Voltage Sag Severity Research Articles

Voltage sag assessment of large power grid based on branch change influence domain

The change of a large-scale power grid topology leads to the change of node voltage sag assessment results. Thus, it is necessary to re-simulate massive line fault scenarios. However, the simulation time of the existing assessment methods is too long to ensure the practicability of the project. To solve the problems above, we propose a voltage sag assessment method for a large-scale power grid based on the branch change influence domain. Firstly, the branch change influence index is constructed to quantify the influence law of the branch change on the node voltage sag level. Secondly, based on the different influence degrees of each region, an adaptive electrical distance threshold selection method is proposed and then the range of the branch change influence domain is divided in order to construct and simulate the fault scene in the branch change influence domain. Finally, the historical simulation results are updated by using the simulation results of the branch change influence domain fault, and the severity of the node voltage sag after the topology change is calculated. Through the example of the IEEE118 node system and the actual grid structure of a city in Fujian, it has been proved that the proposed method can effectively reduce the fault simulation time by up to 96% and improve the efficiency of the voltage sag assessment of a large-scale power grid.

A comprehensive evaluation method of DC voltage sag in medium–low voltage DC distribution system

The development of the DC distribution system (DCDS) has attracted increasing attention, due to its technological superiorities in integrating new energy sources and DC power loads more friendly and effectively. In this paper, a comprehensive evaluation method is proposed for the medium–low​ voltage DCDS to handle the voltage sag assessment problem. Firstly, the topology structure and control strategy of the DCDS are stated, and the pragmatic characteristics of DC voltage sag on the medium-voltage and low-voltage sides based on the dual active bridge (DAB) converter are analyzed. Then, considering the difference in the evaluation indexes of the low-voltage and medium-voltage sides of the DCDS, a comprehensive evaluation system is established. Further, the analytic hierarchy process (AHP) and criteria importance through intercriteria correlation (CRITIC) weighting method are applied to achieve comprehensive weighting, and the TOPSIS model is used to describe the severity of DC voltage sag. Using MATLAB, a 10 kV/ 750 V DCDS with the DAB is built, and comparative assessments are performed. The results show that the proposed method can reasonably evaluate the DC voltage sag of the low-voltage and medium-voltage sides. Compared to the evaluation schemes based on the single index, the proposed method can more effectively reflect the waveform features of the DC voltage sag, and it is very appropriate for the voltage dip evaluation of the medium–low voltage DCDS.

Risk assessment of voltage sag based on multi-source data mining

This paper proposes the data mining method of voltage sag severity based on DHP algorithm and replaceable coefficient to assess the risk of voltage sag. The DHP (Direct Hashing and Pruning) is served to mine the relationship between voltage sag characteristic attribute (VSCA) in the fault scenario and the voltage sag severity (VSS) of node. Using direct hash pruning technology, frequent item sets can be found quickly and mining efficiency can be improved. The association rules are matched with the actual fault scenarios through replaceable coefficients to get the VSS of actual fault scenarios. Finally, the effectiveness and accuracy of this method are verified by simulation and examples.

A Data-Driven Self-Learning Evaluation Method of Voltage Sag Severity

Lightning is one of the main causes of voltage sags, and it is of great significance for subsequent analysis and governance to accurately evaluate the severity of the sag events caused by lightning. There are many uncertain factors between lightning fault events and voltage sag events. To evaluate the severity of voltage sag events caused by lightning, a data-driven self-learning evaluation method for voltage sag severity is proposed. According to a large number of online monitoring data of lightning positioning system and power quality monitoring system, the association rule mining algorithm based on incremental learning is used. And the rules are kept updating through the accumulation of historical data, which may give it the abilities of self-learning. The empirical analysis is carried out based on the monitoring data of a regional power grid. The results show that the method in this paper can accurately mine more valuable rules in reality and solve the problem of low efficiency of mining algorithm when the database changes dynamically.

EVALUATION METHOD OF VOLTAGE SAG SEVERITY FROM GRID SIDE BASED ON POINT-TO-LINE DISTANCE INDEX

Evaluation of voltage sag severity from grid side according to the monitoring data is a very important task for utilities. This paper presents an approach to evaluate the system voltage sag severity based on point-to-line distance index. Representing the sag events in the duration-magnitude plane, the scatters are analysed to obtain the distribution characteristics of all sag events. Cluster analysis is applied to duration of all the sags to obtain serval intervals. Then the medians of retained voltage are solved by total events in different intervals to plot the median line. The severity index named point-to-line distance is defined for a region as the average of the distance from point below the median line to the median line. The method is applied to evaluate the voltage sag severity of 10 regions in an urban city. The feasibility and rationality of the method can be testified by the comparison of the evaluation results with other indices. The method is based on a large number of monitoring data and achieves the system evaluation directly considering both duration and magnitude.

