Effects of wind turbine dimensions on the collision risk of raptors: A simulation approach based on flight height distributions.

Wind energy development is a key component of climate change mitigation. However, birds collide with wind turbines, and this additional mortality may negatively impact populations. Collision risk could be reduced by informed selection of turbine dimensions, but the effects of turbine dimensions are still unknown for many species. As analyses of mortality data have several limitations, we applied a simulation approach based on flight height distributions of six European raptor species. To obtain accurate flight height data, we used high-frequency GPS tracking (GPS tags deployed on 275 individuals). The effects of ground clearance and rotor diameter of wind turbines on collision risk were studied using the Band collision risk model. Five species had a unimodal flight height distribution, with a mode below 25 m above ground level, while Short-toed Eagle showed a more uniform distribution with a weak mode between 120 and 260 m. The proportion of positions within 32-200 m ranged from 11 % in Marsh Harrier to 54 % in Red Kite. With increasing ground clearance (from 20 to 100 m), collision risk decreased in the species with low mode (-56 to -66 %), but increased in Short-toed Eagle (+38 %). With increasing rotor diameter (from 50 to 160 m) at fixed ground clearance, the collision risk per turbine increased in all species (+151 to +558 %), while the collision risk per MW decreased in the species with low mode (-50 % to -57 %). These results underpin that wind turbine dimensions can have substantial effects on the collision risk of raptors. As the effects varied between species, wind energy planning should consider the composition of the local bird community to optimise wind turbine dimensions. For species with a low mode of flight height, the collision risk for a given total power capacity could be reduced by increasing ground clearance, and using fewer turbines with larger diameter.

PD-DEM hybrid modeling of leading edge erosion in wind turbine blades under controlled impact scenarios.

This paper addresses the critical issue of leading edge erosion (LEE) on modern wind turbine blades (WTBs) caused by solid particle impacts. LEE can harm the structural integrity and aerodynamic performance of WTBs, leading to reduced efficiency and increased maintenance costs. This study employs a novel particle-based approach called hybrid peridynamics-discrete element method (PD-DEM) to model the impact of solid particles on WTB leading edges and target material failure accurately. It effectively captures the through-thickness force absorption and the propagation of stresses within the leading edge coating system composed of composite laminates. The amount of mass removed and the mean displacement of the target material points can be reliably calculated using the current method. Through a series of tests, the research demonstrates the method's ability to predict impact force changes with varying particle size, velocity, impact angles and positions. Moreover, this study offers a significant improvement in erosion prediction capability and the development of design specifications. This work contributes to the advancement of WTB design and maintenance practices to mitigate LEE effectively.

CTNet: A data-driven time-frequency technique for wind turbines fault diagnosis under time-varying speeds.

Nonstationary fault signals collected from wind turbine planetary gearboxes and bearings often exhibit close-spaced instantaneous frequencies (IFs), or even crossed IFs, bringing challenges for existing time-frequency analysis (TFA) methods. To address the issue, a data-driven TFA technique, termed CTNet is developed. The CTNet is a novel model that combines a fully convolutional auto-encoder network with the convolutional block attention module (CBAM). In the CTNet, the encoder layer is first designed to extract coarse features of the time-frequency representation (TFR) calculated by the general linear Chirplet transform (GLCT); second, the decoder layer is combined to restore and conserve details of the key time-frequency features; third, the skip connections are designed to accelerate training by linking extracted and reconstructed features; finally, the CBAM is introduced to adaptively explore channel and spatial relationships of the TFR, focusing more on close-spaced or crossed frequency features, and effectively reconstruct the TFR. The effectiveness of the CTNet is validated by numerical signals with close-spaced or crossed IFs, and real-world signals of wind turbine planetary gearbox and bearings. Comparison analysis with state-of-the-art TFA methods shows that the CTNet has high time-frequency resolution in characterizing nonstationary signals and a much better ability to detect wind turbine faults.

Aerodynamic efficiency assessment of a cross-axis wind turbine integrated with an offshore deflector.

