Loss-of-load probability calculation using learning vector quantization Conference Paper

abstract

• 2000 IEEE. This paper proposes a new method employing Learning Vector Quantization (LVQ) and Monte Carlo simulation to calculate the Ioss-of-load probability (LOLP) of power systems. LVQ is a type of classification method whose goal is to use data samples to position the codebook vector in such a way that the nearest neighbor classification method will result in the maximum classification accuracy. The proposed method 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.

name of conference

• PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409)

authors

• Singh, Chanan

published proceedings

• 2000 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY, VOLS I-III, PROCEEDINGS

author list (cited authors)

• Luo, X. C., Singh, C., & Zhao, Q.

citation count

• 2

complete list of authors

• Luo, XC||Singh, C||Zhao, Q

publication date

• January 2000

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

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

Digital Object Identifier (DOI)

• 10.1109/icpst.2000.898238

International Standard Book Number (ISBN) 10

• 0-7803-6338-8

International Standard Book Number (ISBN) 13

• 9780780363380

start page

• 1707

end page

• 1712

volume

• 3

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Ficpst.2000.898238