Power System Assets Research Articles

Distinction between Arcing Faults and Oil Contamination from OLTC Gases

Power transformers are the most important and expensive assets in high-voltage power systems. To ensure an adequate level of reliability throughout the transformer’s lifetime, its maintenance strategy must be well defined. When an incipient fault occurs in the transformer insulation, a gas concentration pattern, representative of the type of fault, is generated. Fault-identification methods use gas concentrations and their ratios to identify the type of fault. None of the traditional or new fault-identification methods attempt to detect transformer oil contamination from on-load tap changer (OLTC) gases. In this study, from dissolved gas analysis (DGA) samples of transformers identified as contaminated in a previous study, fault-identification methods based on graphical representations were used to observe the patterns of results. From such patterns, Duval’s triangle and pentagon methods were modified to include a new zone indicating oil contamination (OC) from OLTC gases. Finally, the proposed modifications were validated using 75 DGA samples extracted from previous studies that were identified as D1 or D2 faults or contaminated from OLTC. This validation showed that only 14.7% and 13.3% of the DGA samples fell within the new OC zone of the proposed triangle and pentagon, respectively.

Vibration-Signal-Based Deep Noisy Filtering Model for Online Transformer Diagnosis

Machine learning methods are effective for the diagnosis of power transformer faults. However, influenced by uncertainty and noise in data, machine learning-based diagnostic methods are still in the initial phase of certain assets in power systems. To mitigate this gap, a deep noisy filtering diagnostic (DNFD) model is proposed for accurate and rapid evaluations of power transformer faults using noisy vibration signals. A balanced isolation forest method is employed to detect abnormal data from the original vibration signals. Two deep noisy filter networks suppress the level of noise, based on which contrastive learning obtains the transformer fault states. Datasets collected from a 10 kV real power transformer validate the proposed model. The results demonstrate that the proposed method acquires a higher fault diagnostic accuracy with respect to the compared algorithms, showing the superiority and efficacy of the proposed model.

Planning and Optimizing the Replacement Strategies of Power Transformers: Literature Review

The power transformer is one of the most critical assets in power systems; therefore, planning and optimizing the economic investment for its replacement is crucial for the financial efficiency of the utility. A compilation of the main approaches reported in the literature for the replacement of oil-immersed power transformers is presented in this article. A chronological description of procedures presented in the literature for the determination of risk index, useful life evaluation, and transformer replacements is provided. Methodologies that use the theoretical basis of the degree of polymerization of the solid insulation of the units through the oxidation aging process to estimate their condition bring together the best tools currently available to achieve this objective. However, it is important and pertinent to complement these methodologies by considering the aging processes by pyrolysis and hydrolysis together and by incorporating economic analyses for appropriate replacement and management of these aged units.

Toward Models of Impact and Recovery of the US Western Grid from Earthquake Events

A Cascadia Subduction Zone (CSZ) earthquake will cause widespread damage to numerous lifelines and infrastructure along the northern US west coast. The goal of the presented research is to provide a bottom up estimate of the impact on and subsequent recovery of a Cascadia Subduction Zone earthquake on the US western grid to supplement and enhance the expert opinion estimates provided to date. The scope is limited to only consideration of shaking damage to utility substation equipment components of a power system model. The analysis utilizes probabilistic models of damage and recovery for substation power system assets, along with graph techniques for modeling connectivity, and Monte Carlo quasi steady state power flow solutions. The results show that a conservative estimate of the initial damage and loss of load is approximately 4000 MW, with a recovery estimate of 230 days.

