Predicting Reliability Improvements

Williams, Charles; McCarthy, Christopher; Cook, C.J.

doi:10.1109/mpe.2007.915185

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…The approaches are based on a reliabilitynetwork-equivalent model that takes into account the effects of feeder layout, the location of recloser, and the application of distributed generators. In paper [18], authors use only SAIFI reliability index in a method to predict reliability improvements, that is, a method for the determination of the quantity, type, and placement of protective devices. Authors in paper [19] also suggested solving the same problem relying on the SAIFI index but by application of a binary programming optimization with the usage of engineering heuristics algorithm in order to reduce the duration of calculation.…”

Section: Allocation Problem Of Sectionalizing Units Within Electrical...mentioning

confidence: 99%

Allocation of 0.4 kV PTL Sectionalizing Units under Criteria of Sensitivity Limits and Power Supply Reliability

et al. 2021

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Sectionalizing 0.4 kV power transmission lines (PTL) improves power supply reliability and reduces electricity undersupply through the prevention of energy disconnection of consumers in the event of a short circuit in the power line behind the sectionalizing unit (SU). This research examines the impact of sectionalizing on power supply reliability and reviews the literature on sectionalizing unit allocation strategies in electrical networks. This paper describes the experience of the use of sectionalizing units with listing strengths and weaknesses of adopted technical solutions and describes the new structure of sectionalizing units. A new methodology is proposed, whereby there are two criteria for allocating SU in 0.4 kV power transmission lines. The first criterion is the sensitivity limits against single-phase short circuits used for calculating the maximum distance at which SU can be installed. The second criterion is power supply reliability improvement, evaluating the cost-effectiveness of installing sectionalizing equipment by reducing power supply outage time. The established methodology was put to the test on an actual electrical system (Mezenka village, Orel area, Russia), which demonstrated that the installation of a sectionalizing unit paid off.

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Section: Allocation Problem Of Sectionalizing Units Within Electrical...mentioning

confidence: 99%

Allocation of 0.4 kV PTL Sectionalizing Units under Criteria of Sensitivity Limits and Power Supply Reliability

et al. 2021

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“…Therefore, short-time voltage interruptions result in extensive sensitive load shutdowns. It has been reported that momentary outages account for two-third (52.3 billion dollars per year) of the overall power interruption cost in the USA [11], [12]. This indicates the main drawback of the fuse-saving scheme that decreases SAIFI at the expense of an increase in momentary average interruption frequency index (MAIFI).…”

Section: Introductionmentioning

confidence: 99%

Optimal Recloser Setting, Considering Reliability and Power Quality in Distribution Networks

Azari¹,

Chitsazan²,

Niazazari³

2017

EPES

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Reclosers and fuses are the commonplace protective devices in distribution networks. A recloser can prevent long-time outages by clearing temporary faults before operation of the fuses in the system. Thus, it decreases the rate of long-term outages and improves system reliability and power quality. Despite positive features of reclosers, each operation of a recloser causes a momentary voltage interruption that exacerbates power quality. Nowadays, power quality issues have become more important because of the increasing use of sensitive equipment to voltage interruptions. According to the mentioned concerns, it seems necessary to set reclosers to strike a balance between power quality and the effectiveness of fuse saving scheme. Thus, we proposed a method to set reclosers. Due to the random nature of faults, the proposed method is stochastic based on the Monte Carlo method. The proposed method determines the optimal number of operations, reclosing intervals, and protection zones. The proposed method efficiency is evaluated according to the simulation results, and the proposed method is capable of establishing an optimal trade-off between power quality and protection efficiency.

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Predictive Reliability Analysis of Power Distribution Systems Considering the Effects of Seasonal Factors on Outage Data Using Weibull Analysis Combined With Polynomial Regression

Dechgummarn,

Fuangfoo,

Kampeerawat

2023

IEEE Access

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In this study, the reliability of power distribution systems is analyzed using a novel strategy of predictive reliability analysis based on the lifetime failure rate cycle in a bathtub curve shape and considering the standard Weibull distribution to determine the trend of the failure rate in each period using median rank regression for parameter estimation. The proposed strategy consists of three processes. The first process involves separating the external and internal factors that influence power outages in the power distribution system from the seasonal multimodal shape in the empirical distribution of the dataset using a bisection algorithm of residuals of polynomial regression. Second, clustering and characterization of each component in the power distribution system according to the condition of the total factor bathtub curve leads to the introduction of the use of shape parameters as the total factor deterioration index (TFDI) with linear regression trends of log scale shape parameters of the useful period. A simple approximation of the system's overall total factor bathtub curve using a sixty-year forecast is the final process presented that can be used in reliability planning to address lifecycle risks. The actual time-to-outage dataset between 2015 and 2020 of the Provincial Electricity Authority, Region 1, Northeastern Thailand, which covers the area of distribution line life in the three periods of the bathtub curve, was used as the test data. The numerical results obtained from the proposed process provide a comprehensive prediction of the reliability of the electrical distribution system for risk response planning. The results show the proportion and amount of internal deterioration versus external disturbances, helps to group components according to health and usability and prioritizes them according to risk. Furthermore, it clarifies the important moments of status transition. All of these factors make it possible to improve reliability in the right place at the right time. Every method that we have chosen to improve for use in analysis is simple, provides a clear visualization of every step, and can be used in practice.

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Predicting Reliability Improvements

Cited by 5 publications

References 2 publications

Allocation of 0.4 kV PTL Sectionalizing Units under Criteria of Sensitivity Limits and Power Supply Reliability

Allocation of 0.4 kV PTL Sectionalizing Units under Criteria of Sensitivity Limits and Power Supply Reliability

Optimal Recloser Setting, Considering Reliability and Power Quality in Distribution Networks

Predictive Reliability Analysis of Power Distribution Systems Considering the Effects of Seasonal Factors on Outage Data Using Weibull Analysis Combined With Polynomial Regression

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