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This contribution addresses the analysis of substation transformer failures in Europe. Based on a transformer population with more than 45.000 unit-years and 212 major failures over a period of 11 years (2000-2010) a failure rate of app. 0.5% was determined. The derived hazard curves show a constant probability of failure at all ages. Replacement s...
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... In 2016, the first 433kV transformer immersed in synthetic ester was commissioned, with a nominal power of 120MVA. Also, HVDC transformers immersed in ester were already successfully tested [4,5]. This paper will be structured in five sections: Firslty Section 1.1 is introductory to address the structure, motivation and contributions of the work. ...
... Authors show that the main causes of failure in transformers are of dielectric origin [5] and are, fundamentally, failures caused by transient phenomena, originating in passive elements of electrical networks such as capacitor banks that significantly alter the waveforms of dielectric stresses or active elements such as circuit breakers. This equipment has an ever-greater breaking capacity and is faster, which causes more severe switching overvoltages [6] [7] [8]. ...
Ester-based dielectric fluids have now been on the market for several decades, providing fire-safe and environmentally friendly alternatives to mineral oils, which have traditionally been used in transformers and other electrical equipment. This opens the door to innovation in power transformers. However, the use of esters-based dielectrics in power transformers is still very limited, especially for the higher voltage levels. The usage of these esters-based dielectrics in higher voltage power transformers is not yet consensual. this work present results with the use of natural esters in power distribution transformers. Tests carried out on mineral oil and natural ester oil found that the ester-based dielectric can withstand higher voltage thresholds for AC and Impulses tests, mainly within the specs of destructive tests, e.g., the natural ester was able to withstand a 185kV impulse without registering dielectric rupture while the natural oil registered a dielectric rupture with a 160kV impulse. Heating and mechanical tests demonstrated that ester-based dielectric oils for power transformers lead to a flow reduction between 16,8% and 18,2% in the cooling system that was design for mineral oils but they achieve a higher heat transfer coefficient, between 0,5% to 5% depending on the location of measurement.
... Statistical failure analysis of European substation transformers [9] reported that 5.2% of the total failures between 2000-2010 were due to improper maintenance, and 0.5% due to copper corrosion problems. It also reported that 12.8% of these failures caused fire and explosion accidents. ...
... Another international survey [10] over the period of 1996-2010 reported 964 transformer failures of 56 substations from 21 countries, where 13% of these failures led to negative impacts due to fire and explosion accidents. Such accidents can expose people to toxic chemical compounds, severe heat, smoke inhalation, and sound pressure [9,11]. The main consequences of transformer fires are the health and safety impacts on people from several tons of ejected oil containing toxic chemicals [12]. ...
The negative impacts of catastrophic fire and explosion accidents due to copper corrosion problems of oil-filled electrical transformers are still in the spotlight due to a lack of effective methods for early fault detection. To address this gap, a condition monitoring (CM) procedure that can detect such problems in the initial stage is proposed in this paper. The suggested CM procedure is based on identified measurable variables, which are the relevant by-products of the corrosion reaction, and utilizes an Early Fault Diagnosis (EFD) model to detect and solve the copper corrosion problems. The EFD model includes a fault trend chart that can track a fault progression during the useful life of transformers. The purpose of this paper is to verify and validate the effectiveness of the suggested CM procedure by an empirical study in a power plant. The result of applying this procedure was early detection of copper corrosion problems in two transformers with suspected copper corrosion propagation from a total of 84. The corrective action was adding an optimized amount of a passivator, an anticorrosion additive, to suppress the corrosion reaction at the correct time. The main conclusion of this study is the importance of early detection of transformer faults to avoid the negative impacts on societal, company, and individual levels.
... The transformer fires that contain several tons of mineral insulating oil can not only impact on the delivery of energy, but also on workplace health and the surrounding environment [6,7]. In [8], statistical data analysis of the failure rate of European substation transformers between 2000 and 2010 showed that around 9.5% of the total failures caused fire accidents and 3.3% caused explosion accidents. Another source of failure rates from 2015 [9] showed a significant increase in fire and explosion accidents in USA. ...