The present work examines the performance of an offshore cross-axis wind turbine (CAWT) with a flow deflector by integrating numerical and analytical methods. The deflector's geometry redirects flow in all directions, causing it to exit vertically and collide with the wind turbine's horizontal blades. In contrast, the blades of a vertical axis wind turbine (VAWT) harness the power of horizontal wind flow. The total power absorbed by the horizontal and vertical turbine blades represents the power of CAWT. In this study, the speed of the outflow from the deflector was initially determined through numerical simulation. The numerical simulation output was then utilized as an input for analytical Double Multiple Stream Tube (DMST) and Blade Element Momentum (BEM) methods to evaluate the vertical and horizontal turbine blades, respectively. This approach reduces the overall simulation time and establishes an offline coupling between analytical and numerical approaches. The findings of this research have unveiled a promising future for offshore wind energy generation. Through the implementation of a modeled deflector on a Cross-Axis Wind Turbine (CAWT), the power output reached a remarkable 19 KW with a power coefficient of 0.35 at an 8.4 m/s wind speed. The results indicate that the CAWT with the deflector produced a power output 35 % higher and was 45 % more efficient than a single Vertical-Axis Wind Turbine (VAWT). These outcomes illustrate the potential for greater energy production and efficiency in offshore wind farms.

Research on Integrated Control Strategy for Wind Turbine Blade Life.

Wind turbine blades bear the maximum cyclic load and varying self-weights in turbulent wind environments, which accelerate the propagation of cracks that ultimately progress from minor faults, resulting in blade failure and significant maintenance and shutdown costs. To address this issue, this paper proposes an adaptive control strategy for the blade's useful life. The control system is divided into the inner control loop and the outer control loop. The outer loop is based on the Paris crack propagation model combined with a particle filtering algorithm and calculates the degradation of the blade life under the crack threshold conditions provided by the operation and maintenance strategy to determine the parameter settings of the inner-loop load-shedding controller. The control strategy we propose can balance the load-shedding capability of the controller with the fatigue load of the pitch actuator while considering the predefined remaining useful blade life in the operation and maintenance strategy, avoiding unplanned downtime and reducing maintenance costs.

A Machine Vision Method for Identifying Blade Tip Clearance in Wind Turbines.

This paper introduces a machine vision method for measuring the blade tip clearance in a wind turbine. An industrial personal computer (IPC) is installed in the nacelle of the wind turbine to continuously receive video data from a digital camera mounted at the bottom of the nacelle. Using the open-source computer vision (OpenCV) digital image processing library data base, the real-time trajectory of the turbine blades is determined from the video data. Furthermore, fast Fourier transform (FFT) analysis is performed for determining the operating frequency of the blades in the images. The amplitude analysis performed at this operating frequency reveals the pixel-based blade tip clearance, which is then used to calculate the actual clearance of the wind turbine. This value is subsequently transmitted to the main controller of the wind turbine. The main controller can enhance the operational safety of the wind turbine by implementing appropriate pitch control strategies to restrict and safeguard the blade tip clearance. The results obtained by conducting experiments on a 2.0 MW wind turbine unit validate the effectiveness of the proposed identification method. In this method, the blade tip clearance can be calculated effectively in real time, and both the video sampling rate and communication speed meet the requirements for controlling the blade pitch.

Fault Diagnosis Method for Wind Turbine Gearbox Based on Ensemble-Refined Composite Multiscale Fluctuation-Based Reverse Dispersion Entropy.

The diagnosis of faults in wind turbine gearboxes based on signal processing represents a significant area of research within the field of wind power generation. This paper presents an intelligent fault diagnosis method based on ensemble-refined composite multiscale fluctuation-based reverse dispersion entropy (ERCMFRDE) for a wind turbine gearbox vibration signal that is nonstationary and nonlinear and for noise problems. Firstly, improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and stationary wavelet transform (SWT) are adopted for signal decomposition, noise reduction, and restructuring of gearbox signals. Secondly, we extend the single coarse-graining processing method of refined composite multiscale fluctuation-based reverse dispersion entropy (RCMFRDE) to the multiorder moment coarse-grained processing method, extracting mixed fault feature sets for denoised signals. Finally, the diagnostic results are obtained based on the least squares support vector machine (LSSVM). The dataset collected during the gearbox fault simulation on the experimental platform is employed as the research object, and the experiments are conducted using the method proposed in this paper. The experimental results demonstrate that the proposed method is an effective and reliable approach for accurately diagnosing gearbox faults, exhibiting high diagnostic accuracy and a robust performance.

In-Depth Study on the Application of a Graphene Platelet-reinforced Composite to Wind Turbine Blades.