A Comprehensive Weight-Based Severity Evaluation Method of Voltage Sag in Distribution Networks

With the increasing use of sensitive loads in frequency converters and in relays in distribution networks, voltage sag has become a major power quality issue that urgently needs to be solved. For the purpose of improving the understanding of voltage sag severity in distribution networks, a comprehensive weight-based severity evaluation method of voltage sag is presented in this paper. First, a multi-side index system that takes into account the combined influence of the source, network, and the load is established. A comprehensive weight method, which combines the improved analytic hierarchy process (IAHP) and the entropy method, is then adopted to determine the index weight. The weight of each index and the degree of superiority are linearly weighted to obtain the severity of voltage sag at different observation points. Finally, the effectiveness of the proposed method is verified using a distribution network model established in DIgSILENT PowerFactory (15.1.7, Gomaringen, Germany).

A Voltage Sag Severity Evaluation Method for the System Side Which Considers the Influence of the Voltage Tolerance Curve and Sag Type

Considering the influence of user equipment voltage tolerance characteristics and sag types on the evaluation results, this paper proposes a voltage sag severity evaluation method for the system side which considers the influence of the voltage tolerance curve and sag type. As such, a quantitative evaluation of the severity of voltage sag events can be achieved. Firstly, the user’s voltage tolerance curve is used to construct the comparison reference value of the energy index, in order to realize the rapid analysis of the severity of the sag event in the normal area and the abnormal area. Secondly, aiming at the problem of insufficient descriptions of the severity difference of sag events in uncertain areas, an improved energy index evaluation model combined with user tolerance characteristics is established through an interval division and interval weight calculation, so as to divide and evaluate the severity of sag events in uncertain areas. Considering the influence of the sag type on the voltage tolerance curve and user equipment, the energy index correction factor is then constructed, and the measurement function is used for an interval evaluation to obtain the ranking result of the voltage sag severity, which is more in line with the actual situation. Finally, the rationality and effectiveness of the proposed method are verified by analyzing 24 voltage sag events at a monitoring node.

Joint Optimal Planning of Distributed Generations and Sensitive Users Considering Voltage Sag

The inevitable voltage sag events cause losses to distributed generation (DG) and sensitive users. Reasonable planning for both of them helps to mitigate the impact of voltage sag. In this paper, a joint optimal planning method is proposed for DG and large sensitive user (LSU) considering the influence of voltage sag. Firstly, the new models of accelerated trip and chain trip for DG under voltage sag are established, to characterize the influence of DG tripping on other DG and sag characteristics during the sag event accurately. Secondly, a new voltage sag frequency assessment method is proposed, which considers models of accelerated trip and chain trip for DG, the tripping characteristics of distance protection (DP), to quantify the voltage sag severity accurately of DGs and LSUs in the gird which is with DP. Lastly, a joint optimal planning model is established considering the losses of DG and LSU under voltage sag, to support the planning of DG and LSU in different scenarios. The method is applied to IEEE RTS-30 for verification, proving that the method can give a direction of the most beneficial solution for the planner, to reduce the losses of voltage sag to both the power system and users.

Voltage sag severity analysis based on improved FP-Growth algorithm and AHP algorithm

In order to accurately evaluate the impact of voltage sag on both utility and customer, a data mining analysis method based on improved FP-growth algorithm and AHP algorithm is proposed. The proposed method selects and classifies voltage sag characteristics and combines voltage sag severity level to construct a data mining analysis framework. The improved FP-growth algorithm is used for data mining on voltage sag events to improve the efficiency of mining. The association rule matching model is constructed by AHP algorithm for evaluating the voltage sag severity level, which improves the accuracy of the evaluation results. Finally, a practical example verifies the practicability of the proposed method.

Evaluation Method of Voltage Sag Severity in Distribution Networks

Recently voltage sags have gradually become one of the most important power quality problems with the large scale use of sensitive electrical equipment. Analysis of varied attributes causing voltage sags can not only guide the planning, equipment selection, operation and maintenance of power supply engineering, but also can provide a theoretical basis for effectively assessing the risks and severity of the power quality incidents. It is meaningful to combine the existing problems of technology and management level to get the assessment results of the voltage sags. In this paper, clustering analysis and evaluation method are proposed for multi-cause attributes that affect voltage sags. The calculation method of the voltage on the multiple fault location parameters in the power grid is derived. The evaluation method of the voltage sags considering the user’s tolerance level is given. The characteristic properties of causes are used as parameters to describe disturbances which provide a basis for voltage sag evaluation. Then the equipment compatibility index is introduced, the analytic hierarchy process is used to determine the weight of the voltage sag evaluation index, and the severity of the voltage sag of each node of the distribution network is calculated to realize the distribution network voltage sag severity assessment. Finally, the voltage sag under multi causal attributes is analyzed using the equipment compatibility index as the standard, and the sag severity of the equipment is analyzed. The multi-factor attributes contribution degree proposed in this paper takes the equipment compatibility as the index, and can accurately reflect the impact of various attributes on equipment after voltage sags.