Comparing the economic value of lithium-ion battery technologies in the nine wholesale electricity markets in North America

Lithium-ion batteries are becoming critical flexibility assets in future electric power systems. Batteries can arbitrage price differences in wholesale electricity markets to make a profit while at the same time reducing total system operating costs and improving renewable energy integration. However, lithium-ion batteries have a limited lifetime due to capacity degradation, and one battery pack can only make a limited profit before reaching its end-of-life. In this paper, we screen the profit potential of Lithium iron phosphate (LFP), nickel manganese cobalt (NMC), and lithium nickel cobalt aluminum oxides (NCA) batteries in all nine wholesale electricity markets in North America. We apply a systematic dynamic valuation framework that finds the highest revenue potential for the considered lithium-ion battery project subjecting to its degradation mechanism, while the degradation model used in the valuation is derived based on real lab test data over varying cycle conditions. The study found that battery valuation depends largely on battery technology and storage duration and varies across operational locations. Moreover, the study revealed that calendar life has a greater impact on battery valuation than cycle life for an 8-years calendar life scenario while cycle life shows greater impact for a 15-year calendar life scenario for all battery technologies. This impact is more pronounced in LFP than in NMC and NCA. The study recommends battery operators consider strategies that would maximize a longer cycle life or calendar life usage of a battery as this would accumulate higher profits over its lifetime.

Oil-Immersed Power Transformer Condition Monitoring Methodologies: A Review

A power transformer is one of the most critical and expensive assets in electric power systems. Failure of a power transformer would not only result in a downtime to the entire transmission and distribution networks but may also cause personnel and environmental hazards due to oil leak and fire. Hence, to enhance a transformer’s reliability and extend its lifespan, a cost-effective and reliable condition monitoring technique should be adopted from day one of its installation. This will help detect incipient faults, extend a transformer’s operational life, and avoid potential consequences. With the global trend to establish digital substation automation systems, transformer online condition monitoring has been given much attention by utilities and researchers alike. Several online and offline condition monitoring techniques have been recently proposed for oil-immersed power transformers. This paper is aimed at providing a state-of-the-art review for the various condition monitoring technologies used for oil-immersed power transformers. Concept of measurements and analysis of the results along with the future trend of condition monitoring techniques are presented.

Review of Grid-forming Inverters in Support of Power System Operation

The penetration of distributed energy resources in electrical grids has been steadily increasing in an effort to reduce greenhouse gas emissions. Inverters, as interfaces between distributed energy resources and grids, have become critical assets in modern power systems. In recent years, the development and application of grid-forming inverters have gained significant traction due to their capability of supporting power grid operations. A comprehensive review of grid-forming inverters is presented for power system applications. A comparison between grid-forming inverters and grid-following inverters is conducted in terms of their functionalities to highlight the potential of grid-forming inverter technologies in support of power system stability and resiliency. In addition, advanced control strategies integrated into grid-forming inverters under various operation conditions are presented through reviewing the innovations introduced in recent literature and in industrial applications. This paper is intended to provide an updated reference regarding grid-forming inverters for power system applications to researchers and practitioners in the field of power electronics.

Пристрій для оцінювання витрачання робочого ресурсу обмоток силового масляного трансформатора

A power transformer is one of the most responsible and expensive assets in power systems and networks. Failure of a power transformer can lead not only to downtime of the entire electricity transmission path, but also to danger to personnel and the environment. One of the main reasons for the failure of a power transformer is the deterioration of the insulation of the windings. The insulation of the transformer windings is affected by many different factors, but one of the main factors is the effect of temperature due to the different values of the currents flowing through the transformer windings. The power transformer is exposed to the effects of long-term and short-term loads. There are known methods and tools that allow you to assess the technical condition under long-term loads. In the literature, less attention is paid to the issue of the influence of short-term loads, although their influence on the thermal aging of the winding insulation is obvious. The author has developed a method and a mathematical model that allows to estimate the thermal effect on the insulation of the windings regardless of the duration of such an effect. The essence of the method is based on the determination of the amount of heat that is released when the current flows through the windings with the subsequent heat spread over the windings and structural elements of the transformer, which allows you to build a temperature distribution surface from the point of heat release. The paper proposes the structure of the device for estimating the residual working life of the insulation of the power transformer, which is based on the basis of the developed mathematical model. The article describes the implementation of this approach in detail. It is important to add that the proposed method does not require significant capital investments and meets the requirements of accuracy and reliability. The developed tool can be recommended for use by energy companies in the tasks of diagnosing power oil transformers, which can be integrated into the monitoring system of all electrical equipment of the distribution device of a power plant or substation, which allows to reduce in a certain way the costs of maintenance of electrical equipment.

