scholarly journals Risk Assessment Algorithm for Power Transformer Fleets Based on Condition and Strategic Importance

Algorithms ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 319
Author(s):  
Diego A. Zaldivar ◽  
Andres A. Romero ◽  
Sergio R. Rivera
Keyword(s):  
Power Transformer ◽  
Critical Role ◽  
Technical Condition ◽  
Electric Power System ◽  
Assessment Model ◽  
Fuzzy Logic Algorithm ◽  
Inherent Risk ◽  
Importance Index ◽  
Utmost Care ◽  
System Power

In every electric power system, power transformers (PT) play a critical role. Under ideal circumstances, PT should receive the utmost care to maintain the highest operative condition during their lifetime. Through the years, different approaches have been developed to assess the condition and the inherent risk during the operation of PT. However, most proposed methodologies tend to analyze PT as individuals and not as a fleet. A fleet assessment helps the asset manager make sound decisions regarding the maintenance scheduling for groups of PT with similar conditions. This paper proposes a new methodology to assess the risk of PT fleets, considering the technical condition and the strategic importance of the units. First, the state of the units was evaluated using a health index (HI) with a fuzzy logic algorithm. Then, the strategic importance of each unit was assessed using a weighting technique to obtain the importance index (II). Finally, the analyzed units with similar HI and II were arranged into a set of clusters using the k-means clustering technique. A fleet of 19 PTs was used to validate the proposed method. The obtained results are also provided to demonstrate the viability and feasibility of the assessment model.

scholarly journals Predicting the technical condition of the power transformer using fuzzy logic and dissolved gas analysis method

2022 ◽  
Vol 12 (2) ◽  
pp. 1139
Author(s):  
Vladimir Mikhailovich Levin ◽  
Ammar Abdulazez Yahya ◽  
Diana A. Boyarova
Keyword(s):  
Fuzzy Logic ◽  
High Efficiency ◽  
Power Transformer ◽  
Thermal Power ◽  
Technical Condition ◽  
Electric Power System ◽  
Diagnostic Methods ◽  
Digital Model ◽  
Vibration Monitoring ◽  
Ratio Method

Power transformers are one of the most important and complex parts of an electric power system. Maintenance is performed for this responsible part based on the technical condition of the transformer using a predictive approach. The technical condition of the power transformer can be diagnosed using a range of different diagnostic methods, for example, analysis of dissolved gases (DGA), partial discharge monitoring, vibration monitoring, and moisture monitoring. In this paper, the authors present a digital model for predicting the technical condition of a power transformer and determining the type of defect and its cause in the event of defect detection. The predictive digital model is developed using the programming environment in LabVIEW and is based on the fuzzy logic approach to the DGA method, interpreted by the key gas method and the Dornenburg ratio method. The developed digital model is verified on a set of 110 kV and 220 kV transformers of one of the sections of the distribution network and thermal power plant in the Russian Federation. The results obtained showed its high efficiency in predicting faults and the possibility of using it as an effective computing tool to facilitate the work of the operating personnel of power enterprises.

Power Transformer Fault Diagnosis Based on Vibration Correlation Analysis

2014 ◽  
Author(s):  
Kaixing Hong ◽  
Hai Huang
Keyword(s):  
Fault Diagnosis ◽  
Correlation Analysis ◽  
Fundamental Frequency ◽  
Vibration Analysis ◽  
Laboratory Tests ◽  
Power Transformer ◽  
Assessment Model ◽  
Vibration Method ◽  
Proposed Model ◽  
Transformer Fault

In this paper, a condition assessment model using vibration method is presented to diagnose winding structure conditions. The principle of the model is based on the vibration correlation. In the model, the fundamental frequency vibration analysis is used to separate the winding vibration from the tank vibration. Then, a health parameter is proposed through the vibration correlation analysis. During the laboratory tests, the model is validated on a test transformer, and manmade deformations are provoked in a special winding to compare the vibrations under different conditions. The results show that the proposed model has the ability to assess winding conditions.

scholarly journals Identification and Assessment of Uncertainty Factors that Influence the Transaction Cost in Public Sector Construction Projects in Pakistan

Buildings ◽  
2018 ◽  
Vol 8 (11) ◽  
pp. 157 ◽  
Author(s):  
Zaigham Ali ◽  
Fangwei Zhu ◽  
Shahid Hussain
Keyword(s):  
Transaction Cost ◽  
Construction Projects ◽  
Critical Role ◽  
Environmental Groups ◽  
Uncertainty Factors ◽  
Competitive Tendering ◽  
Importance Index ◽  
Force Majeure ◽  
Internal Sources ◽  
The Impact

