Transformation Failure: How the World Changed, but Germany Did Not

The work is devoted to the identification of the law of distribution according to statistical data of failure of power transformers of 6–10 kV due to damage to their windings for a three-year period: from 2018 to 2020. According to statistical data, it has been established that there is a tendency to reduce damage to power transformers by almost two times. But the number of these failures still remains quite large. The main cause of power transformers failure is damage to their windings, which accounts for 82.17 % of other causes. Therefore, the statistics that characterize the failure of power transformers due to damage to the windings were taken for research. It was established that in 2018 and 2019, the largest number of damages to power transformer windings occurred in April—July with a peak in June, and in 2020, the maximum damages were recorded in November and December. The prerequisite for building mathematical models for predicting the failure of power transformers due to the damage to the windings in order to ensure the necessary number of spare parts for their quick recovery is the study of the nature of the failure of transformers. The following methods were used to solve the tasks: passive experiment — to collect information about the failure of power transformers; statistical analysis — to build an empirical law of distribution. After analyzing the view of the histogram of the variation series of the sample of failure of power transformers due to damage to the windings, a hypothesis was put forward about the logarithmic normal distribution law of the failure of transformers due to damage to the windings. Pearson's c2-test was used to check it. As a result of the study, the proposed hypothesis was confirmed. Using Student's tables and the c2-distribution table with a confidence probability of g2 = 0.98, confidence intervals were determined for statistical estimates of the mean value, variance and root mean square deviation, which characterize the failure of power transformers due to damage to the windings. With further research, it will be possible to build mathematical models for predicting the failure of power transformers due to damage to the windings.

Failure of physiologic transformation of spiral arteries, endothelial and trophoblast cell activation, and acute atherosis in the basal plate of the placenta

In agriculture, single-transformer consumer substations are widely used. Failure of a transformer in such a substation adversely affects the reliability of power supply to agricultural consumers. The most common reason for the failure of consumer transformers (over 50%) is turn-to-turn short circuits in their windings. Therefore, timely diagnostics of turn-to-turn faults in the windings of such transformers is an urgent task. In this case, it is necessary to take into account the specific conditions of rural electrical networks. It is recognized as permissible to carry out diagnostics at idle running of the transformer. Designed with assumptions in mind, the diagnostic device is simple and easy to use. The operation of the device was investigated on an electronic model using the Matlab software package integrated with the design and programming environment based on Simulink models. As a result of research, it was found that the device is efficient and efficient.

In the field of diagnosis of mechanical failures in power transformer’s active part, i.e., windings, leads and the core, the technique of Frequency Response Analysis (FRA) has been recently approved as the main application tool. Mechanical failures in transformer windings reflect changes on measured terminal frequency responses normally in medium frequency range, from several to hundreds of kHz, which is in fact not easy to interpret for diagnosis. The authors proposed a new method based on simulation of a lumped three-phase equivalent circuit of power transformers to interpret frequency responses effectively, but only within low frequency range. This limitation is due to the fact that, the circuit cannot reflect well physical phenomena at medium and higher frequencies. To improve the FRA performance of the proposed method at medium frequencies for transformer failure diagnosis purpose, the paper introduces an investigation on a distributed three-phase equivalent circuit of a 200 kVA 10.4/0.46 kV Yy6 distribution transformer. Result of the investigation is a simplified procedure in determination of electrical parameters associated with the distributed circuit for better simulation based FRA interpretation at medium frequencies.

The paper proposes a probabilistic methodology to include end-of-life failure of power transformers into cascading failure simulation. To this end, the paper has adopted Arrhenius-Weibull distribution to characterise end-of-life failure of transformers under different loading conditions. In order to simulate different system states, Non-sequential Monte Carlo simulation method has been used. The simulation of cascading failure of transformer is achieved by comparing the unavailability of individual transformers under different loading condition to a random number. The method is applied to a realistic transmission network containing 154 transformers. The method can be used to feed into decision-making process to replace ageing transformers.

Electricity places an important role in the modern world. Transformers are one of the key piece of equipment in modern power systems. Because of various reasons, the failure of transformers can happen unexpectedly, resulting in a power supply outage to the end-users. Distributed generation (DG) allows the bidirectional power flow in the system with higher integration of distributed renewable energy sources (RES), especially solar photovoltaics. It is possible to install the solar PV system in the range between 10% and 120% of the distribution transformer rating under the DG. Failures of distribution transformers affect the power supply to end-users and the DG integration into the distribution grid. Consistent monitoring of distribution transformers by means of physical inspection is one of the major concerns of distribution companies/end-users to prevent unexpected failure. Currently, distribution transformer parameters like state of working (i.e., online/offline) is monitored, and other parameters like oil level, oil temperatures, winding temperature, etc., are not monitored from the remote end. This chapter discusses the monitoring of health conditions of a laboratory prototype 250-VA single phase oil-immersed transformer using Internet of Things (IoT) technology to achieve the conventional distribution systems toward a smart distribution system.

