Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
399045 | International Journal of Electrical Power & Energy Systems | 2009 | 8 Pages |
Abstract
This paper proposes a method for probabilistic load flow in networks with wind generation, where the uncertainty of the production is non-Gaussian. The method is based on the properties of the cumulants of the probability density functions (PDF) and the Cornish–Fisher expansion, which is more suitable for non-Gaussian PDF than other approaches, such as Gram–Charlier series. The paper includes examples and comparisons between different methods proposed in literature.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Julio Usaola,