Enhancing The Wind Turbine Blade Angle Control Using Pelican Optimization Algorithm

Abstract

Electricity demand is increasing every day. Because of the increasing advancements in numerous living areas such as industry, agriculture, and commerce, the necessity for efficient energy sources has become critical. Renewable energy sources are the ideal option because they are both clean and inexpensive sources of electricity. One of the renewable energy technologies employed in this article is the wind turbine system, which relies on tracking the maximum power that the system can produce based on the wind speed value. This study proposes a new optimization method, the Pelican Optimization Algorithm (POA), which aims to improve blade angle control. Comparison of two optimizations. POA optimization and teaching learning-based optimization (TLBO) will be illustrated by tuning the Adaptive Proportional Integral Controller (API). The results show the superiority of POA optimization over TLBO optimization.