Health condition monitoring in wind turbine motor plays an extremely important role, as these devices are highly in demand in the energy sector, especially in renewable energy and are vulnerable to both mechanical and electrical failures, more often. As such, timely identification of internal faults in these electrical devices goes a long way in productive operations by reducing the maintenance time and costs, i.e. such internal faults, if identified at an early stage, repaired or replaced timely will aid in reliable renewable energy supply. Taking this into consideration, automated continuous monitoring of wind turbine machine is a key to making this process more effective. A web application is built in the proposed research enabling quick monitoring of faults in wind turbine motor from a remote access workstation, like a control room. An experimental setup of wind turbine motor is made and data set of stator currents from both healthy and faulty conditions as well as the power spectral density from the motors were used for condition monitoring with a web interface application. Insulation failure in stator winding is a most commonly occurring electrical failure in machines. As such in the current research stator current features from the experimental machine are used for requirement analysis under both healthy and faulty operating conditions. Among the stator insulation failure most commonly occurring stator turn-to-turn faults are taken into consideration in the current research with percentage of insulation failure varying between 25% to 75%. Fault identification is done with the help of wavelet based artificial neural network analysis at the back end and the interface displays the details in the form of dashboards, with the program mainly featuring three dashboards for the unit, stator, rotor, and components in total. Using interactive visualizations, the user will be able to obtain more in-depth knowledge about the suspected faults in the system and its components, and help to take the necessary action. i.e. whether the wind turbine motor needed to be repaired or replaced depending on the vulnerability of the fault. The application also has been experimented with handheld devices by hosting the application on local host and tunneling it over the web. Interactive visualization also includes information about the working conditions of the electrical machine, such as balanced, unbalanced, and failure conditions. Thus internal electrical fault in a wind turbine induction machine can be remotely analyzed, checked and cure can be suggested with a proper online health condition monitoring system.

In this paper, the stochastic optimization of a horizontal-axis composite wind turbine blade is performed. Wind energy has become widely popular in recent decades as an alternative source of energy and many studies have been devoted to finding an optimal wind turbine blade using deterministic optimization. However, the actual responses of the wind turbine blade such as power generation are affected by the stochastic nature of wind, uncertainties in material properties and modeling parameters, and so on. This can have an undesirable impact on the performance and reliability of blades, which demands the consideration of uncertainties during optimization. To this end, a surrogate-based stochastic optimization of a wind turbine blade considering the influence of randomness in wind speed on power generation was studied. A slight gain in average power over the baseline blade was obtained and it demonstrated the promise of the presented framework for the design of wind turbine blades.

This paper presents a comparison of low- and high-fidelity structural analyses of a 10 MW offshore floating wind turbine rotor blade. For low-fidelity analysis, BeamDyn as a part of the OpenFAST toolset is used. For high-fidelity analysis, the Toolkit for the Analysis of Composite Structures (TACS) finite element method is used. First, several numerical examples with reference solutions from the literature are investigated to compare the accuracy and efficiency of the low- and high-fidelity structural models. Next, the DTU 10 MW reference wind turbine blade is analyzed using both the low- and high-fidelity methods. The bending response of the blade is analyzed. The results show that the high-fidelity model agrees with low-fidelity results and reference solutions. The high-fidelity model represents the deformations more accurately than the low-fidelity model and therefore is appropriate for structural analysis of complex wind turbine blade shapes.

This research, a part of more extensive research, presents pre-feasibility and unit sizing analysis of a hybrid system equipped with renewable energy resources in Tabriz, Iran (46°26/E, 38°06/N). This case study examines a GSM telecommunication station as a stand-alone load system. Renewable energy resources include photovoltaic (PV), a wind turbine as primary resources and fuel cell, and a battery stack as backup and energy storage systems, while an electrolyzer is used to provide the required hydrogen in the fuel cell system. Feasibility analysis and unit sizing are conducted based on climatic data such as solar irradiance and wind speed to derive an optimal model during the study. HOMER software is used to simulate the feasibility analysis, measure the size, and optimize the system. The results showed that the hybrid system performs cost-effectively. According to wind energy data and fuel-cell costs, sensitivity analysis is conducted. The load is a stand-alone GSM station that consumes 60kW per day with a maximum of 3.8kW per hour. This analysis showed that wind, PV, electrolyzer, battery, and fuel cells are not currently the best solutions. Shortly, according to improved prediction in fuel-cell technology, it is expected that this source as a backup will be the best option because it has decreased fuel-cell costs up to 65 percent. Some criteria such as size, application, and cost, have been mainly examined. These results provide excellent opportunities for this hybrid system. The result shows using fuel cells in a hybrid system is not affordable by considering current fuel cell price, and the main suggestion hybrid system configuration is PV, wind turbine, and battery, while for the nearby location of Tabriz by decreasing wind speed, using wind turbines is not feasible and more PV array should be added to the system.

