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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Chen Shaonan Chen Biyun Gong Shu Ye Lei Bi Wanxia Wei Hua |
| Copyright Year | 2014 |
| Description | Author affiliation: Guangxi key Lab. of Power Syst. Optimization & Energy Technol., Guangxi Univ., Nanning, China (Chen Shaonan; Chen Biyun; Gong Shu; Ye Lei; Bi Wanxia; Wei Hua) |
| Abstract | For the reliability evaluation of distribution network with wind power, the current application of different simulation methods have a common contradiction between accuracy and computational time. In this paper, a method for the reliability evaluation of distribution network based on Wasserstein distance multi-scene is presented. First, optimal quintile and its probability of wind power scenes are determined by probability distribution of wind speed and wind turbine power curve. Second, the feeder partition algorithm is applied to calculate the reliability indices of distribution network under different scenes. Finally, the total probability formula is used to calculate the reliability indices of distribution network with wind power. A comparison with the results of Monte Carlo simulation method shows that the proposed method is simple and efficient, having high accuracy and suitable for evaluating reliability of distribution network that encompasses wind power. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 298173 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479975372 |
| DOI | 10.1109/APPEEC.2014.7066104 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-12-07 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Monte Carlo methods Wind speed Multi-scene Wasserstein Distance Wind power generation Reliability Evaluation Distribution Network Power system reliability Wind turbines Reliability Feeder Partition |
| Content Type | Text |
| Resource Type | Article |
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