A novel voltage sag state estimation method based on complex network analysis

Hu, Weisheng; Ruan, Zi-hang; Xiao, Xianyong; Xiong, Xiao-yi; Wang, Junqi

doi:10.1016/j.ijepes.2022.108119

Cited by 6 publications

(3 citation statements)

References 19 publications

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“…Ideally the monitoring of all sensitive sites would be required during very long monitoring periods [10], [11] (e.g., if voltage sags occur once a week, it would take at least 7 years of monitoring to obtain a 10% accuracy in the estimation of annual indices [10]). In addition, very often there is a limitation in the number of available monitors which prevents from using this source of information or requires using advanced voltage sags state estimation methods [12], [13], [14], [15].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of Voltage Sags Estimation to Uncertainties

Zambrano

Hernàndez²,

Caro³

et al. 2023

IEEE Access

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Voltage sags are power quality disturbances mainly caused by faults with a highly random nature. For this reason, the severity and frequency of occurrence of voltage sags is typically analyzed by means of probabilistic methods, such as Monte Carlo simulations, where different probability distributions are selected to model the uncertain inputs (e.g., fault impedance, fault location, fault rate, etc.). The selection and parameterization of the appropriate probability functions involves many difficulties to ensure that they represent the distribution of input variables in a realistic way and so, many different approaches can be found in literature. This paper studies the sensitivity of voltage sags severity to the uncertainty in the input models in order to focus modeling effort on the input variables that are more critical and effectively have an influence on voltage sags levels, whereas non-influential parameters can be neglected or modeled by means of simplified hypothesis. The method proposed is based on Design of Experiments and Analysis of Variance (ANOVA) and is able to discriminate with a statistic confidence level whether the uncertainty in the input significantly affects voltage sags severity indices or not. The effect of uncertainty on voltage sags indices SARFI90 and SARFI70 has been evaluated in realistic scenarios for IEEE test networks of 24 and 118 buses and in the power system of Ecuador with 357 nodes. General trends have been also established that help to understand the effect of the modeling of input parameters on the estimated number of sags.INDEX TERMS Analysis of variance, design of experiments, sensitivity analysis, power quality, uncertainty, voltage sag.

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Section: Introductionmentioning

confidence: 99%

Sensitivity of Voltage Sags Estimation to Uncertainties

Zambrano

Hernàndez²,

Caro³

et al. 2023

IEEE Access

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“…It is commonly expressed as a unit value in calculations. The duration of voltage sag is the time difference between the occurrence and end of the sag [4][5][6]. In actual engineering measurements, the duration of the sag process varies depending on the magnitude of the voltage sag.…”

Section: Introductionmentioning

confidence: 99%

Research on Voltage Sag Detection Algorithm based on Regional Transmission System

Wang¹,

Shi²

2023

FCIS

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Voltage sag is the most common power quality issue and often brings huge economic losses. To achieve voltage sag prevention and compensation, it is necessary to effectively detect voltage sag characteristics. An IEEE-39 node system model is built using Simulink, combined with common aer transformation methods and αβ. The transformation method accurately detects voltage sag accidents and incorporates a derivative algorithm, greatly reducing the detection delay and meeting the real-time and accuracy requirements of actual systems.

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“…To evaluate the severity of voltage sag (SVS) events caused by lightning, a data-driven selflearning evaluation method for voltage sag severity is proposed [9]. The voltage sag state estimation method based on complex network analysis is also discussed [10]. A single sag event can result in brief and prolonged interruptions if the sensitive electrical equipment does not have adequate voltage sag ride-through capacity.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach of Voltage Sag Data Analysis Stochastically: Study, Representation, and Detection of Region of Vulnerability

et al. 2023

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A voltage sag is a major power quality problem at any load location, mainly due to short circuit faults. Its effects are especially clear in the industrial sector because they lead to direct financial losses. The first and most important step to getting rid of or at least reducing voltage sag is to find the places in the network where it can happen. So, this article discusses a creative way to find the weak spots in a network where the voltage is more likely to drop. This innovative strategy is based on correlation and a stochastic normal probability distribution. The voltage sag is evaluated using an analytical method. The method simulates the number, type, and location of faults randomly throughout the system. After gathering voltage dip data, it is analyzed using normal probability distribution and correlation concepts. The correlation concept provides the relationship between the sag frequency and other parameters, and the sag occurrence area was indicated by the normal probability distribution. After that, the region of vulnerability (ROV) is developed using the ROV flow chart. This paper uses an IEEE 30-bus RTS system as a case study to demonstrate the usefulness of the suggested strategy using MATLAB software.

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A novel voltage sag state estimation method based on complex network analysis

Cited by 6 publications

References 19 publications

Sensitivity of Voltage Sags Estimation to Uncertainties

Sensitivity of Voltage Sags Estimation to Uncertainties

Research on Voltage Sag Detection Algorithm based on Regional Transmission System

A Novel Approach of Voltage Sag Data Analysis Stochastically: Study, Representation, and Detection of Region of Vulnerability

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