Sustainable energy utilization on Mars is fundamental for the success of habitation on Mars. The two sustainable energy sources for In-Situ Resource Utilization (ISRU) with the highest potential for implementation on Mars are solar and wind. Unfortunately, the former cannot provide a reliable continuous source of energy for multiple reasons. Accordingly, wind energy is presented as a viable solution, or as a strong potential complement to solar energy. The authors investigate different sites on Mars by evaluating the available wind resources to select the most feasible location in terms of energy yield and other critical habitability criteria. This work is conducted by applying the General Circulation Model (GCM) simulation, this particular analysis of wind harvesting feasibility on Mars will be studied by employing the Mars Climate Database (MCD) model. In addition, this novel research provides a systematic approach for future energy harvesting projects on Mars. Moreover, it evaluates different potential wind turbine design concepts applicable for the Martian ISRU. The results of this research lay the foundation for future energy utilization necessary for habitation to thrive, as well as it will be a key for future exploration missions. Ultimately, this will enrich our understanding of wind turbine systems.

Wind turbines can create turbulence and downstream wakes which can introduce generation losses of downstream impacted turbines. These downstream turbine-induced losses are due to two different conditions. The first is from power-producing rotating blades of upstream wind turbines agitating the subsequent downstream wind in a cork-screw like manner. The second is from non-rotating, non-operational, non-power-generating wind turbines. These non-operating turbines may be under scheduled service shutdown, or rendered non-functional due to longer-term or permanent mechanical problems. In this work CFD was used to study downstream turbulence and wakes of a utility-scale, non-operational three-blade horizontal axis wind turbines (HAWT). A flow field was constructed using an unstructured grid around a HAWT (rotor hub elevation of 80 meters and a blade length of 40 meters). Various wind velocities were studied up to 25 meters per second. Incompressible flow was used to assess downstream turbulence using a three-dimensional steady state and unsteady state SST k-ω (two equation) turbulence model. Different blade positions with respect to angle of attack (α) were studied, with a 4 degree angle of attack reported here. Pressures and velocities for distances of 100 meters in front and 500 meters downstream from the wind turbine are reported.

The phenomena of over-cooling commonly exist in data center thermal environment, resulting in a substantial waste of energy. Previous study has proposed a solution that implementing a wind turbine in a raised-floor data center by which the over-provisioned airflow can be utilized. The impingement of the computer room air-conditioner (CRAC) flow on the plenum walls (e.g., the floor slab) may yield key causes of the energy losses. Therefore, studying the effects of the wind turbine on the CRAC flow in the data center is necessary. Here, the data center and wind turbine were simulated and modeled using Computational Fluid Dynamics (CFD) package. In this research, the numerical measure of the pressure distributed on the floor slab was numerically measured as key observations. The positioning and axial induction factors of the wind turbine were treated as the major research parameters. The consequence illustrates that implementing a wind turbine with well-tuned axial induction factor and operating height might be capable of effectively decreasing the CRAC flow impingement and increasing the turbine power efficiency. This research may provide meaningful references for effective wind turbine applications for data center energy efficiencies.

This paper presents a comparison of low- and mid-fidelity aerodynamic modelling of floating offshore wind turbine rotors. The low-fidelity approach employs the conventional Blade Element Momentum theory implemented in AeroDyn of OpenFAST . This model ignores the aerodynamic interactions between different blade elements, and the forces on the blade are determined from the balance between momentum theory and blade element theory. With this method, it is possible to calculate the aerodynamic performance for different settings with low computational cost. For the mid-fidelity approach, the Actuator Line Modeling method implemented in turbinesFoam (an OpenFOAM library) is used. This method is built upon a combination of the blade element theory for modeling the blades, and a Navier-Stokes description of the wake flow field. Thus, it can capture the wake dynamics without resolving the detailed flows near the blades. The aerodynamic performance of the DTU 10 MW reference wind turbine rotor is studied using the two methods. The effects of wind speed, tip speed ratio, and blade pitch angles are assessed. Good agreement is observed between the two methods at low tip speed ratios, while the Actuator Line Modeling method predicts slightly higher power coefficients at high tip speed ratios. In addition, the ability of the Actuator Line Modeling Method to capture the wake dynamics of the rotor in an unsteady inflow is demonstrated. In the future, the multi-fidelity aerodynamic modules developed in this paper will be integrated with the hydro-kinematics and hydro-dynamics of a floating platform and a mooring system, to achieve a fully coupled framework for the analysis and design optimization of floating offshore wind turbines.

