Assessment and Characterization of Potential Locations for Wind Energy Harvest in Bangladesh

Abstract

Wind, solar, hydro, and geothermal renewable energy sources are becoming more and more important for tackling the energy issue and reducing climate change. Wind energy is regarded as one of nature's cleanest, safest, and most durable sources of energy among them. Additionally, plentiful and widely dispersed, wind energy is a desirable choice for power generation. Energy consumption is rising quickly in Bangladesh as a result of population increase and economic expansion. Due to the nation's low indigenous energy resources, imports account for the majority of its energy requirements. The article focuses on locating prospective wind energy harvesting sites in Bangladesh and investigating applications for it. To estimate the prospective sites, two extreme value distribution models—Generalized Extreme Value (GEVD) and Generalized Pareto Distribution (GPD)—have been applied. These distributions make it easier to simulate the behavior of extreme situations like high wind speeds, which are crucial for the production of wind energy. For the chosen sites, a wind rose diagram has also been used to study the directional dispersion of the wind. In order to construct wind turbines that harvest the most energy possible, it is critical to display the frequency and direction of the wind for each place in this graphic. In addition, the study has employed machine learning (ML) methods and statistical models to forecast wind speed behavior. In order to maximize the energy production of wind farms, it is essential to improve the design, operation, and maintenance of wind turbines. Using wind energy technology offers enormous potential for supplying the energy needs of emerging nations like Bangladesh. The study offers crucial insights into locating possible wind energy production sites and investigating their effective use.