Abstract:
The method that aims to operate the wind energy system (WES) at the maximum power point (MPP) is called the maximum power point tracking (MPPT) method in the literature. The grey wolf optimization (GWO) is one of the newest population-based meta-heuristic methods, and its performance as an MPPT algorithm in WESs has not been extensively studied yet. In this study, the standard GWO algorithm has been modified considering the requirements of WES, so that the system can reach the MPP quickly and stably, thereby improving the system's efficiency. Moreover, the performance of the proposed method is examined comparatively with the well-known MPPT methods via simulation and experimental studies for many possible scenarios. It is demonstrated that the proposed modified GWO (MGWO) performance is better than the classic and modified perturb and observe methods. The results have also been compared with the Fibonacci Search (FS) and Golden Section (GS) Search-based MPPT algorithms newly presented in the literature for WES. Although the results of FS, GS, and MGWO-based MPPT algorithms are very close to each other, it has been observed that FS has a slightly better performance.
Description:
Bu yayın 06.11.1981 tarihli ve 17506 sayılı Resmî Gazete’de yayımlanan 2547 sayılı Yükseköğretim Kanunu’nun 4/c, 12/c, 42/c ve 42/d maddelerine dayalı 12/12/2019 tarih, 543 sayılı ve 05 numaralı Üniversite Senato Kararı ile hazırlanan Sakarya Üniversitesi Açık Bilim ve Açık Akademik Arşiv Yönergesi gereğince açık akademik arşiv sistemine açık erişim olarak yüklenmiştir.