The above referenced paper has been removed from publication. (March 10, 2020) Copyright © 2020 by ASME

Upstream wind turbine turbulence can negatively impact the aerodynamic performance of downstream wind turbines. It is important to understand and evaluate the characteristic nature of this inflowing turbulence. Computational Fluid Dynamics (CFD) is a foundational analytical tool used to help predict and describe both boundary layer behavior and the resulting downstream turbulence for both these upstream turbines and the impacted downstream turbines. Increasing the predication accuracy of turbulence models, particularly at the higher Reynolds number regimes, commonly encountered at the outer radius of wind turbine blades, remains a fundamental consideration in such CFD analysis. The work discussed here focuses on understanding how CFD simulations can be impacted by basic CFD approaches and configurations. Commonly use unstructured grids and incremental positive angles of attack around the well-studied NACA0012 airfoil were used to assess how these basic set-up parameters can influence CFD turbulence results. Navier-Stokes equations were solved for incompressible flow to assess downstream turbulence using the SST k-ω (two equation) turbulence model within ANSYS Fluent (SIMPLE solution method). Two airfoil configurations with respect to angle of attack (α) were of interested and studied, with one configuration defined as “fixed-position” and the second configuration defined as “changed-position”. Fixed-position refers to a single common airfoil/grid configuration and changing incoming u x , v y velocity vectors to yield different angle of attack (α) values. Changed-position refers to a utilizing a single u x velocity vector and physically rotating the impacted airfoil in the computational field to yield different angles of attack. A two-dimensional unsteady state SST k-ω turbulence model was used at a Reynolds of 3.0 × 10 6 . The resulting data from the system setup models studied here (fixed and changed-positions) were successfully validated by comparing the computed lift and drag coefficients at these varying α values to common values found in literature. Downstream pressure contours, along with U x and V y , and net-velocity contours at various distances from 1.5 cord lengths up to 12.0 cord lengths from the leading edge of the airfoil at incremental angles of attack were studied. The authors review how such variations in rudimentary approaches impact the CFD downstream output results.

Wind farm energy production optimization has received significant attention in recent years. Much of this effort had been focused on optimizing positions of wind turbines within a wind farm domain during the design and planning stage. Optimization of wind turbine positions can reduce wake interactions of upstream turbines. In addition to optimizing turbine positions to reduce wake interactions, prior studies have shown that optimizing yaw and pitch angles can improve energy production as upstream wakes yaw away from downstream turbines. However, yaw angle optimization at the wind farm level has been difficult due to lack of low-fidelity wake model for simulating yawed wakes. Recently, an analytical wake model capable of simulating yawed turbine wakes had been developed, which enable wind farm-scale yaw optimization. In this work, a binary quadratic programming model problem formulation has been developed to optimize yaw angles of wind farms. Yaw optimization of two position-optimized layouts available in the literature were performed to study the potential of yaw optimization. In particular, we set out to understand how layout and wind farm density affect yaw optimization potential. An optimized layout of 39 turbines with 40m rotor diameter in a 2km by 2km domain was used in this study. For this wind farm, yawing optimization only improved power production by ∼1.5% under favorable wind directions. However, as wind farm power density increases by increasing rotor diameter to 60m and 80m, power production improved by ∼5% and ∼10% respectively, under favorable wind directions. Finally, another yaw optimization was performed on an optimized layout with 48 turbines of 82m rotor diameter in a 4km by 4km domain using the proposed model formulation. Under favorable wind directions, yaw angle optimization improved performance by ∼4%. The results show that yaw optimization can improve power production in the same order of magnitude as layout optimization, and that it should be considered in addition and/or in tandem to layout optimization.

