Power system reliability evaluation using learning vector quantization and Monte Carlo simulation

Autor:	Chanan Singh, X. Luo, A.D. Patton
Rok vydání:	2003
Předmět:	Learning vector quantization Electric power system Artificial neural network business.industry Computer science Monte Carlo method Energy Engineering and Power Technology Artificial intelligence Electrical and Electronic Engineering business Algorithm Reliability (statistics)
Zdroj:	Electric Power Systems Research. 66:163-169
ISSN:	0378-7796
DOI:	10.1016/s0378-7796(03)00025-7
Popis:	Artificial Neural Networks (ANN) based on the Learning Vector Quantization (LVQ) algorithm have received considerable attention as pattern classifiers. This paper proposes a new method for power system reliability evaluation combining Monte Carlo simulation and LVQ which greatly reduces the computing burden of the loss of load probability calculation compared to Monte Carlo simulation only. A case study of the IEEE RTS system is presented demonstrating the efficiency of this approach.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::225c564c36cdb87621b48b2d493b5425 https://doi.org/10.1016/s0378-7796(03)00025-7 Zobrazit plný text záznamu Full Text from ScienceDirect