Determination Of Wind Energy Potential Research Articles

Use of Small-Scale Wind Turbines in Road Lighting

In this research, it has been studied energy consumption by luminaires, used in road lighting, which is providing by small-scale wind turbines. As the application area, the Bitlis-Rahva region, which is the new settlement of the city centre of Bitlis, was chosen. For the study, the wind data at a height of 10 m representing the road lighting poles were recorded with a data logger every 10 minutes (for 1 year). In many studies in the literature, the Weibull distribution has been used in the analysis of wind data and determination of wind energy potential. It has been seen that the accuracy of this method is high and therefore the Weibull distribution is chosen for the power generation capacity of the small-scale wind turbine to be used in road lighting. The maximum likelihood method was used to determine the parameters of the Weibull density function. Considering the dimensions of the lighting poles and the loads they can carry, it was concluded that it would be appropriate to use small-scale vertical-axis wind turbines for energy generation on these poles. It has been determined that the amount of energy produced by the wind turbine on the road lighting pole is much more than the luminaire on a lighting pole will consume.

A novel stochastic model for very short-term wind speed forecasting in the determination of wind energy potential of a region: A case study from Turkey

The dominant use of fossil fuels in energy production and the great damage they have caused to both environment and human health are nowadays well-noticed. This dominant use of fossil fuels brings with it problems such as energy shortage, environmental pollution, and ecological degradation. Recently, there has been a tremendous turn towards renewable energy sources in the future energy investments of the governments. Of renewable energy sources, wind energy has located at a significant owing to its abundance, infinity, independence, reliability, and clearance characteristics. However, it is of great importance of forecasting both the amount and prices of electricity for suppliers, particularly in intraday markets, because it is a serious problem for suppliers to generate more or less electricity than they guarantee. They may face sanctions or lower profit margin risks owing to unbalances between the forecast and generate values. Accordingly, a novel model - variance sensitive exponential smoothing model - (VSES) was proposed in the present study and then compared with three well-known models in the literature namely Trigg & Leach (T-L), Pantazopoulos and Pappis (P-P) and optimized simple exponential smoothing (o-SES). Then the wind speed dataset of Çeşme district (in İzmir, Turkey) in 30-minute, 1-hour, and 3-hour time horizons are tested with these four models. In the comparison of the models, four statistical benchmarks (MAD, MSE, MAPE, and RMSE) are discussed. In the results, the RMSE value of all models is smaller than 0.9 m/s for all forecasting horizons. VSES model proposed in this study has exhibited the very satisfying MAD, MSE, MAPE, and RMSE values of 0.318 m/s, 0.183 m/s, 14.60%, and 0.427 m/s, respectively for 30-minute and 0.382 m/s, 0.258 m/s, 16.29%, and 0.506 m/s, respectively for 1-hour, respectively. On the other hand, the best model for 3-hour time horizon is achieved for the P-P model with the best MAD, MSE, MAPE, and RMSE values of 0.574 m/s, 0.543 m/s, 26.38%, and 0.729 m/s, respectively, and it is closely followed by the VSES model with 0.601 m/s, 0.614 m/s, 26.72%, and 0.775 m/s, respectively. In conclusion, it is clearly observed that the VSES model proposed in this study can be successfully applied for the determination of the wind energy potential of the regions, and effectively used in intraday markets particularly for very short-term wind speed forecasting.

Determination of Tekirdağ (Turkey) wind energy potential and evaluation of selected wind turbines in terms of techno-economic and environmental aspects

In this study, the wind energy potential of Tekirdağ was investigated obtaining the wind data from meteorology stations located in nine districts of the province and recorded hourly at 10 m altitude between the years of 2014 and 2018. Moreover, monthly average wind and Weibull and Rayleigh probability distributions, as well as hourly wind speeds, were analyzed for each district. Furthermore, monthly dominant wind directions and the ratio of dominant winds to all wind blowing numbers were determined for each district and wind speeds and wind power densities by month were compared. In addition to determination of wind energy potential, four different types of wind turbines which can be installed in the examined regions were assessed in terms of techno-economic and environmental aspects by using RETScreen Expert software. Capacity factors of selected wind turbines, initial installation costs, annual savings incomes, and annual energy amounts were determined by district. The gross greenhouse gas emission amounts that can be prevented from being released into the environment have been determined via the usage of wind turbine. Finally, the most suitable wind turbines for the districts were determined through financial sustainability analysis. Correspondingly, it has been determined that if the Enercon E2-82 wind turbine is installed in the Marmara Ereğlisi district, optimal results will be obtained. It is thought that this study will contribute to the development of the wind energy potential and planning of the wind power plants in the regions showing the similar characteristics with the examined one with regard to wind energy.

Optimum Method for Determining Weibull Distribution Parameters Used in Wind Energy Estimation

One of the well-known methods for the determination of wind energy potential is the two-parameter Weibull distribution. It is clear that the success of the Weibull distribution for wind energy applications depends on the estimation of the parameters which can be determined by using various numerical methods. In the present study, Monte Carlo simulation method is performed by using six parameters estimation method that is used in the estimation of Weibull distribution parameters such as Maximum Likelihood Estimation (MLE), Least Squares Method (LSM), Method of Moments (MOM), Method of Logarithmic Moments (MLM), Percentile Method (PM), and L-Moment Method (LM), and is compared to Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). In this study, the wind energy potential of the Meşelik region in Eskişehir was modeled with two-parameter Weibull distribution. The average wind speed (m/s) data, which are gathered in 10-minute intervals from the measuring device installed 10 meters about the ground in Meşelik Campus of Eskişehir Osmangazi University, is used. As a result of the simulation study, it has been determined that MLE is the best parameter estimation method for two-parameter Weibull distribution in large sample sizes, and LM has the closest performance to MLE. The wind speed (m/h) data of the region has been successfully modeled with two-parameter Weibull distribution and the highest average wind power density has been obtained in July as 49.38295 (W/m2) while the lowest average wind power density has been obtained in October as 19.30044 (W/m2).