A weather data collection study is currently conducted using a renewable energy training system. The system is composed of a LabVolt trainer, two sun tracking photovoltaic solar panels and a small wind turbine. The LabVolt training system is located in one of the McCoy School of Engineering laboratories, the solar panels and the wind turbine are located in the neighborhood of the Engineering building at Midwestern State University in Wichita Falls, Texas. A set of meteorological data collecting outdoor sensors to monitor the impact of weather conditions on the power generation of the sun-tracking photovoltaic solar panels and the wind turbine have been installed on the building roof. Weather parameters such as atmospheric temperature, pressure, humidity, and rainfall are monitored using a Davis Vantage Pro 2 data collecting system. A number of LabVIEW data acquisition cards and signal processing modules are used to monitor the sun-tracking photovoltaic solar panels’ output voltage, the wind turbine output voltage, the atmospheric temperature, the solar irradiance, and the wind direction, speed, and RPM. A voltage divider has been built to step down the 90V DC voltage produced by the solar panels to 12V DC voltage required for the trainer electrical circuits. A LabVIEW data processing program is used to create instantaneous graphic displays of the collected data on a monitoring screen. The LabVolt trainer is equipped with two charge controller electronic devices, one is used for the sun tracking photovoltaic solar panels, and one is used for the wind turbine. They are used to control the flow of electrical energy through a set of electrical loading devices and a set of storages batteries. Additionally, the LabVolt trainer is equipped with two kilowatt-hour-meters counting the electrical energy consumed by the electrical loads. The trainer is also equipped with two inverters transforming the 12 V DC voltage collected from both energy producing devices to 120 V that can be used by the electrical loading devices. A brief description of all used electronic components and devices is provided in the paper, as well a detailed experiment set-up with a procedure to run them. The project has been divided into three consecutive phases. The first phase dealt with connecting the solar panels, wind turbine, and data collecting sensors to the LabVIEW data acquisition software. The second phase is currently dealing with setting up the trainer solar and wind electricity providing circuits. In the third upcoming phase, it is expected that the data collected by the sensors will be gradually archived using Excel files and analyzed for weather data correlation purposes. It is also expected that the training system will be used to teach upcoming mechanical engineering students about how to set up an independent renewable energy system and the necessary equipment required to run it.

Inflowing turbulence influences aerodynamic behaviors of the impacted geometries, and are important considerations for systems such as sailing vessels, wind turbines, ground vehicles, and aircraft. It is important to understand and evaluate the characteristic nature of this turbulence. Computational Fluid Dynamics (CFD) is now a foundational analytical instructional tool used to help educate both undergraduate and graduate engineering students on how predict and describe both boundary layer behavior and the resulting downstream turbulence. Increasing the predication accuracy of turbulence models, particularly at higher Reynolds number regimes remains a fundamental consideration in CFD analysis. The work discussed here focuses on understanding how CFD simulations can be impacted by basic CFD approaches and configurations. Commonly use unstructured grids and incremental positive angles of attack around the well-studied NACA0012 airfoil were used to assess how these basic set-up parameters can influence CFD turbulence results. Navier-Stokes equations were solved for incompressible flow to assess downstream turbulence using the SST k-ω (two equation) turbulence model within ANSYS Fluent (SIMPLE solution method). Two airfoil configurations with respect to angle of attack (α) were of interested and studied, with one configuration defined as “fixed-position” and the second configuration defined as “changed-position”. Fixed-position refers to a single common airfoil/grid configuration and changing incoming U x , V y velocity vectors to yield different angle of attack (α) values. Changed-position refers to a utilizing a single U x velocity vector and physically rotating the impacted airfoil in the computational field to yield different angles of attack. A two-dimensional unsteady state SST k-ω turbulence model was used at a Reynolds number of 3.0 × 10 6 . The resulting data from the system setup models studied here (fixed and changed-positions) were successfully validated by comparing the computed lift and drag coefficients at these varying α values to common values found in literature. Downstream pressure contours, along with U x and V y net-velocity contours at various distances from 1.5 cord lengths up to 12.0 cord lengths from the leading edge of the airfoil at incremental angles of attack were studied. The authors review how such variations in rudimentary approaches can impact the CFD downstream output results.