Evaluation Method and Probabilistic Index of Voltage Sag Severity Considering Point-on-wave

The impact of voltage sag on sensitive devices is related to the time when the sag occurs. However, the point-on-wave of a sag is uncertain. Therefore, this paper presents a novel approach to evaluate the voltage sag severity considering a random point-on-wave. First, the uncertainty of equipment malfunction is revealed. Second, under a given residual voltage, the relationship between the point-on-wave and the duration that the device can withstand is described with a fitting curve. Third, a voltage sag probabilistic index is proposed to describe the severity. The evaluation procedure is also presented. Finally, three types of releasers are tested and analyzed to determine the effectiveness of the proposed method. The evaluation method can help instruct electrical engineers establish more well-grounded sag mitigation proposals.

Severity index‐based voltage sag insurance for high‐tech enterprises

Economic losses caused by power disturbances such as voltage sags and short interruptions have become an important concern for high-tech enterprises in recent years. A potential solution to address this challenge is to provide value-added services such as voltage sag insurance to help enterprises to manage voltage sag risks. This study presents a severity index-based voltage sag insurance scheme including the liability, period, premium and compensation. Voltage sag severity is used as the index of insurance to define the trigger and limit of liability. The production value of enterprises suffered with voltage sags is obtained by introducing economics thus can accurately quantify the interaction between technical indexes of voltage sag and the economic indexes required for premium. Finally, case studies of three high-tech enterprises located in China have proved the correctness and rationality of the proposed insurance scheme.

Method to estimate sag frequency in doubly fed induction generator integrated power system based on adaptive kernel density estimation

Voltage sag frequency estimation is necessary for understanding the voltage sag severity in power system and offering full information for the interested parties to mitigate voltage sag. The high penetration of wind power in the power system and the uncertainty of the fault distribution raise new challenges to accurate voltage sag frequency estimation. This study presents a systematic voltage sag frequency estimation method, considering the fault distribution density, fault ride-through (FRT) process of wind turbines during voltage sag and the interval characteristic of voltage sag frequency. First, this study proposes a fault distribution estimation model based on adaptive kernel density. Second, this study proposes a method for calculating the residual voltage and duration of voltage sag during FRT and combines the common distance protection action to analyse the effect on voltage sag by FRT process of wind turbines. Lastly, this study proposes an interval-valued voltage sag estimation method considering the interval characteristics of fault rate in the power system. IEEE 30-bus test system is used to verify the proposed method, the estimation results show better performance of the proposed method compared with the typical estimation methods.

Optimal selection of voltage sag mitigating devices for micro‐level customer in distribution system

Power quality is a vital issue in distribution systems. Power quality issues have become important for the extensive use of sensitive equipment and integration of renewable generation. Several researchers have proposed for voltage sag mitigation devices to minimise financial losses arising from voltage sag. Augmentation of micro-level units like housing complex, super-specialty hospitals, rapid urbanisation has opened up demand for electricity. Modernisation in life has led to coextensive requirement for good quality power. Importance of micro-level consumers is to be considered while looking into the matter of optimal selection of voltage sag mitigation devices. In this study, a new framework is proposed for optimal selection of voltage sag mitigation devices to minimise voltage sag occurrence in a distribution system based on Nested Logit model. Nested Logit model has the essential characteristic for selection of optimal option by allowing equal preference to all the available customers' choice. This model gives unbiased and equal importance to all the available mitigation devices. The optimal selection of mitigation devices is obtained using aggregate forecasting. Voltage sag severity index is used for placement of optimally selected voltage sag mitigation device. Two case studies are described to validate the proposed approach.

Research on uncertainty evaluation measure and method of voltage sag severity

Voltage sag is an inevitable serious problem of power quality in power system. This paper focuses on a general summarization and reviews on the concepts, indices and evaluation methods about voltage sag severity. Considering the complexity and uncertainty of influencing factors, damage degree, the characteristics and requirements of voltage sag severity in the power source-network-load sides, the measure concepts and their existing conditions, evaluation indices and methods of voltage sag severity have been analyzed. Current evaluation techniques, such as stochastic theory, fuzzy logic, as well as their fusion, are reviewed in detail. An index system about voltage sag severity is provided for comprehensive study. The main aim of this paper is to propose thought and method of severity research based on advanced uncertainty theory and uncertainty measure. This study may be considered as a valuable guide for researchers who are interested in the domain of voltage sag severity.

