# Systematic Analysis of Wind Resources for Eolic Potential in Bangladesh
## 1 Introduction
However, Wind-Mind Internationals (WMI) conducted a baseline study for harvesting wind energy in Bangladesh. The findings reported an annual onshore and offshore wind intensity of 5 and 6 m/s, respectively, at 50 m [16]. Consequently, investigating wind for gentle speeds is important to assess to expand the potential energy for riverside regions as well with suitable height in particular location. From the above literature, two significant aspects are underlined such as seasonal variations in wind speeds and Weibull PDF for power estimation. However, these discoveries limit the study regions only to coastal areas and up to 30 m heights. Similar to WMI, the U.S. Department of Energy (USDE) reported potential wind resources and feasibility for installing power plants over Bangladesh. This empirical investigation summarized wind resources at various heights (up to 200 m) and diverse locations by numerical modelling, onsite observations (seven meteorological towers, one remote sensing, and a sonic detection), and accuracy of power generation [17]. This opens a platform to include onshore regions for potential wind resources assessment. Moreover, Global Wind Atlas (GWA) estimates wind resource and potential power mapping around the globe and sub-regions. GWA datasets also encourage employing wind and power to model energy forecasts. Both USDE and GWA resources are significant to understand mean wind and power relations for maximizing RE production in Bangladesh. As energy demands are projected to double in the future, energy sectors are required to incorporate sustainable production with emerging tools and expertise. Recent technologies in RE are constantly evolving for converting efficiencies with new materials to harvest power. For instance, in photovoltaic (PV) applications, a computationally efficient approach for a DC-DC converter is developed to detect the steady-state for PV devices [18]. This type of new finding encourages researchers to revisit potential locations for applying RE sources such as wind, solar, or hybrid energy and approximating energy production. Since most studies, particularly in this region, approximate either power density based with 50% accuracy [14] or theoretical outputs [19], this shows a gap in both energy forecasts and annual production. There are several applications on wind power prediction by either physical, statistical, or hybrid methods [20; 21; 22]. Notable studies are also found in fitting wind speeds and energy based on polynomial regression models [23; 24; 25; 26]. The approach by nonlinear polynomial functions outperforms for fitting both unimodal and multimodal wind distributions, power-curve, and forecasts by utilizing either synthetic or historical data [22; 23; 24; 25; 26]. These statistical modellings and findings also have over 90% accuracy and 0.97 for the determination of coefficients in power forecasts. Thus, in the context of Bangladesh, the above studies illustrate that RE production is inevitable to meet growing energy demands as well as to sustain the environment. As technologies are advancing and expanding significantly, continuous efforts will put RE productions forward with affordable costs for developing countries such as Bangladesh. Current enhancements in computational resources demonstrate wind power estimation for both physical and statistical techniques. As previous studies limit their findings in estimating power at coastal regions in Bangladesh, this paper aims to extend detailed and systematic analyses in onshore wind resources for energy potential. Likewise, the study also attempts to develop a general power estimation model by applying GWA datasets that can be applied for operational uses. Finally, this paper addresses how Bangladesh can lead annual energy production both onshore and offshore at a small and/or large-scale. Therefore, this current research explores wind speeds and boundary layer heights in various cities and optimizes suitable turbine hub heights.