Graphene platelets (GPLs) are gaining popularity across various sectors for enhancing the strength and reducing the weight of structures, thanks to their outstanding mechanical characteristics and low manufacturing cost. Among many engineering structures, wind turbine blades are a prime candidate for the integration of such advanced nanofillers, offering potential improvements in the efficiency of energy generation and reductions in the construction costs of support structures. This study aims to explore the potential of GPLs for use in wind turbine blades by evaluating their impact on material costs as well as mechanical performance. A series of finite element analyses (FEAs) were conducted to examine the variations of mechanical performances-specifically, free vibration, bending, torsional deformation, and weight reductions relative to conventional fiberglass-based blades. Details of computational modeling techniques are presented in this paper. Based on the outcomes of these analyses, the mechanical performances of GPL-reinforced wind turbine blades are reviewed along with a cost-benefit analysis, exemplified through a 5MW-class wind turbine blade. The findings affirm the practicality and benefits of employing GPLs in the design and fabrication of wind turbine blades.

Crack Detection Method for Wind Turbine Tower Bolts Using Ultrasonic Spiral Phased Array.

High-strength bolts are crucial load-bearing components of wind turbine towers. They are highly susceptible to fatigue cracks over long-term service and require timely detection. However, due to the structural complexity and hidden nature of the cracks in wind turbine tower bolts, the small size of the cracks, and their variable propagation directions, detection signals carrying crack information are often drowned out by dense thread signals. Existing non-destructive testing methods are unable to quickly and accurately characterize small cracks at the thread roots. Therefore, we propose an ultrasonic phased array element arrangement method based on the Fermat spiral array. This method can greatly increase the fill rate of the phased array with small element spacing while reducing the effects of grating and sidelobes, thereby achieving high-energy excitation and accurate imaging with the ultrasonic phased array. This has significant theoretical and engineering application value for ensuring the safe and reliable service of key wind turbine components and for promoting the technological development of the wind power industry.

Controlling wind turbine tower vibration under external force by applying control systems combination.

The global focus has recently shifted away from fuel-based power sources, and one of the most important projects for energy production is wind energy. To maintain low costs, the current research examines the problem of vibrations affecting wind turbine towers' performance (WTTs). In particular, the tower, resulting from excessive vibrations, can negatively affect a structure's power output and service life, as it can cause fatigue. Therefore, we conducted numerical tests on various types of controlled systems. Our tests revealed that combining a new technique cubic negative velocity control (CNVC) and linear negative acceleration control (LNAC) was the most effective and cost-efficient option for vibration damping. This solution was derived by using an approximation method for the averaging technique. The external force is an important component of a nonlinear dynamic system and can be characterized by two-degree-of-freedom (2-DOF) differential coupled equations. After implementing the control measures, we conducted a numerical analysis of the vibration values before and after the operation. Stability is studied numerically. The numerical and approximate solutions were confirmed through the frequency response equation and time history with fourth-order Runge-Kutta (RK-4). Finally, we investigated the effect of parameters and compared our results with those of previously published studies.

Control approaches of power electronic converter interfacing grid-tied PMSG-VSWT system: A comprehensive review.

The growing interest in wind power technology is motivating researchers and decision-makers to focus on maximizing wind energy extraction and enhancing the quality of power integrated into the grid. Over the past decades, significant advancements have been made in Wind Energy Conversion Systems (WECS), such as moving to variable speed wind turbines (VSWT), using various generator types, and interfacing with many power electronic converter topologies. Recently, the majority of wind turbine industries have adopted the VSWT, which is based on the permanent magnet synchronous generator (PMSG) and incorporates a fully controlled power electronic converter (FCPEC) topology due to its notable features of full controllability, ultimately enhancing the efficiency and power quality of the WECS. This paper presents a concise overview of the PMSG-VSWT system and comprehensively reviews the most recent control approaches developed for the FCPEC that play a crucial role in the operation and performance of the PMSG-VSWT system. The paper begins with a comprehensive review of the Maximum Power Extraction Algorithms (MPEA) used in the PMSG-VSWT system, as reported in esteemed research articles over recent years. It investigates the fundamental concepts of each MPEA, examining their advantages and disadvantages, providing critical comparisons, highlighting related work, and discussing the advancements achieved in this field. Subsequently, the paper reviews the prevalent control schemes for the Grid-Side Inverter and Machine-Side Rectifier (GSI/MSR) in the FCPEC. It covers common control approaches such as vector control, direct control, sliding mode control, and model productive control, including modern and intelligent techniques. Additionally, the paper details recent improvements and approaches adopted to address challenges in these common schemes, involving optimizing algorithms and adaptive techniques. The paper provides essential insights into trends, improvements, and challenges in the domain and acts as a crucial reference for researchers working with PMSG-VSWT systems.