Fire and explosion accidents of oil-filled electrical transformers are leading to negative impacts, not only on the delivery of energy, but also on workplace health and safety as well as the surrounding environment. Such accidents are still being reported, regardless of applying the regular maintenance strategy in the power plants. The purpose of this paper is to integrate a sustainability perspective into the maintenance strategy. The problem addressed is: how can we approach the relevant cost-effective sustainable maintenance for oil-filled electrical transformers? For this purpose, an empirical study in a power plant in Kuwait was introduced. The first stage was to carry out a sustainability assessment using the ABCD procedure. In this procedure, gaps to approach sustainability were identified and actions prioritized to close these gaps were demonstrated. Applying this procedure yielded an early fault diagnosis (EFD) model for achieving cost-effective sustainable maintenance using a fault trend chart based on a novel numerical method. Implementing this model resulted in an extension of the lifetime of transformers with suspected failure propagation, leading to a deferral of the replacement investment costs. The principal conclusion of this paper is the importance of viewing the maintenance strategy of transformers from a strategic sustainability perspective, in order to approach relevant cost-effective sustainable maintenance.
... One clear example is the transformer -the most expensive equipment in a substation and thus expected to be safeguarded against the abnormal conditions in the power network. Despite low failure rates in the range of <1% for the power transformers [1]- [3], the criticality of their service becomes more demanding due to the recent change in the consumer dynamics. The availability and reliability need of the transformers are just getting higher, due to ever demanding network challenges, volatile renewable penetration, and multi-terminal connections. ...
The paper presents the modern-day challenges of the utilities in dealing with several monitoring solutions available in the market without a clear direction of how to interpret this data coming out of different constituent assets. A unified framework is thus proposed, where the operational behavior, performance, life cycle and usability of individual assets are monitored and presented in a utility substation. Such a framework is built on a condition monitoring platform that helps assessing the assets on a continuous basis, defines the interdependencies amongst different subsystems and pre-sent clear actionable directions to different stakeholders of the substation, namely- the asset owner, operator, mainte-nance and service personnel. The holistic solution encompasses the entire signal chain from sensors to system informat-ics, built on a unified data model platform that covers generic asset properties, independent of manufacturers and communication interface of sensors. The anomaly detection is handled by the performance models of various assets of an entire substation, which are compared for its current value against its historical baseline, thereby presenting a uniquely optimized and cost-effective maintenance strategy.
... The formation of CSD can lead to many undesirable consequences such as reducing the electrical resistivity of insulating paper, increasing dielectric losses, and formation of electrical discharges due to migration of semi-conductive Cu 2 S through the layers of insulating paper [4,5]. A statistical failure analysis of a data set collected from 32 power stations from Germany, Austria, Swiss, France, United Kingdom, Spain, Denmark and Netherlands over a period of 11 years from 2000-2010 displayed that 0.5% of the total transformer failures were due to copper corrosion fault [6]. An example of unplanned failure was reported in 2017 when melting of HV windings occurred due to arcing phenomenon and damage of its insulating paper of a transformer with a rating of 20 MVA in a power station at the Saudi Aramco Company. ...
The purpose of this study is to determine whether the currently applied condition monitoring (CM) techniques are sufficient and effective for early detection of copper corrosion fault in transformers and to establish a more relevant CM technique for early detection of such fault. In this study, experimental work is carried out by applying appropriate methods on different commercial insulating mineral oils for the detection and identification of additional related by-products of copper corrosion process, if any. The major finding of this experimental investigation includes identification of additional by-products, which could be useful to establish a more effective CM technique. Furthermore, the role of sulphur compounds in copper corrosion fault is considered, and a relevant reaction mechanism of formation CSD is developed based on the findings of the related by-products. It is concluded that, the application of a relevant CM technique is necessary for establishing a cost-effective condition based maintenance (CBM) to minimize the economic losses, hazardous effects on human life and the environment.
... Also, monitoring usually relies on condition assessment models based on data obtained from specialized sensors for gas in oil, temperature, dielectric losses, partial discharges, among others. Furthermore, because the failure rate of power transformers is about one percent per year [2][3][4], most transformers are monitored manually by taking periodic offline measurements. The infrequency of these measurements heavily restricts the ability of the operators to react quickly to faults, or to correlate a reading to a system event. ...
... The on-load tap changers are the only transformer parts that utilize mechanical movement and therefore account for approximately one-third of transformer failures [2][3][4]. ...
ABB’s new field-tested model-based monitoring system is integrated within
standard substation equipment and presented in MicroSCADA Pro. This unique
approach allows an asset’s performance to be evaluated while in actual service as
well as imminent faults to be detected.