Practical Evidence-Based Evaluation of a Combined Heat Reduction Technique for Power Transformer Buildings

Transformer buildings are at the heart of the effective operation of distribution systems, and heating problems of transformers under severe operational conditions are among the main factors affecting the lifetime, efficiency, technical losses, etc., of such important power system assets. It is crucial that the inside temperature of transformer buildings is higher than the outside temperature due to the operation of the transformer and the effect of ambient conditions. This issue may cause several problems such as additional transformer aging, losses, and moisture. The main purpose of this study is to decrease the inside temperature of transformer buildings; in other words, to prevent the inside temperature from being higher than the outside temperature. To realize this, it is recommended to apply a combined heat reduction technique by covering the outer surface with a reflective surface and use a low-emitting material on the inner surface. The relevant results of the practical evidence in this manner are presented in detail at a distribution system in Turkey with different climate and loading conditions in the summertime.

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Summary As the share of variable renewable energy (VRE) grows in the electric grid, so does the risk of curtailment. While energy storage and hydrogen production have been proposed as solutions to the curtailment problem, they often pose technological and economic challenges. Here, we analyze the potential of data center load migration for mitigating curtailment and greenhouse gas (GHG) emissions. Using historical hourly electricity generation, curtailment, and typical data center server utilization data, we simulate the effect of migrating data center workloads from the fossil-fuel-heavy PJM to the renewable-heavy CAISO. The results show that load migration within the existing data center capacity during the curtailment hours in CAISO has the potential to reduce 113–239 KtCO2e per year of GHG emissions and absorb up to 62% of the total curtailment with negative abatement costs in 2019. Our study demonstrates the overlooked role that data centers can play for VRE integration and GHG emissions mitigation.

Distributed coordination of deferrable loads: A real-time market with self-fulfilling forecasts

Increased uptake of variable renewable generation and further electrification of energy demand necessitate efficient coordination of flexible demand resources to make most efficient use of power system assets. Flexible electrical loads are typically small, numerous, heterogeneous and owned by self-interested agents. Considering the multi-temporal nature of flexibility and the uncertainty involved, scheduling them is a complex task. This paper proposes a forecast-mediated real-time market-based control approach (F-MBC) for cost minimizing coordination of uninterruptible time-shiftable (i.e. deferrable) loads. F-MBC is scalable, privacy preserving, and usable by device agents with small computational power. Moreover, F-MBC is proven to overcome the challenge of mutually conflicting decisions from equivalent devices. Simulations in a simplified but challenging case study show that F-MBC produces near-optimal behaviour over multiple time-steps.

Design and implementation of a test bed for building controls

Advanced controls play an essential role toward the improvement of building operational efficiency and the integration of responsive loads in buildings for grid services. Ideally, control algorithms must be sufficiently tested and validated before they are applied on real systems. This paper presents the development and current state of such an evolving test bed to support and enable experiments on advanced controls for buildings. The test bed presented in this paper consists of nine operating buildings—which possess various types of equipment and systems having different control systems and communication mechanisms (e.g., media and protocols) used in building automation systems—on the Pacific Northwest National Laboratory campus. The test bed architecture is developed in such a way that (1) it supports interactions among the buildings and heterogeneous building components and systems, including both virtual and physical devices, e.g., heating, ventilating, and air-conditioning and lighting systems; (2) it can be easily reconfigured for different control topologies and methodologies, e.g., centralized and distributed; (3) it allows selection of communication protocols, communication media, and computation resources; and (4) it is part of a larger cyber-physical test bed that includes both physical and virtual assets on distributed renewable generation, energy storage, and power system assets. Practical application: The test bed presented in this paper can be used by industry to develop and evaluate the performance of advanced control algorithms on real systems for buildings and buildings-to-grid applications. This provides practitioners an opportunity to test the applications and modify them accordingly based on their use cases and selection criteria, e.g., a controller modulating the temperature in a hospital will have different criterion as compared to an office building.

