A Failure Probability Calculation Method for Power Equipment Based on Multi-Characteristic Parameters

Hang, Liu; Wang, Youyuan; Yang, Yi; Liao, Ruijin; Geng, Yujie; Zhou, Liwei

doi:10.3390/en10050704

Cited by 8 publications

(6 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Proposed theory of the determination of threshold value T T1 can be confirmed by theory [53]. In this case, the dissolved gasses in transformer oils in different transformers were studied for three years.…”

Section: Description Function/value Of Parametermentioning

confidence: 67%

Proposal of Physical-Statistical Model of Thermal Aging Respecting Threshold Value

Soucek¹,

Trnka

Hornak

2017

Energies

View full text Add to dashboard Cite

Abstract:The aging of electrical insulation material or a system is a main issue for designers of high-voltage (HV) machines. Precise determination of the life cycle of electrical insulation is one way of improving the efficiency of electrical machines involved in the production and transmission of electrical energy. Much effort has been devoted to preparing statistical or physical methods of Electrical Insulating System (EIS) life time estimation in the real operation of electrical machinery. The main aim of this paper is to introduce a new physical-statistical model of thermal aging respecting the threshold value. This model is based on thermal aging model and the main difference between this model and previously published models is taking into account the threshold value of degradation factor. The complete design of this model is presented in this paper, including functions defining the threshold value of the effect of the degradation factor depending on the temperature. Proposed model was verified by accelerated thermal aging test at selected temperatures (160, 170, 180 • C) and time intervals (0, 120, 240 h) on a commonly used transformer board. The breakdown voltage was set as an indicating parameter of the level of thermal aging and was measured according to standard IEC 60243-1. Collected data from these measurements were used for threshold value determination (431.23 K) and verification of proposed physical-statistical model of thermal aging respecting the threshold value.

show abstract

Section: Description Function/value Of Parametermentioning

confidence: 67%

Proposal of Physical-Statistical Model of Thermal Aging Respecting Threshold Value

Soucek¹,

Trnka

Hornak

2017

Energies

View full text Add to dashboard Cite

show abstract

“…The probabilistic approach based on the MC method has been implemented to evaluate the shielding failure flashover rate and back flashover rate of 230 kV overhead lines 26 . A quantitative method to failure probability evaluation has been described 27 . The method was implemented to determine the failure probability of two 230 kV transformers, which suggests the power equipment's failure trends.…”

Section: Introductionmentioning

confidence: 99%

Reliability assessment for DFIG ‐based WECS considering the impact of 3‐phase fault and lightning impulse voltage

Kumar

Sarita

Saket

et al. 2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary The assimilation of wind energy into the conventional grid brings several considerable challenges when uncertainties are considered. The uncertainties, including the occurrence of three‐phase fault and lightning fault, are considered to analyze the reliability and performance of the wind energy system. So, a study is a prerequisite for the power system, including wind farm (WF), voltage source converter (VSC), and lightning voltage and current phenomena. Therefore, the present work deals with the generation of lightning envelopes of impulse voltage and current and rectangular pulse current by considering the realistic equivalent circuit. The generated impulse voltage acting as a lightning fault is then implemented on the 3‐phase terminals of grid‐connected Doubly Fed Induction Generator (DFIG) based Wind Integrated Power System (WIPS), which includes six wind turbines (WT) of 1.5 MW each and 120 kV, 60 Hz grid. A 3‐phase short circuit fault is applied further to compare the output responses of the DFIG‐based WIPS. The system's behavior under both faults is observed by determining the controller gain values. The gains, including proportional (kp) and integral (ki) of a sixth‐order transfer function for Wind Turbine Generator (WTG), have been determined by using particle swarm optimization (PSO) algorithm. A reliability assessment of VSC considering DC voltage is done using the Monte‐Carlo (MC) method, considering the lightning impulse voltage (LIV) as a major cause of converter failure. It is found that the DFIG‐based WIPS achieves considerable responses under both types of faults by obtaining the optimal controller values. It has been also observed that the reduction in the number of failures that occurred in VSC during the lightning strike improves the system's reliability.

show abstract

“…In recent decades, numerous approaches to evaluate failure have been developed [6]. Generally, they can be classified into three categories [7]: (1) conventional methods based on system structure, (2) deterministic methods, and (3) probabilistic analysis methods.…”

Section: Introductionmentioning

confidence: 99%

Probability-Based Failure Evaluation for Power Measuring Equipment

et al. 2021

View full text Add to dashboard Cite

Accurate reliability and residual life analysis is paramount during the designing of reliability requirements and rotation of power measuring equipment (PME). However, the sample dataset of failure is usually sparse and contains inevitable pollution data, which has an adverse effect on the reliability analysis. To tackle this issue, this paper first applies nonlinear regression to fuse the failure rate and environmental features of PME collected from various locations. Then, a novel binary hierarchical Bayesian probability method is proposed to model the failure trend and identify outliers, in which the outlier identification structure is embedded into hierarchical Bayesian. Integrating binary hierarchical Bayesian and the bagging method, a binary hierarchical Bayesian with bagging (BHBB) framework is further introduced to improve predictive performance in a small sample dataset by resampling. Last, the influence of typical environmental features, failure rate, and reliability are obtained by the BHBB under the real sample dataset from multiple typical locations. Experiments show that our framework has superior performance and interpretability comparing with other typical data-based approaches.

show abstract

A Failure Probability Calculation Method for Power Equipment Based on Multi-Characteristic Parameters

Cited by 8 publications

References 14 publications

Proposal of Physical-Statistical Model of Thermal Aging Respecting Threshold Value

Proposal of Physical-Statistical Model of Thermal Aging Respecting Threshold Value

Reliability assessment for DFIG ‐based WECS considering the impact of 3‐phase fault and lightning impulse voltage

Probability-Based Failure Evaluation for Power Measuring Equipment

Contact Info

Product

Resources

About