Using Genetic Programming to Estimate WECS Output Power | ||||
| The International Conference on Mathematics and Engineering Physics | ||||
| Article 8, Volume 3, International Conference on Engineering Mathematics and Physics (ICMEP-3), May 2006, Page 1-8 PDF (581.93 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/icmep.2006.29911 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Said A. Gouda | ||||
| Ph. D., Department of Mathematics Air-Defense College, Egypt. | ||||
| Abstract | ||||
| Abstract: A statistical technique to characterize wind speed data for use in wind energy conversion system (WECS) is presented. We start by examining the frequency distribution of long-term data. The histogram is generated for observed wind speed for a particular hour over a month for a number of years. It is fitted to two distributions (Weibull, and β).Genetic Programming (GP) also used to fit the distribution. Two goodness-of-fit criteria are employed in checking the best fit. These are Chi-square (χ2), and Kolmogorov-Smirnov (KS). Long-term data from International Logan Airport, Boston, MA, USA are analyzed. It is found that the GP fits the long-term hourly data best. | ||||
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