Title :
Stochastic prediction of voltage sags in a large transmission system
Author :
Qader, Mohammed R. ; Bollen, Math H J ; Allan, Ron N.
Author_Institution :
Centre for Electr. Energy, Univ. of Manchester Inst. of Sci. & Technol., UK
Abstract :
This paper discusses two stochastic prediction methods for voltage sags and applies them to a 97-bus model of the 400 kV National Grid of England and Wales. The method of fault positions is most suitable for implementation in a software tool. It has been used to get exposed areas and sag frequencies for each bus. The results are presented in different ways, including a so-called voltage sag map showing the variation of the sag frequency through the network. The method of critical distances is more suitable for hand calculations, as both the amount of data and the complexity of the calculations are very limited. It has been used to obtain sag frequencies for a number of buses. A comparison with the results obtained by using the method of fault positions shows that the method of critical distances is an acceptable alternative where software or system data are not available for a more accurate analysis
Keywords :
fault location; power supply quality; power transmission faults; power transmission reliability; stochastic processes; 97-bus model; England; National Grid; Wales; critical distances method; exposed areas; fault positions method; large transmission system; power quality; power system reliability; sag frequencies; sag frequency variation; software tool; stochastic prediction methods; voltage sag map; voltage sags; Circuit faults; Frequency; Industrial power systems; Monitoring; Power engineering and energy; Power quality; Power system reliability; Power systems; Stochastic processes; Voltage fluctuations;
Journal_Title :
Industry Applications, IEEE Transactions on