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All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics
WANG Xin-wei
North China Electric Power University
Computer Science & IT Electrical & Electronics Engineering Engineering

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Reliability Assessment of Power Generation System With Wind Farm WANG Xin-wei; ZHANG Jian-hua; JIANG Cheng; YU Lei; SHANG Jingfu
Bulletin of Electrical Engineering and Informatics Vol 2, No 1: March 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (170.742 KB) | DOI: 10.11591/eei.v2i1.258

Abstract

The reliability of power generation system with wind farm is evaluated based on Monte-Carlosimulation, and in the reliability assessment the randomness of wind speed and power load, failure rate ofwind turbine generator(WTG) and conventional generator are take into account. Monte-Carlo simulationused in power generation system with wind power need large sample size and has low efficiency. So thispaper proposes an improved Monte Carlo method (IMC) based on the combination of Latin HypercubeSampling and Cholesky decomposition, this IMC method is effective to improve sample values coverage ofrandom variables input spaces and the sampling efficiency. The calculation and analysis of improvedIEEE-RTS 79 reliability test systems show that the proposed Assessment algorithm is effective.
Reliability Assessment of Power Generation System With Wind Farm WANG Xin-wei; ZHANG Jian-hua; JIANG Cheng; YU Lei; SHANG Jingfu
Bulletin of Electrical Engineering and Informatics Vol 2, No 1: March 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v2i1.258

Abstract

The reliability of power generation system with wind farm is evaluated based on Monte-Carlosimulation, and in the reliability assessment the randomness of wind speed and power load, failure rate ofwind turbine generator(WTG) and conventional generator are take into account. Monte-Carlo simulationused in power generation system with wind power need large sample size and has low efficiency. So thispaper proposes an improved Monte Carlo method (IMC) based on the combination of Latin HypercubeSampling and Cholesky decomposition, this IMC method is effective to improve sample values coverage ofrandom variables input spaces and the sampling efficiency. The calculation and analysis of improvedIEEE-RTS 79 reliability test systems show that the proposed Assessment algorithm is effective.
Reliability Assessment of Power Generation System With Wind Farm WANG Xin-wei; ZHANG Jian-hua; JIANG Cheng; YU Lei; SHANG Jingfu
Bulletin of Electrical Engineering and Informatics Vol 2, No 1: March 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (170.742 KB) | DOI: 10.11591/eei.v2i1.258

Abstract

The reliability of power generation system with wind farm is evaluated based on Monte-Carlosimulation, and in the reliability assessment the randomness of wind speed and power load, failure rate ofwind turbine generator(WTG) and conventional generator are take into account. Monte-Carlo simulationused in power generation system with wind power need large sample size and has low efficiency. So thispaper proposes an improved Monte Carlo method (IMC) based on the combination of Latin HypercubeSampling and Cholesky decomposition, this IMC method is effective to improve sample values coverage ofrandom variables input spaces and the sampling efficiency. The calculation and analysis of improvedIEEE-RTS 79 reliability test systems show that the proposed Assessment algorithm is effective.
Co-Authors JIANG Cheng SHANG Jingfu YU Lei ZHANG Jian-hua