Risk assessment‐based long‐term transmission system hardening under prior probabilistic information

In the long-term transmission system hardening, critical components in transmission infrastructure should be identified and hardened to reduce the load loss risk in the presence of scheduled and unscheduled outages. Generally, the probabilistic information of assets in power systems can be evaluated via historical statistics. On the basis of the prior probabilistic information, this study proposed a tri-level optimisation model to deal with the problem of long-term transmission system hardening, in which the risk assessment is taken into account in the objective function. Furthermore, the problem is formulated as a two-stage robust optimisation model. To address the non-linear problem in the inner model, logarithmic transformation and piecewise linearisation are utilised to exactly linearise the non-linear terms in the model. Finally, the standard column-and-constraints generation algorithm is employed to solve the proposed model with a master-sub-problem framework. The test results on a standard IEEE RTS-96 system show the effectiveness of the proposed model.

Blockchain-based orchestration of distributed assets in electrical power systems

For historical reasons, power systems are designed, controlled and operated centrally. A coordination of the rising number of increasingly heterogeneous, small-scale and citizen- or company-owned assets is not possible with this approach, especially not in the distribution system. The goal of the PhD project presented in this extended abstract is to find out how well distributed approaches perform in orchestrating distributed assets in future power systems from a holistic point of view in comparison to centralized approaches. The research questions are defined and the planned methodology of the project is presented. The most promising use cases in this context are identified, the concept of a decentralized virtual power plant is proposed as a new use case for providing flexibility with small-scale assets and the first ideas for an evaluation framework are presented. Next steps in the project are refining the evaluation framework and evolving the yet existing lab setups. Once these are completed, simulation models can be developed and the main research questions can be answered in detail.

Performance Comparison of Multi Design Method and Meta-Heuristic Methods for Optimal Preliminary Design of Core-Form Power Transformers

Large power transformers are regarded as crucial and expensive assets in power systems. Due to the competing global market, to make a good and competing power transformer design, a non-linear optimization problem should be solved in a very short time in the preliminary design stage. The paper shows and compares the performance of four different methods to solve this problem for three phase core type power transformers. The first algorithm is a novel meta-heuristic technique which combines the geometric programming with the method of branch and bound. Then this conventional multi design method is solved by a simple iterative technique and two novel evolutionary algorithms to enhance the convergence speed. One of these algorithms is the particle swarm optimization technique which is used by many other researchers and the grey wolf optimization algorithm which is a new method in this optimization sub-problem. An example design on an 80 MVA, three phase core type power transformer using these four methods is presented and its performances are analyzed. The results demonstrate that the grey wolf optimization is a good alternative for this optimization problem.

A new monitoring and characterization system of partial discharges based on the analysis of the spectral power

<p>Partial Discharges (PD) are one of the possible causes for unexpected faults in power systems equipment, so that its measure is an essential tool for high-voltage electrical equipment maintenance. In order to characterize the PD activity, some statistic magnitudes are necessary. For this reason, the acquisition and processing of PD is very important when making critical decisions regarding disconnection or repairing assets in power systems. On the other hand, the measurement environments often present multiple sources of electrical noise, thus the proper interpretation of PD patterns is a challenge in the identification of sources of different nature. In this paper, the development of a PD monitoring system capable of displaying in real time the classic PD parameters, the PD waveform, its frequency spectrum and calculating statistical parameters of the acquisition, are presented. On the whole, a new method of identifying sources of PD and electrical noise, developed by the authors, which is based on measuring the relative spectral power of PD pulses, is shown. This method has proven effective in characterizing PD and electrical noise; a series of experiments conducted in several test objects are presented in order to validate the performance of the proposed system</p><p><span><br /><br class="Apple-interchange-newline" /></span></p>

A new monitoring and characterization system of partial discharges based on the analysis of the spectral power

