This paper studies erosion at the tip of wind turbine blades by considering aerodynamic analysis, modal analysis and predictive machine learning modeling. Erosion can be caused by several factors and can affect different parts of the blade, reducing its dynamic performance and useful life. The ability to detect and quantify erosion on a blade is an important predictive maintenance task for wind turbines that can have broad repercussions in terms of avoiding serious damage, improving power efficiency and reducing downtimes. This study considers both sides of the leading edge of the blade (top and bottom), evaluating the mechanical imbalance caused by the material loss that induces variations of the power coefficient resulting in a loss in efficiency. The QBlade software is used in our analysis and load calculations are preformed by using blade element momentum theory. Numerical results show the performance of a blade based on the relationship between mechanical damage and aerodynamic behavior, which are then validated on a physical model. Moreover, two machine learning (ML) problems are posed to automatically detect the location of erosion (top of the edge, bottom or both) and to determine erosion levels (from 8% to 18%) present in the blade. The first problem is solved using classification models, while the second is solved using ML regression, achieving accurate results. ML pipelines are automatically designed by using an AutoML system with little human intervention, achieving highly accurate results. This work makes several contributions by developing ML models to both detect the presence and location of erosion on a blade, estimating its level and applying AutoML for the first time in this domain.
In recent times, the application of small-scale horizontal axis wind turbines (SHAWTs) has drawn interest in certain areas where the energy demand is minimal. These turbines, operating mostly at low Reynolds number (Re) and low tip speed ratio (λ) applications, can be used as stand-alone systems. The present study aims at the design, development, and testing of a series of SHAWT models. On the basis of aerodynamic characteristics, four SHAWT models viz., M1, M2, M3, and M4 composed of E216, SG6043, NACA63415, and NACA0012 airfoils, respectively have been developed. Initially, the rotors are designed through blade element momentum theory (BEMT), and their power coefficient have been evaluated. Thence, the developed rotors are tested in a low-speed wind tunnel to find their rotational frequency, power and power coefficient at design and off-design conditions. From BEMT analysis, M1 shows a maximum power coefficient (Cpmax) of 0.37 at λ = 2.5. The subsequent wind tunnel tests on M1, M2, M3, and M4 at 9 m/s show the Cpmax values to be 0.34, 0.30, 0.28, and 0.156, respectively. Thus, from the experiments, the M1 rotor is found to be favourable than the other three rotors, and its Cpmax value is found to be about 92% of BEMT prediction. Further, the effect of pitch angle (θp) on Cp of the model rotors is also examined, where M1 is found to produce a satisfactory performance within ±5° from the design pitch angle (θp, design).
In this study, the performance of a new wind turbine design derived from a conventional Savonius turbine is optimized by numerical simulation. The new design consists of three blades without passage between them (closed center). The coupling between the CFD codes (ANSYS Fluent) and the optimizer (OPAL) is used through an automatic procedure in-house codes, as documented, for example, in Thévenin et al.’s Optimization and Computational Fluid Dynamics (2008). A single-objective function (output power coefficient, Cp) is considered as the target of the optimization technique and the shape of the blade as an optimization parameter and relies on evolutionary algorithms. An optimal solution can emerge from this optimization study. By comparison between regular design (semi-cylindrical shape blades) and the optimal configuration, a considerable improvement (up to 7.13% at λ = 0.7) of the optimal configuration performance can be obtained in this manner.
In this work, a 3D computational model based on computational fluid dynamics (CFD) is built to simulate the aerodynamic behavior of a Savonius-type vertical axis wind turbine with a semi-elliptical profile. This computational model is used to evaluate the performance of the wind turbine in terms of its power coefficient (Cp). Subsequently, a full factorial design of experiments (DOE) is defined to obtain a representative sample of the search space on the geometry of the wind turbine. A dataset is built on the performance of each geometry proposed in the DOE. This process is carried out in an automated way through a scheme of integrated computational platforms. Later, a surrogate model of the wind turbine is fitted to estimate its performance using machine learning algorithms. Finally, a process of optimization of the geometry of the wind turbine is carried out employing metaheuristic optimization algorithms to maximize its Cp; the final optimized designs are evaluated using the computational model for validating their performance.
