Title :
Risk Evaluation of Generation-Load System Based on Monte Carlo Method and Fast Clustering Analysis Method
Author :
Jiang, Jingliang ; Huang, Anping ; Liu, Yuanyuan
Author_Institution :
Electr. Power Coll., South China Univ. of Technol., Guangzhou, China
Abstract :
Generation-load system risk indicators are important indicators which measure power system´s adequacy. Presently, the references of calculation of Generation-load system risk indicators are rare. This paper applies Monte Carlo to simulate the generator´s working state and fast clustering analysis to classify the loads´ data to estimate Generation-load System risk indicators. Then, with the IEEE RTS-6-bus system as an example, its results prove the algorithm to be effective.
Keywords :
Monte Carlo methods; load (electric); pattern clustering; power system measurement; power system security; risk analysis; Monte Carlo method; clustering analysis method; generation load system; power system measurement; risk indicators; Capacity planning; Generators; Load modeling; Monte Carlo methods; Power systems; Probability distribution; Reliability; Generation state; Generation-load system risk indicators; Monte Carlo; fast clustering analysis; load classification;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6880-5
DOI :
10.1109/iCECE.2010.1016
