DocumentCode
2605261
Title
Probabilistic estimation of PCC loss due to voltage sags in large power systems
Author
Li, Gengyin ; Yang, Xiaodong ; Zhou, Ming
Author_Institution
Key Lab. of Power Syst. Protection & Dynamic Security Monitoring & Control under Minist. of Educ., North China Electr. Power Univ., Beijing, China
fYear
2009
fDate
6-7 April 2009
Firstpage
1
Lastpage
6
Abstract
In this paper probabilistic estimation of PCC loss is approached in distribution systems. For the difficulty of directly solving the impedances of the star-connected equivalent model, a port-based model is adopted for voltage magnitude calculation under four fault types (TPF, SLGF, LLF and DLGF). The specific energy (SE) function is used to evaluate voltage sags involving the voltage magnitude and sag duration simultaneously, and PCC loss is directly computed from the trip probability density, which derives from the normal probability distribution function of SE. The distribution characteristic of balanced and unbalanced faults is also considered. The estimation method for PCC loss is proved fast and effective by IEEE RBTS system.
Keywords
power distribution faults; power supply quality; statistical distributions; PCC loss; balanced fault; distribution systems; large power systems; normal probability distribution function; point of common coupling; port-based model; probabilistic estimation; specific energy function; star-connected equivalent model; trip probability density; unbalanced faults; voltage magnitude calculation; voltage sags; Circuit faults; Impedance; Power quality; Power system faults; Power system modeling; Power system protection; Power system simulation; Power systems; Probability; Voltage fluctuations; PCC loss; probabilistic estimation; probability density; specific energy; voltage sag;
fLanguage
English
Publisher
ieee
Conference_Titel
Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-4934-7
Type
conf
DOI
10.1109/SUPERGEN.2009.5348316
Filename
5348316
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