Voltage Sag Source Localization Based on the Voltage Distance Function in Distribution Network

2013 ◽  
Vol 391 ◽  
pp. 607-610 ◽  
Author(s):  
Yu Liu ◽  
Jin Hao Wang ◽  
Chao Ying Yang
Keyword(s):  
Least Squares ◽  
Source Localization ◽  
Distance Function ◽  
Distribution Network ◽  
Voltage Sag ◽  
Sorting Algorithm ◽  
Line Voltage ◽  
Function Fitting ◽  
Fitting Method ◽  
Bus Voltage

To realize voltage sag source localization in distribution network, the paper proposes a function fitting method based on the least squares. Establish a voltage distance function in response to fault distance changes by the line voltage. According to the voltage distance function, combine with the bus voltage after fault to find out likely fault section and distance. Through the sorting algorithm to sort all possible results, weaken the effect of pseudo fault point on the judgment result. Finally the simulation verifies the effectiveness of the method.

scholarly journals Mitigation of Voltage Dip and Voltage Flickering by Multilevel D-STATCOM

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
M. S. Ballal ◽  
H. M. Suryawanshi ◽  
T. Venkateswara Reddy
Keyword(s):  
Power Quality ◽  
Distribution System ◽  
Reactive Power ◽  
Distribution Network ◽  
Voltage Sag ◽  
Service Interruptions ◽  
Flexible Ac Transmission ◽  
Voltage Dip ◽  
Basic Power ◽  
Ac Transmission

The basic power quality problems in the distribution network are voltage sag (dip), voltage flickering, and the service interruptions. STATCOM is a Flexible AC Transmission Systems (FACTS) technology device which can independently control the flow of reactive power. This paper presents the simulation and analysis of a STATCOM for voltage dip and voltage flickering mitigation. Simulations are carried out in MATLAB/Simulink to validate the performance of the STATCOM. A comparison between the six-pulse inverter and the five-level diode-clamped inverter is carried out for the performance of 66/11 KV distribution system.

scholarly journals Flux control coefficients determined by inhibitor titration: the design and analysis of experiments to minimize errors

1993 ◽  
Vol 296 (2) ◽  
pp. 423-433 ◽  
Author(s):  
J R Small
Keyword(s):  
Random Errors ◽  
Flux Control ◽  
Graph Method ◽  
Function Fitting ◽  
Fitting Method ◽  
Simple Extrapolation ◽  
Experimental Errors ◽  
Flux Control Coefficients ◽  
Fitted Function ◽  
Control Coefficients

This paper is a study into the effects of experimental error on the estimated values of flux control coefficients obtained using specific inhibitors. Two possible techniques for analysing the experimental data are compared: a simple extrapolation method (the so-called graph method) and a non-linear function fitting method. For these techniques, the sources of systematic errors are identified and the effects of systematic and random errors are quantified, using both statistical analysis and numerical computation. It is shown that the graph method is very sensitive to random errors and, under all conditions studied, that the fitting method, even under conditions where the assumptions underlying the fitted function do not hold, outperformed the graph method. Possible ways of designing experiments to minimize the effects of experimental errors are analysed and discussed.

scholarly journals Methods for Fitting the Limit State Function of the Residual Strength of Damaged Ships

2022 ◽  
Vol 10 (1) ◽  
pp. 102
Author(s):  
Zhiyao Zhu ◽  
Huilong Ren ◽  
Xiuhuan Wang ◽  
Nan Zhao ◽  
Chenfeng Li
Keyword(s):  
Least Squares ◽  
Residual Strength ◽  
Least Squares Method ◽  
Limit State ◽  
Nonlinear Least Squares ◽  
State Function ◽  
Limit State Function ◽  
Distribution Models ◽  
Sample Distribution ◽  
Fitting Method

The limit state function is important for the assessment of the longitudinal strength of damaged ships under combined bending moments in severe waves. As the limit state function cannot be obtained directly, the common approach is to calculate the results for the residual strength and approximate the limit state function by fitting, for which various methods have been proposed. In this study, four commonly used fitting methods are investigated: namely, the least-squares method, the moving least-squares method, the radial basis function neural network method, and the weighted piecewise fitting method. These fitting methods are adopted to fit the limit state functions of four typically sample distribution models as well as a damaged tanker and damaged bulk carrier. The residual strength of a damaged ship is obtained by an improved Smith method that accounts for the rotation of the neutral axis. Analysis of the results shows the accuracy of the linear least-squares method and nonlinear least-squares method, which are most commonly used by researchers, is relatively poor, while the weighted piecewise fitting method is the better choice for all investigated combined-bending conditions.

scholarly journals Implementation of Voltage Stability System in Distribution Network by using D-STATCOM

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3374-3379
Keyword(s):  
Power Quality ◽  
Distribution Network ◽  
Life Time ◽  
Project Work ◽  
Voltage Sag ◽  
Safe Operation ◽  
Distribution Line ◽  
Quality Issues ◽  
Transmission And Distribution ◽  
Stable Voltage

This project work presents a proposed D-STATCOM system, Which is implemented in the distribution network. In the present scenario, the customer or consumer should be supplied with a quality power. The power quality issues like voltage sag, swell, lightning surges etc, can be reduced by using several advanced techniques. Among all these power quality issues voltage sag is considered and has been compensated in this project work by using D-STATCOM. The major advantage of D-STATCOM is that instead of installing the compensating device in the transmission and distribution line, the D-STATCOM unit is implemented at the consumers premises to maintain stable voltage for the connected electrical equipment’s and also to provide safe operation of the electrical equipment’s by extending their life time. The software ie., implemented by using MATLAB Simulink and the results are also verified experimentally by a hardware unit

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