Like other kinds of projects, construction projects are exposed to uncertainty, which plays a critical role in determining the transaction cost (TC). This study explores the uncertainty factors that are associated with construction projects that substantially influence the TC. To obtain the opinions of construction professionals, a survey questionnaire was developed after identifying 30 relevant causes of uncertainty from the literature. A survey of 216 professionals was conducted in Pakistan, and the relative importance index (RII) was used to prioritize the significant uncertainty factors that escalate the TC. Based on the responses from various construction professionals, this study determined that the most significant uncertainty factors that influence TC are: competitive tendering, incomplete design and specifications, late payments, conflict management, delayed possession of sites, force majeure, and work acceleration. This study also compared and analyzed the views of project managers and consultants and found that uncertainty from internal sources has a more significant influence on TC than that from external sources. The political and environmental groups do not contribute much escalating the TC. However, uncertainties that arise from the commercial, project site, and technical groups are more of an influence on TC. This research helps practitioners and professionals to adopt integrative systems in most uncertain situations proactively to find opportunities in volatile markets to reduce the impact of uncertainty on the total project cost.

scholarly journals Forecast model for estimating the service life of a diagnosed object based on the Neyman–Pearson method

2018 ◽  
Vol 216 ◽  
pp. 03011
Author(s):  
Sergey Barsukov ◽  
Sergey Pakhomov
Keyword(s):  
Service Life ◽  
Power Transformer ◽  
Impurity Content ◽  
Forecast Model ◽  
Threshold Value ◽  
Technical Condition ◽  
Transformer Oil ◽  
Average Risk ◽  
Iron Impurity ◽  
Object Based

The paper is aimed at developing a forecast model for estimating the service life of a diagnosed object based on the Neyman–Pearson method. It presents a procedure for selecting necessary and sufficient number of diagnostic indicators using the forecast model. The technique has been tested on the basis of a power transformer with a liquid dielectric. A condition-based operation strategy has been proposed for the transformer. According to this strategy, the iron impurity content in the dielectric liquid (oil) of the transformer should be measured every year of operation. Based on the forecast model, it is possible to calculate the variation of average risk (R) and a threshold value of iron impurity content in the transformer oil (k0) for each year of operation. Using these parameters, a reliable forecast model can be constructed to estimate the remaining service life of the transformer. The obtained relationships make it possible to identify a scientifically grounded stage in the service life of a diagnosed object, at which the number of measurable diagnostic indicators (indicators that are necessary for assessing the real technical condition of equipment) can be minimized.

scholarly journals Study on Seismic Reliability of UHVDC Transmission Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Kun Yao ◽  
Jiang Qian
Keyword(s):  
Electrical Equipment ◽  
Transmission System ◽  
Electric Power System ◽  
Assessment Model ◽  
Economic Losses ◽  
Seismic Reliability ◽  
High Voltage Direct Current ◽  
Design Requirements ◽  
State Enumeration

Electric power system is critical to maintain the welfare of the general public with impact on economic losses and other cascading. In this paper, the seismic reliability of the ultra-high-voltage direct current (UHVDC) transmission system was evaluated from a perspective of the subsystem fault logic. An assessment model of system seismic reliability was proposed based on the state enumeration method. A case study was presented by taking a typical 800 kV UHVDC transmission system as the example. The finite element models of major components in the UHVDC transmission system were established to evaluate their seismic reliability. The results reveal that though the seismic reliability of major components seems satisfactory overall, the UHVDC transmission system may still suffer from seismic hazards to a certain degree due to the complexity of the full system. This calls for a further enhancement in seismic design requirements of the electrical equipment.

scholarly journals Study of Transformer Lifetime Due to Loading Process on 20 KV Distribution Line

2018 ◽  
Vol 2 (2) ◽  
pp. 25
Author(s):  
A.A.N. Amrita ◽  
W.G. Ariastina ◽  
I.B.G. Manuaba
Keyword(s):  
Residual Life ◽  
Power Transformer ◽  
Short Circuit ◽  
Life Time ◽  
Electric Power System ◽  
Transformer Oil ◽  
Maximum Efficiency ◽  
Iron Core ◽  
Distribution Transformers ◽  
Work Area

Power transformer is very important in electric power system due to its function to raise or lower the voltage according to its designation. On the power side, the power transformer serves to raise voltage to be transmitted to the transmission line. On the transmission side, the power transformer serves to distribute the voltage between the main substations or down to the distribution voltage. On the distribution side, the stresses are channeled to large customers or lowered to serve small and medium customers. As the power transformer is so importance, it is necessary to protect against disturbance, as well as routine and periodic maintenance, so that the power transformer can operate in accordance with the planned time. Some factors that affect the duration of the power transformer is the ambient temperature, transformer oil temperature, and the pattern of load. Load that exceeds the maximum efficiency of the transformer which is 80% of its capacity will cause an increase in transformer oil temperature. Transformer oil, other than as a cooling medium also serves as an insulator. Increasing the temperature of transformer oil will affect its ability as an isolator that is to isolate the parts that are held in the transformer, such as iron core and the coils. If this is prolonged and not handled properly, it will lead to failure / breakdown of insulation resulting in short circuit between parts so that the power transformer will be damaged. PLN data indicates that the power transformer is still burdened exceeding maximum efficiency especially operating in the work area of PLN South Bali Area. The results of this study, on distribution transformers with different loads, in DS 137, DS 263 and DS 363, show that DS 363 transformer with loading above 80% has the shortest residual life time compared to DS 263 and DS 137 which loading less than 80%.