<p>Partial Discharges (PD) are one of the possible causes for unexpected faults in power systems equipment, so that its measure is an essential tool for high-voltage electrical equipment maintenance. In order to characterize the PD activity, some statistic magnitudes are necessary. For this reason, the acquisition and processing of PD is very important when making critical decisions regarding disconnection or repairing assets in power systems. On the other hand, the measurement environments often present multiple sources of electrical noise, thus the proper interpretation of PD patterns is a challenge in the identification of sources of different nature. In this paper, the development of a PD monitoring system capable of displaying in real time the classic PD parameters, the PD waveform, its frequency spectrum and calculating statistical parameters of the acquisition, are presented. On the whole, a new method of identifying sources of PD and electrical noise, developed by the authors, which is based on measuring the relative spectral power of PD pulses, is shown. This method has proven effective in characterizing PD and electrical noise; a series of experiments conducted in several test objects are presented in order to validate the performance of the proposed system</p><p><span><br /><br class="Apple-interchange-newline" /></span></p>

Real-Time Monitoring of Substation Ground Potential Rise and Grounding System Impedance Using Power System Faults

Grounding system engineers and power utility owners have a duty of care to ensure that substation grounding systems continue to meet their safety performance requirements over the operational lifetime of the installation. Changes to power system or third-party assets associated with an installation, as well as environmental factors such as temperature or moisture level fluctuations, can cause variation in a grounding system's performance. To perform a grounding system assessment, engineers must select a suitable set of fault scenarios on which to base their assessments. However, the relative risk level of hazards produced by a ground fault (GF) depends on that proportion of the fault current that passes to ground through the local grounding of the installation and the duration of the event. The consideration of all hazards posed by a single installation is thus physically and theoretically an expensive proposition, particularly for installations with complex grounding systems. An electronic recording system is proposed to capture the characteristics of power system ground potential rise (GPR) events during GFs. This system allows the failure of critical grounding system components to be highlighted as indicated by a substantial change in the measured impedance. The system also establishes the GPR event frequency, allowing the probabilistic nature of GFs associated with an installation to be assessed. This paper provides an explanation of the GPR monitoring rationale and a methodology for implementing such a system, and typical results are shown from trials undertaken in recent years.

Separation of radio-frequency sources and localization of partial discharges in noisy environments.

The detection of partial discharges (PD) can help in early-warning detection systems to protect critical assets in power systems. The radio-frequency emission of these events can be measured with antennas even when the equipment is in service which reduces dramatically the maintenance costs and favours the implementation of condition-based monitoring systems. The drawback of these type of measurements is the difficulty of having a reference signal to study the events in a classical phase-resolved partial discharge pattern (PRPD). Therefore, in open-air substations and overhead lines where interferences from radio and TV broadcasting and mobile communications are important sources of noise and other pulsed interferences from rectifiers or inverters can be present, it is difficult to identify whether there is partial discharges activity or not. This paper proposes a robust method to separate the events captured with the antennas, identify which of them are partial discharges and localize the piece of equipment that is having problems. The separation is done with power ratio (PR) maps based on the spectral characteristics of the signal and the identification of the type of event is done localizing the source with an array of four antennas. Several classical methods to calculate the time differences of arrival (TDOA) of the emission to the antennas have been tested, and the localization is done using particle swarm optimization (PSO) to minimize a distance function.

A device-level service-oriented middleware platform for self-manageable DC microgrid applications utilizing semantic-enabled distributed energy resources

Dynamic and adaptable integration of Distributed Energy Resources (DERs) into novel power system assets, such as microgrids, is one of the key prerequisites for accelerated Smart Grid deployment. By using standardized network interfaces and semantic descriptions for remotely controllable DERs, it is possible to develop intelligent microgrid applications capable of dealing with dynamic loads and intermittent DER power production. IEC 61850 standard has been accepted as one of the prime movers of successful and interoperable Smart Grid communication and integration. Although primarily being applied to the substation automation, IEC 61850 now provides semantic definitions for DER devices allowing it to be applied to expert microgrid application development. The current IEC 61850 middleware definition cannot cope with certain Smart Grid requirements such as support for autonomous microgrid applications with DER plug-and-play capability. These issues could be solved by integrating the device-level Service Oriented Architecture (SOA) paradigm into IEC 61850 applications. Developing a device-level SOA middleware platform based on IEC 61850 principles could significantly facilitate standards-compliant DER integration and accelerate microgrid deployment. A new middleware platform for microgrid applications is proposed. It is based on integrating device-level SOA design principles into IEC 61850 applications in order to fulfil dynamic microgrid management requirements.