Assessment of Equipment Trip Probability Due to Voltage Sags Based on Fuzzy Possibility Distribution Function

Assessment of equipment trip is needed for proper estimation of interruption/disruption cost and voltage sag mitigation. The equipment trip depends on the severity of voltage sag and the tolerance of the equipment toward the sag. However, the occurrence of voltage tolerance of an equipment in between the two known bound levels is uncertain in nature. The existing evaluation methods for equipment trip analysis fail to properly assess this uncertain property of voltage tolerance curves. This paper presents a novel approach to assess the equipment trip by handling the uncertainties by using fuzzy probability and possibility distribution. A new method is proposed to transform a rigorously performed statistical data into a fuzzy possibility distribution function, which eliminates the ambiguity that comes with the non-standardized selection of membership function/possibility function. With the proposed method, the statistical data are used to extract the fuzzy probability distribution of voltage sag intensity, which is given by both the magnitude and time duration of voltage sags, while the concept of fuzzy probability is used to calculate the fuzzy trip probability or equipment failure probability. The proposed method is finally applied to estimate the number of trips for six different sensitive equipments connected to two practical Indian distribution systems.

An Integrated High Side Var-Voltage Control Strategy to Improve Short-Term Voltage Stability of Receiving-End Power Systems

To make better use of local generators' dynamic var reserve to improve short-term voltage stability (STVS), this paper proposes an integrated high side var-voltage control (IHSV $^{2}$ C) for power plants in receiving-end power systems. The IHSV $^{2}$ C consists of a plant-level multi-machine var coordinator (MMVC) and several unit-level high side voltage controllers (HSVCs). MMVC coordinates the reactive power output among generators and provides control parameters for HSVCs, while HSVCs can maintain the voltage of a pre-defined voltage control point (VCP) by regulating the voltage reference of the excitation control of each generator. Therefore, when the system suffers a serious fault, IHSV $^{2}$ C can drive the generators to provide stronger var support. Consequently, the voltage stability can be improved. A conceptual model of the receiving-end power system in China Southern Power Grid (CSG) is established, and the IHSV $^{2}$ C has been validated through a simulation analysis on the system. Both time-domain simulation results and the voltage sag severity index (VSSI) have fully demonstrated its performance. Therefore IHSV $^{2}$ C offers a new and effective approach to improve STVS of receiving-end power systems.

Voltage Sag Planning of a Power System with Specially Connected Transformers Using Hybrid Differential Evolution Considering ITI Curve

This paper outlines the voltage sag planning of a power system with a three-phase to two-phase transformer. We compared systems with V-V and Scott connection schemes using the hybrid differential evolution (HDE) method to determine the design parameters by taking into account the ITI curves and coordination of over-current relays. The proposed model comprises a node admittance matrix for the calculation of voltage sag in order to determine the severity of system sag after single or two-phase faults. These analytical equations are useful in the mathematical determination of optimal design parameters. We also used the proposed method to obtain suitable values for the relay time multiplier and transformer impedance. Experiment results on V-V and Scott power systems demonstrate that the severity of voltage sag can be reduced through the tuning of relay settings and transformer impedance.

Voltage quality performance improvement of a distribution feeder with Superconducting Fault Current Limiter

Due to the rapid growth of load demand, different power sources are added to the power system, and the interconnection among various power devices for a modern electric grid also becomes more and more complicated. Therefore, the fault current is dramatically increasing, and Superconducting Fault Current Limiter (SFCL) has introduced to solve the related problems. In this paper proposes the strategies of applying SFCL to distribution feeder for the system performance improvement of power quality, including the fault current limiter and the mitigations of voltage variations including sag and swell. And the effectiveness for different feeder types, radial and closed-loop structures, is analyzed for Taiwan Power Company (Taipower) system. When a single-phase to ground fault happens to a certain point along the feeder or at the tie breaker, the simulation results show that SFCL can effectively limit the fault current, and the decrease in amplitude can be up to approximately 55%. Besides, the research results illustrate that the voltage sag severity at fault phase and voltage swell at non-fault phase are dependent of fault location. Therefore, the effectiveness of voltage quality improvement is definitely illustrated by the curve of Information of Technology Industry Council (ITI Curve).

Voltage sag problems in large‐scale clustering wind farms

Accompanied by the development of large‐scale wind energy and integration into grid in China, wind farm cascading trip‐off accidents resulting from voltage sag have occurred frequently in the past few years. Before proposing countermeasures, it is necessary to clarify the voltage sag problem of wind farms. First, three voltage sag risk indices are proposed. Second, the simplified equivalent circuit of double fed induction generator (DFIG) for short‐circuit calculation, stochastic model of wind speed and the fault model of buses/lines are presented in this paper. Third, assessment method of voltage sag in wind farm, implemented by Digsilent dynamic programming language (DPL), is proposed to analyze the severity and probability of voltage sag. Finally, a case study of wind farm connected to WSCC nine‐bus benchmark systems is analyzed in detail, and the validity of the proposed approach is confirmed. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.