Electric Discharges Localization for Substation Fault Monitoring Using Two Elements Sensor

2020 ◽  
Vol 17 (2) ◽  
pp. 1009-1013
Author(s):  
Lorothy Morrison Buah Singkang ◽  
Kismet Anak Hong Ping ◽  
P. R. P. Hoole
Keyword(s):  
Fault Detection ◽  
Power Transformer ◽  
Circuit Breaker ◽  
Electric Power System ◽  
Array Antenna ◽  
Electric Discharges ◽  
Localization Accuracy ◽  
Fault Monitoring ◽  
Electromagnetic Signals ◽  
Element Array

A substation is an important unit in the electric power system. Thus, the monitoring process must be carried out effectively to detect the operation status of the equipment, and pre-fault threat detection is necessary for safe operation. Many methods and intelligent techniques have been developed to provide a better way of fault detection. However, power authorities unwilling to adopt those techniques due to the high cost of installation and more sensors required to improve localization accuracy. Therefore, to reduce cost and increase the speed of detection, this paper presents a 2-element array antenna acted like a sensor to detect and localize the electric discharges from abnormal radiated electromagnetic activities in the substation based on the direction of arriving angle (DOA) received by the array antenna. Software implemented signal processor was used to obtain the radiation patterns for different value of DOA relative to the normalized Array Factor (AFN). This 2-element Sensor was proven to eliminate the undesired signals (such as electromagnetic signals from outside the substation) and maximize the signals in the direction of the desired signal by detecting the DOA of abnormal radiation from power apparatus (such as power transformer or circuit breaker bushings) inside the substation. It was proven that this cohesive unit was able to perform the two tasks by simultaneously eliminating or maximizing signals with very small (such as 0.0873 radians) angle difference between external radiation and radiation from apparatus inside the substation. By performing these tasks, the 2-element Sensor was promisingly able to detect and localize the abnormal electrical activities such as Electric Corona and Electric Arcs discharges that may occur in any substation based on the identified DOA from the power apparatus within the substation as a preventative approach for substation breakdown and to improve the efficiency and the performance of fault detection technique in future Substation Fault Monitoring.

Study on Risk Assessment of Power Transformer Based on Life Cycle Quality Information

2014 ◽  
Vol 615 ◽  
pp. 88-92
Author(s):  
Tian Shu Bi ◽  
Jin Meng Chen
Keyword(s):  
Risk Assessment ◽  
Manufacturing Process ◽  
Large Scale ◽  
Control Method ◽  
Comprehensive Evaluation ◽  
Power Transformer ◽  
Fault Tree Analysis ◽  
Assessment Model ◽  
Fuzzy Synthetic Evaluation ◽  
Manufacture Process

It has significant impact on the safe operation of the power grid for large scale power transformer. The technique is complex, and the manufacture process is long. The users always take the manufacturing supervision on spot as the quality control method. The quality is determined during the manufacturing process. The quality defects may cause serious safe problems. It has important significance to strengthen the risk assessment and prevention. The quality defects of power transformer are classified based on the fault tree analysis theory. The quality defects of power transformer from the manufacturing supervision of State Grid Corporation of China (SGCC) in 2012 are analyzed as examples. The manufacturing process has multiple layers and factors. The index system for comprehensive evaluation of transformer is put forward. A risk assessment model for power transformer based on fuzzy synthetic evaluation is built. The example shows that the method can estimate the risk effectively. It can provide feasible decision basis for the risk management and maintenance.

scholarly journals Assessment of the current technical condition of electrical equipment based on an artificial neural network

2021 ◽  
Vol 2131 (5) ◽  
pp. 052049
Author(s):  
V Z Manusov ◽  
M R Otuzbaev ◽  
M A Scherbinina ◽  
G V Ivanov
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
High Efficiency ◽  
Power Transformer ◽  
Reliability And Validity ◽  
Electrical Equipment ◽  
Technical Condition ◽  
Computer Assisted ◽  
Technical Diagnostics ◽  
Artificial Neural

Abstract Assessment of the current technical condition is an important task, so the state of electrical equipment depends on its further operability. Thanks to modern computing devices, it is possible to implement actively artificial intelligence and computer-assisted learning methods that allow achieving high efficiency in data processing. A study was conducted and an algorithm for diagnosing the technical condition based on an artificial neural network was developed. A model based on a multilayer perceptron is proposed, which allows evaluating the technical condition of a high-voltage power transformer. The result of the technical diagnostics of the model is the assignment of the condition to one of the five classes, proposed by the guidelines presented by the International Council on Large Electrical Systems. The methodology is presented on the example of a 250 MVA transformer with a certain defect history, which allowed us to show the reliability and validity of the obtained results. It is shown that the use of the proposed model makes it possible to achieve accuracy in determining the technical condition of 0.95. The introduction of this model into an automated monitoring and diagnostics system will allow assessing the technical condition of electrical equipment in real time with sufficient accuracy.

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