In this study, the failures in Transformer Centers in Mersin Province Erdemli District have been investigated. The causes of the failures have been discussed. It is aimed to create a method for the reasons of possible failures of power transformer. The data have been collected by investigating the faults occurring at the Erdemli Substations. The failure statistics of the 200 power transformer failures that occurred between 2003 and 2019 in the Erdemli district of Mersin province have been examined. Examples of different power transformer failures have been given in fault analysis. The reasons of power transformer failures and the precautions to be taken have been explained.

Summary form only given. Utilities have used for years indicators such as loading, hot spot and top oil temperatures to determine ratings and health of substation transformers where the required data is readily available. However, the same level of data is not available for low voltage distribution transformers and loading prediction is difficult. Overload failures of distribution transformers, while not particularly significant to the utility network, can strain maintenance budgets, drain resources and sour customer relationships. Typically utilities use a transformer load management program that aggregates customer usage, estimates a peak and aggregates the peaks to a transformer for determining transformer load. Transformer replacement programs will then use loading as an indicator of replacement priority. However, most utilities have many more overloaded distribution transformers than they can economically replace, and predicting transformer failure is a very inexact science. One cause among several is poor data quality. Yet estimating loading requires good customer to transformer connectivity data and validated usage data at a minimum. We presented here one utility's experience with a continuous program of proactive distribution transformer replacements based on continuous calculation of loading from end use data. This program was the result of an alarming rate of transformer failures experience during several recent hot summers. Byproducts of this program were the recognition that loading alone is not a good indicator of potential outage, and that transformer age appears to have little or no correlation with transformer outages. Three consecutive years of locating and proactively replacing transformers that are likely to cause a transformer outage were presented including: data sources; methods; analysis; results to date; issues; conclusions to date. Calculated loading on actually failed distribution transformers was compared with loading of a large control group of not, or not-yet failed, distribution transformers, showing a clear correlation of calculated loading with probability of transformer failure.

ResumenEste artículo presenta una revisión general del marco conceptual relacionado con la gestión activos para transformadores de potencia y la evaluación del riesgo asociado a sus fallas.El índice de riesgo es una herramienta esencial para realizar la gestión de activos, especialmente porque apoya al gestor en el proceso de toma de decisiones.El índice de riesgo está compuesto por dos factores: i) el factor de consecuencia, que valora los impactos que se podrían presentar en caso de falla del equipo; y ii) la probabilidad de falla que se determina a partir de los resultados de las pruebas de funcionamiento, de la historia de la operación y del historial de fallas, entre otros aspectos.Se presentan aspectos generales relacionados con la gestión de activos según las normas internacionales, para luego tratar con mayor detalle aspectos específicos relacionados con la evaluación del índice de riesgo del transformador, encontrados en la literatura.

With its potentially disruptive nature, the smart grid can be viewed from both a transformational and an innovation systems perspective. Synthesising these, a research approach is adopted in which a Technological Innovation System (TIS) analysis is combined with a transformational perspective to identify a broader range of success and failure factors. This study analyses smart grid innovation system development. The main research question is: What systemic and transformational failures are identified in the development of smart grid innovation in the Netherlands from 2001 to 2021 by combining TIS and a transformational perspective? The question is answered by mapping the events to TIS functions and identifying both ‘systemic failures’ and ‘transformational failures’. Transformational failures are linked to events outside the smart grid TIS that work against the alignment and harmonising of activities within the TIS. Results show that the smart grid innovation system experienced three periods and that it suffers from various structural and transformational failures. TIS functions like knowledge diffusion, and the creation of legitimacy were only fulfilled to a limited extent. Consequently, smart grid innovation is currently still not considered a mainstream technology in the energy transition, and there is little attention to the role of end-users. The study ends with suggestions for future research, including the suitability of the research approach for other contexts and when applied to other energy system innovations.