Chaotic self-adaptive sine cosine multi-objective optimization algorithm to solve microgrid optimal energy scheduling problems.

Researchers are increasingly focusing on renewable energy due to its high reliability, energy independence, efficiency, and environmental benefits. This paper introduces a novel multi-objective framework for the short-term scheduling of microgrids (MGs), which addresses the conflicting objectives of minimizing operating expenses and reducing pollution emissions. The core contribution is the development of the Chaotic Self-Adaptive Sine Cosine Algorithm (CSASCA). This algorithm generates Pareto optimal solutions simultaneously, effectively balancing cost reduction and emission mitigation. The problem is formulated as a complex multi-objective optimization task with goals of cost reduction and environmental protection. To enhance decision-making within the algorithm, fuzzy logic is incorporated. The performance of CSASCA is evaluated across three scenarios: (1) PV and wind units operating at full power, (2) all units operating within specified limits with unrestricted utility power exchange, and (3) microgrid operation using only non-zero-emission energy sources. This third scenario highlights the algorithm's efficacy in a challenging context not covered in prior research. Simulation results from these scenarios are compared with traditional Sine Cosine Algorithm (SCA) and other recent optimization methods using three test examples. The innovation of CSASCA lies in its chaotic self-adaptive mechanisms, which significantly enhance optimization performance. The integration of these mechanisms results in superior solutions for operation cost, emissions, and execution time. Specifically, CSASCA achieves optimal values of 590.45 €ct for cost and 337.28 kg for emissions in the first scenario, 98.203 €ct for cost and 406.204 kg for emissions in the second scenario, and 95.38 €ct for cost and 982.173 kg for emissions in the third scenario. Overall, CSASCA outperforms traditional SCA by offering enhanced exploration, improved convergence, effective constraint handling, and reduced parameter sensitivity, making it a powerful tool for solving multi-objective optimization problems like microgrid scheduling.

Hardware-in-the-Loop experiments in model ice for analysis of ice-induced vibrations of offshore structures.

The study investigated the use of a Hardware-in-the-Loop (HiL) technique applied in model ice experiments to enable the analysis of offshore structures with low natural frequencies under dynamic ice loading. Traditional approaches were limited by facility capacities and ineffective downscaling of the geometry of the offshore structures. The goal of the present study was to overcome these challenges and to enhance the understanding and explore the applicability of a hybrid testing technique in model ice experiments. To achieve the objective, 204 Hardware-in-the-Loop simulations in model Ice (HiLI) were analyzed. Results showed robust behavior and good performance of the HiLI due to minimal variation in measured delay, normalized root mean square error, and peak tracking error and low magnitudes of such parameters despite alterations in factors such as the choice of the numerical structural model, physical prototype, measurement system, and ice type. Notably, the performance of the HiLI was affected when testing with warm model ice or scaling for harsh ice conditions, attributed to a reduced signal-to-noise ratio and instability of the system, respectively. Experimental identification of the critical delay, along with the application of an analytical stability criterion, revealed that the instability observed, was likely induced by reducing the structural stiffness of the numerical structural model to fulfil the scaling requirements when testing for harsh ice conditions. Additionally, the study showed improved HiLI performance when the physical prototype was in contact with the model ice. This observation was further analyzed and is assumed to be caused by the coupling between the ice and physical prototype, causing a coupled and thus increased eigenfrequency of the physical prototype-ice system.

Techno-economic analysis of off-grid hybrid wind-photovoltaic-battery power system by analyzing different batteries for the industrial plant in Shiraz Industrial Town, Iran.

The world has moved toward renewable energy resources for three major reasons: (1) to mitigate climate change arising from the excessive emission of greenhouse gases, (2) to protect health by lowering greenhouse gas emissions, and (3) to meet ever-increasing demands for energy. Shiraz is a major city in Iran and struggles with pollution challenges due to the presence of highly polluting industries. The increased energy demand and the lack of a demand-supply trade-off have led to frequent power outages in Shiraz in recent years. Batteries have been of great interest to researchers as they have a wide range of compounds and variety in the market and strongly influence the function and initial costs of hybrid energy systems. This study models a hybrid renewable energy system using four different batteries, that is, lead-acid, Li-ion, vanadium redox, and zinc-bromine batteries. These four scenarios were subjected to techno-economic analysis in HOMER. The system was assumed to generate 3000 kW of industrial power and 300 kWh of office/domestic power. It was demonstrated that the hybrid system with the lead-acid battery was the most optimal system to supply power to the case-study industrial plant for both industrial and domestic load, with a levelized cost of energy of 0.47 USD/kWh and an initial cost of 6.02 million USD. However, the hybrid system with the Li-ion battery will become more optimal than the system with the lead-acid battery if Li-ion batteries continue to become more affordable in < 5 years. This system would decrease CO2 emissions by 1,060,133 kg every year as compared to the diesel system.