Finsler Geometry for Two-Parameter Weibull Distribution Function

To construct the geometry in nonflat spaces in order to understand nature has great importance in terms of applied science. Finsler geometry allows accurate modeling and describing ability for asymmetric structures in this application area. In this paper, two-dimensional Finsler space metric function is obtained for Weibull distribution which is used in many applications in this area such as wind speed modeling. The metric definition for two-parameter Weibull probability density function which has shape (k) and scale (c) parameters in two-dimensional Finsler space is realized using a different approach by Finsler geometry. In addition, new probability and cumulative probability density functions based on Finsler geometry are proposed which can be used in many real world applications. For future studies, it is aimed at proposing more accurate models by using this novel approach than the models which have two-parameter Weibull probability density function, especially used for determination of wind energy potential of a region.

Wind Data Analysis and Wind Flow Simulation Over Large Areas

Abstract Increasing the share of renewable energy sources is one of the core policies of the European Union. This is because of the fact that this energy is essential in reducing the greenhouse gas emissions and securing energy supplies. Currently, the share of wind energy from all renewable energy sources is relatively low. The choice of location for a certain wind farm installation strongly depends on the wind potential. Therefore the accurate assessment of wind potential is extremely important. In the present paper an analysis is made on the impact of significant possible parameters on the determination of wind energy potential for relatively large areas. In the analysis the type of measurements (short- and long-term on-site measurements), the type of instrumentation and the terrain roughness factor are considered. The study on the impact of turbulence on the wind flow distribution over complex terrain is presented, and it is based on the real on-site data collected by the meteorological tall towers installed in the northern part of Bulgaria. By means of CFD based software a wind map is developed for relatively large areas. Different turbulent models in numerical calculations were tested and recommendations for the usage of the specific models in flows modeling over complex terrains are presented. The role of each parameter in wind map development is made. Different approaches for determination of wind energy potential based on the preliminary developed wind map are presented.

Determination of wind energy potential and its implementation concept for the electricity market in the Vojvodina region (north Serbia): An overview

Determination of wind energy potential and its implementation concept for the electricity market in the Vojvodina region (north Serbia): An overview

Determination of wind energy potential in the Mwingi-Kitui plateau of Kenya

Wind energy can be used to enhance access to affordable energy to the rural poor owing to its cost effectiveness, enormity of availability and non-polluting nature. Kenya is however yet to embrace this technology due to non-availability of the resource data for most parts of the country. This study endeavors to provide the missing data and investigate the feasibility of employing Small Wind Turbine Generators (SWTG) for provision of modular power to the arid rural Mwingi-Kitui plateau where access to electricity is very low yet the land is flat with visible effects of wind on trees such as tree flagging. The region lies between the earlier studied coast and north eastern parts of the country both of which have good wind potential, raising the prospects of finding sustainable quality wind in it. Ten-minute interval wind speed data was collected at 20 m and 40 m elevations above the ground for a period of one year and analyzed to portray the vertical wind shear exponent, mean wind speed (daily, monthly and annual) variations, wind gusts, probability distributions, directional data and wind power density over the study period. The study gave annual mean wind speed at the 20 m and 40 m heights above the ground as 4.24 m/s and 4.88 m/s respectively leading to vertical wind shear exponent (α) of 0.20. Wind speeds at 40 m hub height and above rated above 3.5 m/s cut-in speed with flow prevalently from south east direction for most of the year. The maximum available wind power densities at 60 m, 80 m and 100 m were 84.3 W/m2, 100.5 W/m2 and 115 W/m2 respectively. These findings reflect characteristics suitable for operation of small wind turbine electricity generators.

Determination of Wind Energy Potential in Kirklareli-Turkey

Wind energy has become an important source that has begun to be used for energy in all over the world in recent years. In this study, by examining the wind potential of the western region of Turkey in detail, an analysis was made. The data were provided by the State Meteorology Affairs Kirklareli Office. In Kirklareli region, the energy produced on a 7.8 MW wind plant pattern constituted a model through ANFIS (Adaptive-Network Based Fuzzy Inference Systems). Then, with Wind Atlas Analysis and Application Program (WASP) and by counting the rates of capacity usage, wind energy potential was examined. In the light of the data obtained in the study, it has been determined that the method is quite successful and Kirklareli is suitable for wind plant investment.

Determination of Wind Energy Potential and Wind Speed Data in Bishkek, Kyrgyzstan

Wind speed is the most important parameter in the design and study of wind energy conversion systems. Probability density functions, such as the Weibull and Rayleigh, are often used in wind speed and wind energy analyses. In this study, statistical methods were used to analyze the wind speed data of Bishkek in the northern region of Kyrgyzstan. Measured daily time series of wind speed data were obtained from the State Meteorological Station in Bishkek, Kyrgyzstan, over a three-year period from 2003 to 2005. The probability density distributions are derived from the time series data and the distributional parameters are identified. Two probability density functions are fitted to the measured probability distributions on a monthly, seasonally, and yearly basis. The wind energy potential of the location is studied based on the Weibull and the Rayleigh models.