COMPARATIVE ANALYSIS OF MATHEMATICS, STATISTICS AND PHYSICS BASED ALGORITHMS FOR OBTAINING OPTIMUM WEIBULL PROBABILITY DISTRIBUTION PARAMETERS FOR POWER DENSITY ESTIMATION IN WIND ENERGY: LORAS AND FOCA EXAMPLES
Küçük Resim Yok
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Turkish Soc Thermal Sciences Technology
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this work, the k and c parameters of the Weibull probability distribution function, which is generally used in the feasibility and efficiency studies of wind energy and preferred in electrical energy production, were estimated by Simulated Annealing Algorithm (SA) and Generalized Reduced Gradient Algorithm (GRG). AFunction parameters were also estimated by classical numerical methods, Least Squares Method(LMS), AJustus Empirical Moment Method(EMJ) and Lysen Empirical Moment Method(EML). When comparing the results, the coefficient of determination, the root mean square error (RMSE) and the chi-square distribution criteria(x(2)) Awere used. Wind speed frequency distributions were calculated with the estimated shape and scale parameter and compared with the measurement results. Consequently, better results can be seen from GRG algorithm than the classical numerical methods with coefficient of value of 0.0182 RMSE, determination of 0.8473, and the value x(2) of 0.0079 for Loras and with coefficient of value of 0.0066 RMSE, determination of 0.9793, and the value of 0.0011 for
Açıklama
Anahtar Kelimeler
Renewable Energy Sources, Weibull distribution parameters, Simulated Annealing Algorithm, Generalized Reduced Gradient Algorithm, Classical Numerical Methods, Wind Energy Potential