... For the component layer, their weights are determined based on failure statistics of transformer components as shown in Fig.3. Fig.3 Statistics of failure compoents of power transformers [36,37]. ...
A probabilistic framework for transformer health condition assessment is proposed based on Bayesian information fusion. The proposed framework can integrate different kind of transformer condition monitoring data as well as failure statistics. By making use of these data and information, an inference model is constructed using the Bayesian belief network and its parameters like the prior/condition probabilities are also determined with the availability of the obtained data, accordingly. In the model, the condition probability is taken as significance of the condition data on corresponding component and is decided by combing both the principal component analysis and expert's experience, while the contribution of independent variables to dependent ones is quantified with a score-probability transform. The constructed model then derives a probabilistic health index to take into account the uncertainties in data acquisition, interpretation and modeling. Numeric experiments are carried out using several field collected datasets. The results demonstrate the applicability of the proposed model in transformer condition assessment.
... Long duration PD activity usually results in some degradation of dielectrics and may cause some serious apparatus faults and even catastrophic events. A significant share of all electric power distribution system failures are directly or indirectly associated with the PD (Borucki, 2012;Chaidee et al., 2007;Vahidi, Tenbohlen, 2014). Hence, adequately early detection and recognition of any insulation faults of the primary apparatus such as generators or power transformers, not only allows to provide a reliable electric power delivery but also may reduce some potential costs related to uncontrolled failures of the infrastructure or overhaul process (Borucki et al., 2017;Wotzka et al., 2012). ...
An alternative method for analysis of acoustic emission (AE) signals generated by partial discharges (PD), based on a correlation between voltage phase run and AE pulses, so called phase resolved PD pattern (PRPD), is presented in the paper. PRPD pattern is a well-known analysis tool commonly used in such PD diagnostic methods as conventional electrical and UHF ones. Moreover, it yields various signal analysis abilities and allows a direct correlation indication between measurement results achieved using different methods. An original PRPD measurement methodology applied for AE method as well as some exemplary measurement results and further data analysis capabilities are presented in the paper. Also a comparative analysis of PRPD patterns achieved using various measurement methods and different PD source configurations have been investigated. All presented experiments were done under laboratory conditions using PD model sources immersed in the insulation oil. The main purpose of the presented research is to indicate an all-embracing analytical tool that yields an ability to direct comparison (qualitative as well as quantitative) of the AE measurement results with other commonly applied PD measurement methods. The presented results give a solid fundamental for further research work concerning a direct correlation method for AE and other described in the paper diagnostic techniques, mainly in order to continue PD phenomena analysis and assessment in real life high voltage apparatus insulation systems under normal onsite operation conditions.
... From a data collection between 1960 and 1980, of 32 utilities from Germany, Austria, Swiss, France, United Kingdom, Spain, Denmark and Netherlands, it was reported that an average of 0.005 failure per years for transformer up to 500 kV [21] with a repair time between 173.2 and 308.9 hours [13,22]. ...
... Later, the eigenvalues and eigenvectors of are as follows respectively: (19) (20) Knowing that at the component is in operational state , then (16) can written as: (21) Solving for and : (22) Finally, the solution of a Markov chain for a repairable component that follows an exponential distribution function with two operational states is: ...
This paper presents a reliability model of a Static Var Compensator (SVC) using an innovative algorithm based on sequential Monte Carlo simulation and Markov chains. The method employs the equivalent circuit of a SVC and takes the failure rate and repair time of each component as input in order to compute the failure rate and repair time of the whole SVC system. The specific contribution of this investigation is that it presents a mathematical pathway to model operating conditions of a SVC subject to individual operating states of its components, resulting in a comprehensive reliability model.
... where m is the number of parent nodes and ∑ ߱ ൌ 1. [36][37][38]. Convert the condition scores of the child nodes to probabilities corresponding to condition states using a score-probability transform: ...
This study proposes a Bayesian information fusion approach for determining the probabilistic health index of power transformer. The proposed approach integrates a variety of data obtained from transformer measurements, maintenance records, and failure statistics. By making use of these data, an inference model is constructed using Bayesian belief network (BBN). In the inference model, the significance of each individual measurement on the corresponding component in the BBN is decided by both principal component analysis and expert's experience, and subsequently quantified with a score-probability transform. Finally, the inference model is used to derive a probabilistic health index. Case studies are provided to demonstrate the applicability of the proposed approach for evaluating transformer condition.
