Wednesday, March 20th, 2019

Wind characterization analysis incorporating genetic algorithm: A case study in Taiwan Strait

Publication year: 2011brbSource:/b Energy, In Press, Corrected Proof, Available online 8 March 2011brFeng-Jiao, Liu , Pai-Hsun, Chen , Shyi-Shiun, Kuo , De-Chuan, Su , Tian-Pau, Chang , …brIn this paper, the genetic algorithm (GA) is originally applied to compute the Weibull parameters for wind characterization analysis, in which an objective function required in GA for searching optimization solution has been first defined as well. Wind data analyzed are observed at a wind farm in the Taiwan Strait from 2006 to 2008. To accurately describe wind speed distribution three kinds of probability density functions are compared, i.e. the Weibull, logistic and lognormal functions. Statistical parameters including the max error in the Kolmogorov–Smirnov test, root mean square error, Chi-square error and relative error of wind power density are considered…br Research highlights: ► The genetic algorithm was applied for the first time to calculate the Weibull parameters for wind energy assessment. ► Weibull probability function fits the observed wind speed distribution better than both logistic and lognormal functions. ► Wind and solar energy potential in Taiwan show a great complementary relationship.

Speak Your Mind

Questions or comments? We'd love to hear from you!