This work presents the design and analysis of a novel wind energy harnessing system that makes use of wind defecting structures to increase the ambient wind speed at geographic locations with relatively low wind speed. The system however reacts to highspeed wind conditions by altering the profile of the wind defecting structure in order to eliminate wind speed amplification attribute of the system, thereby protecting the wind turbine assembly at high speed wind conditions. Although increasing the wind speed is advantageous at geographic locations that the wind speed is typically low; however, from times to time, there could be sustained high-speed wind conditions at the same locations that may damage the wind turbine systems that take advantage of the wind defecting structures. The present work disclosed a wind deflecting structure formed by at least two sail-like partial cylindrical structures that are supported atop of a tower-like foundation in a symmetric arrangement, where one or more wind turbines can be installed in the space between the two partial cylinders. The two partial cylinders, each substantially in form a quarter cylinder is made of plurality of parallel ribbed-like bars, hereafter referred to as “bars” with a flexible thin material that are mechanically supported by the bars. The bars are oriented in a direction perpendicular to the ground; allowing the wing deflecting structures to accept horizonal axis or vertical axis turbines in the space between them. The function of the bars is to allow the thin material, attached to them, to assume a curved configuration substantially in the form of a quarter cylinder. The apparatus is equipped with wind speed monitoring devices, and power source and power transmission means, such as cable-pulleys, chain-sprockets, gears, or mechanical linkages that all work in concert to deploy or stow the thin material along the vertical rods depending to the magnitude of the prevailing wind speed. Preliminary computational fluid dynamics analyses have shown that the wind deflecting structure proposed here in amplifies the wind speed by a factor of 1.65.

Understanding and minimizing the uncertainties in the wind energy field is of high importance to reduce the reliability risks and financial risks of wind farm projects. The present work aims to observe the levels of uncertainty in modeling the wake effect by attempting to perform statistical inference of a wake parameter, the wind speed deficit. For this purpose, an uncertainty propagation framework is presented. The framework starts by randomly sampling mean wind speed data from its probability density function (PDF), that is fed an inflow model (TurbSim), resulting in random full-flow fields that are integrated into an aeroelastic model (FAST), which results in the variability of the power and thrust coefficients of a wind turbine. Such coefficients and wind data, finally, fed the wake engineering model (FLORIS). The framework ends with the determination of the 95% coefficient intervals of the time-averaged wind speed deficit. The results obtained for the near and far wake regions introduce fundamentals in estimate the uncertainty in wind speed deficit of a single wind turbine wake and concludes that a systematic uncertainty quantification (UQ) framework for wind turbine wakes may be a useful tool to wind energy projects.

The root region of small wind turbines experience low Reynolds number (Re) flow that makes it difficult to design airfoils that provide good aerodynamic performance and at the same time, provide structural strength. In the present work, a multi-objective genetic algorithm code was used to design airfoils that are suitable for the root region of small wind turbines. A composite Bezier curve with two Bezier segments and 16 control points (11 of them controlled) was used to parametrize the airfoil problem. Geometric constraints including suitable curvature conditions were enforced to maintain the airfoil thickness between 18% and 22% of chord and a trailing edge thickness of 3% of chord. The objectives were to maximize the lift-to-drag ratio for both clean and soiled conditions. Optimization was done by coupling the flow solver to a genetic algorithm code written in C++, at Re = 200,000 and for angles of attack of 4 and 10 degrees, as the algorithm was found to give smooth variation of lift-to-drag ratio within such a range. The best airfoil from the results was tested in the wind tunnel as well as using ANSYS-CFX. The experimental airfoil had a chord length of 75 mm and was provided with 33 pressure taps. Testing was done for both free and forced transition cases. The airfoil gave the highest lift-to-drag ratio at an angle of 6 degrees with the ratio varying very little between 4 degrees and 8 degrees. Forced transition at 8% of chord did not show significant change in the performance indicating that the airfoil will perform well even in soiled condition. Fixed trailing edge flaps (Gurney flaps) were provided right at the trailing edge on the lower surface. The lift and drag behavior of the airfoil was then studied with Gurney Flaps of 2% and 3% heights, as it was found from previous studies that flap heights of 1% or greater than 3% do not give optimum results. The flaps considerably improved the suction on the upper surface and also improved the pressure on the lower surface, resulting in a higher lift coefficient; at the same time, there was also an increase in the drag coefficient but it was less compared to the increase in the lift coefficient. The results indicate that Gurney flaps can be effectively used to improve the performance of thick trailing edge airfoils designed for the root region of small wind turbines.

The current trend in the wind power market is to develop large diameter rotors in order to maximize the power extraction from the wind. Those rotors exhibit issues related to blade deflection and structural integrity that can be mitigated implementing design variations that were present on the early wind turbine designs, such as rotors with less than three blades located behind the tower in downwind configuration. This work assesses the aerodynamic performance of a downwind two-bladed wind turbine based on CFD simulations coupled with the Actuator Line Model (ALM). This design is compared with the MEXICO project upwind three-bladed wind turbine, for which experimental data is available. The simulations showed good agreement with measurements especially upstream the rotor and for higher inlet velocities. Furthermore, the downwind configuration was successfully modeled using ALM and the performance prediction of the turbines was physically accurate since realistic variations were obtained between the evaluated wind turbines and none of their performance coefficients exceeded Betz theoretical limit.