Energy needs in Indonesia continue to increase, while the availability of non-renewable energy sources is decreasing and is exacerbated by the increasing use of fuels that are not environmentally friendly, so efforts are needed to find alternative uses of renewable energy that are renewable and environmentally friendly. The Cirebon coast has good wind conditions which can be used to create renewable energy sources through the wind. This study aims to utilize the energy that is already available by designing a horizontal wind turbine blade. The method used starts from literature study, selecting airfoils, analyzing data, selecting the best airfoils, analyzing the best airfoils and ending with design drawings. The initial data used as the initial design is the Cirebon City wind data which has the highest average wind speed of 9 m/s. This study designed a horizontal wind turbine blade using QBlade Software with 3 types of NACA, NACA 4415, 6412 and 6415. NACA 6415 has a power coefficient of 0.40%, the highest coefficient is then obtained NACA 6412 with a coefficient of 0.41%, and The highest power coefficient was obtained by NACA 4415 with a coefficient of 44%
The present work uses the method of Blade Element Momentum Theory as suggested by Hansen. The method applied to three blade models adopted from Rahgozar S. with the airfoil data used the data provided by Wood D. The wind turbine performance described in term of the thrust coefficient C_T, torque coefficient C_Q and the power coefficient C_p . These three coefficient can be deduced from the Momentum theory or from the Blade element Theory(BET). The present work found the performance coefficient derived from the Momentum theory tent to over estimate. It is suggested to used the BET formulation in presenting these three coefficients. In overall the Blade Element Momentum Theory follows the step by step as described by Hansen work well for these three blade models. However a little adjustment on the blade data is needed. To the case of two bladed horizontal axis wind
As the world focuses more on clean and green Earth, wind energy plays a significant role. Wind energy is a renewable source of energy that can cope with the ongoing global fossil fuel crisis. The wind energy converters like wind turbines have been studied a lot in terms of design and performance. The current work includes analyzing the output effects of a horizontal axis wind turbine (HAWT) with a modified blade configuration at specific wind speeds. A numerical investigation is carried out using two different numerical software on the chosen airfoil used in blade design validated with the analysis carried out in open-loop wind tunnels. The study is divided into two phases: first, the selected airfoil is tested experimentally and using CFD, and then the findings are compared to those of the University of Illinois Urbana Champaign wind tunnel tests at low Reynolds numbers. The second phase includes the numerical analysis based on the blade element momentum method and non-linear lifting line simulations of modified blade design at high Reynolds number. The numerical results of rotor performance analysis have been compared to existing experimental results. The findings of all numerical investigations agree with those of the experiments. An optimal value of the power coefficient is obtained at a particular tip speed ratio close to the desired value for large wind turbines. For maximum power, this study investigates the optimum pitch angle. The work demonstrated the improved HAWT rotor blade design to produce better aerodynamic lift and thus improve performance.
This paper presents the performance of the diffuser augmented wind turbine (DAWT) with the various diffuser shapes using the numerical investigations. DAWT is also a type of wind turbine and the diffuser shapes, the nozzle shapes and the cylindrical shapes are commonly inserted around the horizontal axis wind turbine (HAWT) to become the more efficient wind turbine. The aim of this study is to find the more efficient design of the diffuser for the horizontal axis wind turbine using the numerical investigations. In this research, the converging and diverging diffuser shape is inserted and the airfoil design is calculated by using the Blade Elementary Momentum Theory. The airfoil type NACA 4412 is chosen because it is suitable for the low wind speed area and easy to produce. The turbulent model k-ω is combined with the Navier Stoke equation to solve the 3-dimensional steady flow simulation of the diffuser augmented wind turbine using the Computational Fluid Dynamics (CFD) simulations. The numerical investigation is used to compare and predict the power coefficient of the DAWT with various shapes. The baseline design of the diffuser (L = 170 mm, H = 57 mm and α = 11̊) is firstly investigated. To predict the power coefficient of the various diffuser shapes, the range of the length of the diffuser is (L/D = 0.5 to 1.5), the range of the brim height of the diffuser (H/D = 0.1 to 0.35) and the range of the angle of the diffuser (α = 5̊ to 15̊ ) are also investigated. The parameters of the diffuser shapes are assigned by using the Central Composite Design Face Centered Method. The response surface method is also used to predict the most efficient diffuser design. The performance of the horizontal axis wind turbine, that of the diffuser augmented wind turbine and that of the diffuser augmented wind turbine with various shapes of diffuser are compared. The performance of new diffuser augmented wind turbine (IND_009) is 50% and 55% higher than the baseline diffuser augmented wind turbine and the horizontal axis wind turbine at rated velocity. The flow visualization of the HAWT, DAWTs are also discussed.
The smart electricity meter (SEM) is an important part of smart power grid, and the accuracy of SEMs is the basis for power grid operation control and trade settlement between power supply and electricity consumption, but the evolution behaviors of metering error of SEMs under field operation conditions have not yet been identified. The SEMs were installed and operated on site, metering error data were collected under various temperature and current conditions. The influences of current, power coefficient, and temperature on metering error and consistency were analyzed separately with the help of quadratic polynomials, and then an integrated model elaborating the joint effects of multi-stress was developed based on a binary quadratic polynomial. We find that a lower temperature and a larger current result in a higher metering error of SEMs; however, the effects of current on metering error are determined by power coefficients. The results have reference value for remote metrological verification, error monitoring, and the optimization of the operation and maintenance scheme of SEMs.