

Innovative electrical assets are being developed in transmission and distribution, as well as in electrified transportation, from ships to aerospace. In general, power electronics have to master the whole power supply, being the driver of high specific power, low weight and volume components, in addition to enabling flexible and highly variable power flow. In these conditions, electrical and electronic insulation systems will have to withstand new types and levels of electric stresses, while still maintaining its reliability throughout its whole design life. This paper presents a study on the interrelation between insulating material properties and surface field of standoff insulators. The aim is mainly to provide indications on material properties which can be tailored to provide a robust, reliable and optimised insulator design that will hold for any type of electrical stress the insulation will have to withstand during operation. Specifically, we focus on ac and dc supply, including voltage transients, which could feed the same insulator depending on operation, according to a hybrid asset paradigm. The challenge is, indeed, to establish a pattern to material and insulation system design which takes into account the differences between the types of electrical stress profile and magnitude when insulators are supplied either in a dc or in ac, in order to infer which type of material characteristics would be more appropriate for the sake of life and reliability. The main contribution of this paper is to show that engineering the values of bulk and surface conductivity (which can be done selecting appropriate materials or modifying them, e.g., by nano-structuration) and modelling surface discharge inception would allow the electric field profile to be stabilised whatever the shape of the applied waveform. This will enable us to reach a reliability target that not only accounts for macroscopic phenomena, but also for the likelihood of extrinsic accelerated aging mechanism occurrence as partial discharges. In such a way, optimization of conditions to improve life, reliability, design and creepage and clearance characteristics can be achieved.

Smart charging strategies for heavy electric vehicles

With emission standards tightening around the world and the popularity of electric cars rising, the electrification of heavy-duty vehicles (e.g., diesel trucks) appears to be a natural progression. For electric truck (ET) charging, a return-to-base strategy with chargers located where trucks begin and end each day, such as trucks used in cargo, freight, and delivery entities, is becoming increasingly viable and attractive. This return-to-base strategy; however, has impacts on the peak demand of a facility which can contribute to an increase in demand charge and requires electrical asset upgrades in certain circumstances. This challenge is different and unique compared to the light-duty passenger vehicles charging challenge (i.e., low distributed charging load and longer charging periods). To address this ET charging challenge, this paper proposes a smart charging system (SCS) that manages the charging process of ETs at their commercial facilities, with the objective of minimizing the peak demand of the aggregate load profile at the facility. Our simulation studies show the effectiveness of the proposed SCS in reducing the peak demand of the facility. The proposed solution can achieve a monthly saving in demand charge of up to 54% compared to uncontrolled charging schemes. • A smart charging system to address the challenges of ET charging at their facilities. • Addresses ET operators' concerns over the increase of demand charges of ET charging. • Accommodates the V2V and V2G technologies in the smart charging system of ETs. • Increases the adoption rate of electric trucks into the different commercial fleets. • The proposed solution can achieve a monthly saving in demand charge of up to 54%.

A fuzzy inference-based approach for estimating power transformers risk index

Risk assessment is a key point for power system operators interested in the implementation of asset management systems. Among critical electrical assets, the power transformer is probably the most representative. This paper presents a novel method for estimating a risk index for power transformers. The proposed method is based on three Fuzzy Inference Systems (FIS), aimed to integrate expert criteria for the creation of rules and the definition of the membership functions of the entries. The first FIS is dedicated to the calculation of a transformer Health Index (HI), based on the results of the physical-chemical tests normally performed on the insulating liquid of the units. The second FIS is oriented to the determination of a Consequence Factor (CF) of the final failure of the power transformer, and it is determined considering aspects such as overload to other assets, average load supplied by the unit, critical loads supplied, oil volume, proximity to other buildings and penalties for the unavailability of the asset. The last FIS combines the results of the previous FIS, i.e., HI and CF, to provide an estimation of the transformer risk index. The methodology has been designed to perform management of power transformer fleets by allowing decisions to be made, regarding investments, based on risk assessment. The proposal has been tested on a fleet of 15 units. Obtained results show that the FIS for combining HI and the CF leads to more consistent risk indexes, than those obtained when performing the conventional operation of multiplication between HI and FC.

Impacts of Harmonic Voltage Distortions on the Dynamic Behavior and the PRPD Patterns of Partial Discharges in an Air Cavity Inside a Solid Dielectric Material

The monitoring of partial discharges (PDs) is one of the main methods used worldwide for evaluation and diagnosis of the insulation conditions in equipment powered by medium and high voltages. The occurrence of PDs is usually an indication of the appearance of insulation defects, which over time can compromise the dielectric withstand of the material used, increasing the probability of complete breakdown. In general, laboratory tests for detecting and registering PDs are carried out using purely sinusoidal voltages. However, it is very common for an electrical asset to be subjected at some point in its operating life to voltages distorted by harmonic components. Some studies reported in the literature reveal that harmonic distortions can affect the PDs’ characteristics, nevertheless, the effects of individual harmonic components on PDs still need to be analyzed. In this context, this paper proposes to evaluate the impacts of harmonic voltage distortions on the dynamic behavior and the phase-resolved partial discharge (PRPD) patterns of PDs in an air cavity within a solid dielectric material. For this, a simulation model was implemented, which was used to analyze the effects of applying distorted voltages composed of different harmonic orders (third, fifth, and seventh) and distinct levels of distortion (1%, 3%, 5%, 10%, 15%, and 20%). In addition, the influence of the third harmonic phase angle on PDs is also analyzed. The results extracted from the simulations revealed that the harmonic distortions caused changes in the numbers of PDs per cycle, in the mean apparent charges of the PDs per cycle, and in the PRPD patterns’ characteristics. These changes were very significant for higher distortion levels, which in practice may impair the interpretation of PD measurement records for the diagnosis of the condition of the insulation system.

Numerical Analysis of Filtering Circuit for Partial Discharges

Partial Discharge (PD) is a small electrical spark that happens within the insulation of medium and high voltage electrical assets. It is important to note that the discharge will erode the insulation and eventually result in disastrous insulation failure. Thus, PD detection is a crucial issue in high voltage insulation area. However, the on-site field PD tests, the high frequency PD signals detected by sensors, are vulnerable to interferences and background noises. This has a negative effect on high voltage apparatus fault diagnosis and localization accuracy. For that reason, noise suppression has become an urgent and vital issue for field high frequency PD signal testing. Thus, this research aims to model a filtering circuit to suppress the noise along with PD in high frequency measurement. A filtering circuit was analysed by using Proteus software to filter out the noise along with PD with decent accuracy and efficiency. Then, performance investigation of active high pass and passive high pass was conducted and studies to filter out PD noise suppression in high frequency were successfully developed. The active filter was focusing on the first order stage until fourth order stage. The passive filter only concentrated on two types of order stage; first order stage and second order stage. The result demonstrated that active high pass filter presented the best performance with low decibel frequency response (-20 dB), and was suitable for this research purpose compared to passive high pass filter. Besides, 700 Vrms has been selected to check the response at high voltages and the frequency values set at 50 Hz for low frequency and 8 kHz for high frequency. This specification design values have been selected because it is suitable for situations in high-tension power line. This type of filtering circuit is suitable to be used for academic and lab experimentation.