Initial Study of the Onsite Measurement of Flow Sensors on Turbine Blades (SOTB).

This paper presents a new framework using MEMS flow sensors on turbine blades (SOTB) to investigate unsteady flow features of a rotating wind turbine. Self-heating flow sensors were implemented by the U18 complementary metal-oxide semiconductor (CMOS) MEMS foundry provided by Taiwan Semiconductor Research Institute (TSRI). Flow sensor chips with a size of 1.5 mm × 1.5 mm were parylene-coated, output via a wireless data acquisition system (WDAQ), and mounted at the root, middle and tip of a 1.2 m diameter semi-rigid turbine blade of a 400 W horizontal axis wind turbine (HAWT). The instantaneous angles of attack (AOAs) of the SOTB were found to be 46~62°, much higher than the general stall AOA of 15°, but were accurate considering the normal detection of the flow sensors. The computational fluid dynamics (CFD) simulation of the HAWT was also compared with the SOTB output. The onsite measurement herein revealed that the 3D secondary flow increment, mostly obvious near the middle part of the turbine blades, degraded both the sensor and the turbine performance and initially justified the onsite measurement application.

Exploratory Study on the Application of Graphene Platelet-Reinforced Composite to Wind Turbine Blade.

With the growth of the wind energy market and the increase in the size of wind turbines, the demand for advanced composite materials with high strength and low density for wind turbine blades has become imperative. Graphene platelets (GPLs) stand out as highly premising reinforcements due to their exceptional physical properties, resulting in their widespread adoption in the composite industry in recent years. The present study aims to analyze the applicability of a graphene-platelet-reinforced composite (GPLRC) to wind turbine blades in terms of structural performance. A finite element blade model is constructed by referring to the National Renewable Energy Laboratory (NREL) 5 MW wind turbine, and its reliability is verified through a convergence test. The performance of the wind turbine blade is quantitatively examined in terms of the deflection and stress, natural frequencies, and twist angle. The applicability of the GPL-reinforced wind blade is explored through a comparison with wind blades manufactured with glass fiber and carbon nanotubes (CNTs). The comparison indicates that the performance of a wind blade can be remarkably improved by reinforcing with GPLs instead of traditional fillers, and the weight of not only the wind blade itself but also the wind turbine system can be remarkably reduced. The present results can be useful in the development of next-generation high-strength lightweight wind turbine blades.

Natural Frequency Transmissibility for Detection of Cracks in Horizontal Axis Wind Turbine Blades.

Defects on horizontal axis wind turbine blades are difficult to identify and monitor with conventional forms of non-destructive examination due to the blade's large size and limited accessibility during continuous operation. This article examines both strain and acceleration transmissibility as methods of continuous damage detection on wind turbine blades. A scaled 117 cm offshore wind turbine blade was first designed, 3D printed, and modelled numerically in ANSYS. Transverse cracks were deliberately introduced to the blade at 10 cm intervals along its leading edge. Subsequent changes in the transmissibility, relative to an undamaged baseline model, were measured using different variable combinations at the blade's first three natural frequencies. Experimental results indicated that strain transmissibility was able to locate a 1.0 cm defect at a range of 70-110 cm from the blade hub using the amplitudes of the first natural frequency of vibration. The numerical model was able to simulate the strain experimental results and was determined to be valid for future defect characterization. Acceleration transmissibility was unable to experimentally identify defects sized at 1.0 cm and below but was able to identify 1.0 cm sized defects numerically. It was concluded that transmissibility is viable for continuous damage detection on blades but that further research into other defect types and locations is required prior to conducting full-scale testing.

Recovering high-quality glass fibers from end-of-life wind turbine blades through swelling-assisted low-temperature pyrolysis.

