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

abstract

• 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. 2003 Elsevier Science B.V. All rights reserved.

authors

• Singh, Chanan

published proceedings

• ELECTRIC POWER SYSTEMS RESEARCH

author list (cited authors)

• Luo, X. C., Singh, C., & Patton, A. D.

citation count

• 29

complete list of authors

• Luo, XC||Singh, C||Patton, AD

publication date

• August 2003

publisher

• Elsevier  Publisher

published in

• Electric Power Systems Research  Journal

keywords

• Learning Vector Quantization
• Loss-of-load Probability
• Optimal Power Flow
• Reliability Evaluation

Digital Object Identifier (DOI)

• 10.1016/S0378-7796(03)00025-7

start page

• 163

end page

• 169

volume

• 66

issue

• 2

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2Fs0378-7796%2803%2900025-7