Analysis of the Wind Turbine Selection for the Given Wind Conditions

Abstract

The aim of the current paper is to present an approach to a wind turbine selection based on an annual wind measurements. The proposed approach led to a choice of an optimal device for the given wind conditions. The research was conducted for two potential wind farm locations, situated on the north of Poland. The wind measurements pointed out a suitability of the considered localizations for a wind farm development. Six types of wind turbines were investigated in each localization. The power of the wind turbines were in the range of 2.0 to 2.5 MW and with a medium size of the rotor being in the range of 82 to 100 m. The purpose of the research was to indicate a wind turbine with the lowest sensitivity to the variation of wind speed and simultaneously being most effective energetically. The Weibull density distribution was used in the analyses for three values of a shape coefficients k. The energy efficiency of the considered turbines were also assessed. In terms of the hourly distribution of the particular wind speeds, the most effective wind turbines were those with a nominal power of 2 MW, whereas the least effective were those with the nominal power of 2.3–2.5 MW. The novelty of the proposed approach is to analyze the productivity for many types of wind turbines in order to select the one which is the most effective energy producer. The analyses conducted in the paper allowed to indicate a wind turbine which generates the highest amount of energy independently on the wind speed variation.

Site Selection of Wind Farms in Poland: Combining Theory with Reality

“…Although this study offers valuable insights, it is crucial to acknowledge its constraints. For example, economic considerations, such as the cost of building and maintaining wind farms [110,111] and social factors, such as visual impact and community acceptance [112,113], could be helpful for future models. The need for constant updating of input data could affect the final result.…”

Multi‐parameter optimization of performance and economic viability of Ferris wheel wind turbine for low wind speed regions in Africa

“…The power extractable from the wind by a wind turbine is represented by [35, 36] $$$$\begin{equation}P = \frac{1}{2}\rho A{V}^3\end{equation}$$$$where A is the area swept by turbine blades (m 2 ), R is the radius which is equal to the blade length ( l ), and V is the wind speed (m/s). $${C}_p$$, the power coefficient of each turbine, is a function of wind speed.…”

“…A payback calculation compares revenue to costs and determines the amount of time it will take to recover an original expenditure. Equation () gives the simple payback period (SPP) [35] $$$$\begin{equation}SPP = \frac{I}{{AEP*{P}_e}}\end{equation}$$$$where I is the installed wind turbine's capital cost plus the cost of civil works. The shipping and installation costs, which typically account for 20% to 30% of the total cost of a wind turbine, are included in the civil works costs.…”

Comparative analysis of different methods in estimating wind speed distribution, and evaluation of large‐scale wind turbine performance in Rahva‐Bitlis, Turkey

“…Bitlis meteorological station is in 252529 E, 4262353 N (according to UTM coordinate system) at 1794 m above sea level (Figure 1) [38]. In the literature, it is recommended to use at least 1 year's wind data in wind analysis [39,40]. The data used in this study consists of 10-min wind values measured at an altitude of 10 m between 2011 and 2012.…”