The recycling of end-of-life wind turbine blades has become a global environmental challenge driven by the rapid growth of wind power. Pyrolysis is a promising method for recovering glass fibers from these discarded blades, but traditional pyrolysis is often operated at high temperatures, which degrades the mechanical properties of recovered fibers. To address this issue, a swelling-assisted pyrolysis method was proposed to recover high-quality glass fibers from end-of-life wind turbine blades at low temperatures. The results confirmed that the decomposition of the resin matrix within the blade was significantly promoted at low temperatures in the swelling-assisted pyrolysis process, achieving a resin decomposition ratio of 76.8 % at 350 °C. This improvement was attributed to enhanced heat transfer and co-pyrolysis with acetic acid. Swelling could physically disrupt the cross-linked structure of the blade, creating a more porous and layered structure, thereby enhancing heat transfer during the pyrolysis process. Simultaneously, the co-pyrolysis with acetic acid could generate hydrogen radicals, which promoted the cracking of macromolecular oligomers into lighter products or gaseous alkanes. Consequently, the formation of pyrolysis char within the solid pyrolysis product was reduced, shortening the oxidation duration to 30 min. In comparison to traditional pyrolysis, the swelling-assisted pyrolysis process effectively suppressed the diffusion of surface defects over the recovered fibers, leading to promising improvements in their flexibility, elasticity, and mechanical properties, with tensile strength notably increased by 27.5 %. These findings provided valuable insights into recovering high-quality glass fibers from end-of-life wind turbine blades.

Power regulation of variable speed multi rotor wind systems using fuzzy cascaded control.

Power quality is a crucial determinant for integrating wind energy into the electrical grid. This integration necessitates compliance with certain standards and levels. This study presents cascadedfuzzy power control (CFPC) for a variable-speed multi-rotor wind turbine (MRWT) system. Fuzzy logic is a type of smart control system already recognized for its robustness, making it highly suited and reliable for generating electrical energy from the wind. Therefore, the CFPC technique is proposed in this work to control the doubly-fed induction generator (DFIG)-based MRWT system. This proposed strategy is applied to the rotor side converter of a DFIG to improve the current/power quality. The proposed control has the advantage of being model-independent, as it relies on empirical knowledge rather than the specific characteristics of the DFIG or turbine. Moreover, the proposed control system is characterized by its simplicity, high performance, robustness, and ease of application. The implementation of CFPC management for 1.5 MW DFIG-MRWT was carried out in MATLAB environment considering a variable wind speed. The obtained results were compared with the direct power control (DPC) technique based on proportional-integral (PI) controllers (DPC-PI), highlighting that the CFPC technique reduced total harmonic distortion by high ratios in the three tests performed (25%, 30.18%, and 47.22%). The proposed CFPC technique reduced the response time of reactive power in all tests by ratios estimated at 83.76%, 65.02%, and 91.42% compared to the DPC-PI strategy. Also, the active power ripples were reduced by satisfactory proportions (37.50%, 32.20%, and 38.46%) compared to the DPC-PI strategy. The steady-state error value of reactive power in the tests was low when using the CFPC technique by 86.60%, 57.33%, and 72.26%, which indicates the effectiveness and efficiency of the proposed CFPC technique in improving the characteristics of the system. Thus this control can be relied upon in the future.

Experimental investigation of multi-step airfoils in low Reynolds numbers applications.

This study provides a detailed analysis of the aerodynamic performance of various airfoil configurations, focusing on lift coefficient, stall characteristics, and maximum lift-to-drag ratio. The investigation includes the NACA23012C profile and configurations with different step geometries, ranging from one-step to five-step designs. Experimental measurements were conducted using a well-equipped aerodynamic laboratory, Institute of Aviation Engineering and Technology (IAET), Giza, Egypt. The lab features a wind tunnel, propeller test rig, and data acquisition system. The experiments were conducted meticulously to ensure accuracy and reproducibility, with a standardized method employed for uncertainty analysis. The results reveal distinct aerodynamic behaviors among the different configurations, highlighting the significant impact of design variations on aerodynamic performance. Notably, the three-step configuration consistently exhibited high performance, with a competitive or superior lift coefficient across a range of Reynolds numbers, showing an improvement of up to 35.1 %. Similarly, the four-step configuration demonstrated substantial increases in lift-to-drag ratios, reaching up to 53.2 %, while the five-step configuration exhibited varying trends with a minimum drag coefficient. The study also investigated stall characteristics and sensitivity to Reynolds numbers, revealing the complex trade-offs inherent in airfoil design. The findings provide valuable insights into optimizing airfoil performance under different operational conditions. Additionally, the adoption of two and three stepped airfoils resulted in significant reductions in blade material and associated costs for turbine blades.