Failure of physiologic transformation of the spiral arteries in the placental bed in preterm premature rupture of membranes

Failure of physiologic transformation of the spiral arteries in patients with preterm labor and intact membranes

Background and ObjectiveFetal growth during pregnancy is directly related to the transformation of spiral arteries of the placental bed into uteroplacental arteries (physiologic conduits containing endothelial cells and trophoblastic cells embedded in fibrinoid deposits that replace the smooth muscle cell layer). Failure of physiologic transformation of the spiral arteries leads to development of uteroplacental atherosis (UA), a lesion similar to native atherosclerosis (native atherosis). Our objective was to evaluate UA cell composition, variations in cell composition among obstetrical syndromes, and evidence of activation and inflammation in the lesions.MethodsBasal plate samples (5.6 ± 0.9/placenta) from placentas with (n=134) and without (n=134) UA were studied histo and immunohistochemically for different cell types. Statistical comparisons for UA and no UA groups were performed with Fisher’s exact, Kruskal‐Wallis, Wilcoxon Rank Sum test, and analysis of variance (ANOVA); and a Bonferroni‐adjusted level of significance of <0.025 was used.ResultsAll 134 placentas with UA had failure of spiral artery physiologic transformation (total and/or partial); 125 (93.3%) being from complicated pregnancies, and 9 (6.7%) from normal pregnancies. UA was found in small for gestational age (n=31), preeclampsia (n=73), preterm labor (n=8), preterm pre‐labor rupture of membranes (n=9), fetal death (n=4) and adequate for gestational age (n=9) placentas. UA had 52.4% smooth muscle cells, 29.4% foam cells, 30.6% oil red O‐positive cells, 16.2% endothelial cells and 0% intra‐arterial trophoblast cells; failure of physiologic transformation had 82.2% smooth muscle cells, 17.0% endothelial cells, 0% foam cells, 0% oil red O‐positive cells and 0% intra‐arterial trophoblast cells; physiologic transformation had 81.0% intra‐arterial trophoblast cells, 17.6% endothelial cells, 0% foam cells, 0% oil red O‐positive cells and only 0.4% smooth muscle cells. UA lesions were 100% fibrin‐positive and had 31.5% CD68‐ and 30.8% CD36‐positive macrophages within the fibrin matrix; while arteries with failure of physiologic transformation and with physiologic transformation had no fibrin and less than 1% CD68‐ and CD36‐positive macrophages. UA had 48.0–48.9% ICAM‐1‐, HLA‐DR‐ and NFκB‐positive cells (endothelium and macrophages), 17.4% being CRP‐reactive (predominantly proinflammatory tissue‐associated monomeric CRP); failure of physiologic transformation had 13.4–13.8% ICAM‐1‐ and HLA‐DR‐positive cells (endothelium), 7.6% of them were NFκB‐positive but none CRP‐reactive; no activation and inflammation markers were found in physiologic transformation.ConclusionsWe conclude that UA cell composition is the same in all obstetrical syndromes and in normal pregnancies; and UA lesions have cell activation and inflammation and oil red O‐positive CD68‐reactive macrophages containing the scavenger receptor CD36, sharing similar characteristics with native atherosclerosis.

There is an increasing consensus among policy makers and academics that Mission-oriented Innovation Policy is needed to tackle the grand societal challenges of our time. However, there is little experience in actually carrying out this new type of policy. In this light, we investigate Sweden's ambitious traffic safety policy known as 'Vision Zero'. We consider this policy as a mission-oriented innovation policy towards a societal challenge, as it started from the articulation of a bold, societal goal (zero traffic deaths), fostered multiple types of innovations (technological infrastructural, regulatory), and involved a variety of actors (public, private and professional organizations). We explain what the Vision Zero policy entails, how stakeholders dealt with 'transformational failures', and what made the policy a success. We end with lessons for the development of new mission-oriented innovation policies to address societal challenges.

Switching transients associated with circuit breakers have been observed for many years. Recently this phenomenon has been attributed to a significant number of transformer failures involving primary circuit breaker switching. These transformer failures had common contributing factors such as 1) primary vacuum or SF-6 breaker, 2) short cable or bus connection to transformer, and 3) application involving dry-type or cast coil transformers and some liquid filled. This paper will review these recent transformer failures due to primary circuit breaker switching transients to show the severity of damage caused by the voltage surge and discuss the common contributing factors. Next, switching transient simulations in the electromagnetic transients program (EMTP) will give case studies which illustrate how breaker characteristics of current chopping and re-strike combine with critical circuit characteristics to cause transformer failure. Design and installation considerations will be addressed, especially the challenges of retrofitting a snubber to an existing facility with limited space. Finally, several techniques and equipment that have proven to successfully mitigate the breaker switching transients will be presented including surge arresters, surge capacitors, snubbers and these in combination.