A concept for an innovative wind turbine blade with an actively transformable twist distribution is presented. A simulation model demonstrates that adapting the blade twist distribution can increase the aerodynamic efficiency during partial-load operation. A blade concept consisting of a rigid spar that is surrounded by deformable modular shells is also proposed. The outer shells are assumed to be produced using additive manufacturing (AM) technology. Integrated features enabled by the AM process tune the stiffness, and thus the degree of flexibility for each surrounding segment. The unique local stiffness and the placement of actuators establishes a nonlinear twist angle distribution (TAD). An optimal design procedure is devised for setting the stiffness and actuator locations. It maximizes the aerodynamic efficiency for a discrete range of wind speed. The blade performance is quantified using data acquired from the National Renewable Energy Laboratory (NREL) Aerodyn software. A computer cluster is used to facilitate this process. It must consider the TAD for the range of wind speed that corresponds to the partial-load operation. The design procedure first establishes the TAD geometry based on the theoretical aerodynamic modeling. The TAD geometry is then passed to a mechanical design algorithm. At this point, the actuator positions are set, and the stiffness ratios of the adaptable shells are defined using the objective function. It minimizes the amount of deviation between the actual TAD and that found in the aerodynamic analysis. The free-shape TAD is determined in the final step. This is the shape of the blade when no actuation force is applied to the shells. This shape is then selected to minimize the amount of deflection needed to shape the TAD between its extreme positions. A case study demonstrates the ability of the blade and the proposed design process. The study indicates that a blade with five actuators can achieve the full range of TAD motion. The final solution shows that the adaptive TAD can increase the efficiency by 3.8 and 3.3%, respectively, at the cut-in and rated speeds.

The Archimedes wind turbine boasts an innovative blade design with the potential of harvesting energy from wind with much more efficiency. The blade design utilizes both lift and drag forces, and boasts several other advantages over conventional horizontal axis and vertical axis wind turbines, which implies higher power production efficiency and a possibility of being used in urban areas with attendant low wind speed regimes for small scale power generation, being more portable. However, there exists a dearth of experimental reports on the Archimedes wind turbine besides CFD simulations, to observe and study its real-life performance and power production potential. This paper is an experimental report on the design and wind test of the Archimedes wind turbine prototype, together with calculations made to gauge its tip speed ratio, power output and energy production potential. To show the viability of the prototype, the power produced is used to charge a HTC Desire cell phone, which proves that it can be relied upon to meet the title objective of small scale power storage with a power bank. Results are thereafter compared to other published work and show relatively good agreement. Minor deviations are attributed to the challenges encountered during the fabrication process.

There is a growing need for an environmentally friendly source of energy that can replace the conventional fossil fuel energy. This is because the effects of global warming is becoming very obvious, as evidenced by the severe flooding that occurred in the U.S. in 2017 1 . Two notable solutions to this dilemma are wind and solar energy. Solar powered devices derive their energy from the sun, hence, the amount of energy is severely limited during the cold months of the year when solar intensity is typically low. Wind energy, on the other hand is most prevalent during this cold months when the wind speed is typically higher. The aim of this research is therefore to conduct a comprehensive assessment of wind energy potential in Michigan City, Indiana, United States. This information will allow homeowners and investors with interest in alternative energy to make critical decisions in this regard. The study was conducted using wind speed data collected over a five-year period from 2012 to 2016. In this work, we have also determined the best method for evaluating the Weibull parameters (shape and scale factors) for wind data analysis. The site average wind speed ranged from 4m/s to 9m/s with a peak in the winter months and minimum in the summer months. The wind speed with the maximum energy at the hub height varied between 5.84 m/s in August 2016 to 12.79 m/s in October 2012 with annual average speeds between 8.85 and 9.35 m/s and a five-year average of 9.13 m/s. The prevailing wind speed was within the range of 4–8m/s and strongest on the Southern part of the site especially in the South Southeastern direction. Consequently, siting a wind turbine on the Southern part of the City would generate more energy than on any other direction. Among the turbines analyzed, ITALTECH 250 will yield the maximize energy production with a capacity factor of 0.385 and average annual energy production of 840 MWh/yr. The results presented in this work proves the great potential for investments in wind energy in Michigan City.