An empirical investigation into wind energy modeling: a case study utilizing five distributions and four advanced optimization methods

Abstract

Accurate wind energy modeling is challenging in wind power planning and operation. The main task in modeling wind energy is specifying wind speed distribution. Therefore, selecting compatible functions for describing wind speed distribution is crucial. This chapter presents five distribution functions based on four optimization methods to estimate wind speed patterns. The employed distributions are Rayleigh, Weibull, Gamma, Burr type XII, and generalized extreme value. At the same time, genetic algorithm, gray wolf optimization, particle swarm optimization, and whale optimization algorithm are the optimization methods. Besides, seven statistical descriptors, four error criteria, and power density are utilized to compare these methods. The net fitness test is also presented to identify the best matching estimation method. Catalca in the Marmara region in Istanbul, Turkey, was selected to perform the analysis. Finally, this chapter provides many significant findings to accurately model wind energy at any site. © 2023 Elsevier Inc. All rights reserved.