Small-scale Wind Research Articles

Design guidelines for HAWT / VAWT decision-making in the context of underserved communities

Underserved communities in rural areas often lack access to appropriate technologies that provide sustainable and reliable energy sources vital to their well-being and economic activities. In this context, the potential of small-scale wind turbine generators (WTGs) as a renewable energy source is investigated, as they can provide enough energy while being relatively easy to operate and maintain. Nevertheless, limited research is carried out about the comparative advantages of vertical axis wind turbines (VAWTs) and horizontal axis wind turbines (HAWTs) for these resource-limited conditions. The research approach includes a literature review, a field study in Kenya, and a multi-criteria decision analysis (MCDA) tailored to local wind conditions and humanitarian engineering design principles. Structural, operational, and performance differences between HAWTs and VAWTs are explored as well as the local needs of underserved communities. The MCDA results highlight design principles for the deployment of small wind turbines in rural areas and provide useful design guidelines for WTG development in underserved regions.

Deep Learning Parameterization of Vertical Wind Velocity Variability via Constrained Adversarial Training

Abstract Atmospheric models with typical resolution in the tenths of kilometers cannot resolve the dynamics of air parcel ascent, which varies on scales ranging from tens to hundreds of meters. Small-scale wind fluctuations are thus characterized by a subgrid distribution of vertical wind velocity W with standard deviation σW. The parameterization of σW is fundamental to the representation of aerosol–cloud interactions, yet it is poorly constrained. Using a novel deep learning technique, this work develops a new parameterization for σW merging data from global storm-resolving model simulations, high-frequency retrievals of W, and climate reanalysis products. The parameterization reproduces the observed statistics of σW and leverages learned physical relations from the model simulations to guide extrapolation beyond the observed domain. Incorporating observational data during the training phase was found to be critical for its performance. The parameterization can be applied online within large-scale atmospheric models, or offline using output from weather forecasting and reanalysis products. Significance Statement Vertical air motion plays a crucial role in several atmospheric processes, such as cloud droplet and ice crystal formation. However, it often occurs at scales smaller than those resolved by standard atmospheric models, leading to uncertainties in climate predictions. To address this, we present a novel deep learning approach that synthesizes data from various sources, providing a representation of small-scale vertical wind velocity suitable for integration into atmospheric models. Our method demonstrates high accuracy when compared to observation-based retrievals, offering potential to mitigate uncertainties and enhance climate forecasting.

Optimal airfoil selection for small horizontal axis wind turbine blades: A multi-criteria approach

Over the last century, the growing demand for clean energy has emphasized wind energy as a promising solu-tion to address contemporary energy challenges. Within the realm of wind energy, the wind turbine plays a pivotal role in harnessing the kinetic energy of the wind and converting it into electrical power. Among the various components of the wind turbine system, turbine blades assume a critical role in capturing the wind's kinetic energy and converting it into rotational motion. Consequently, the design of wind turbine blades holds the utmost importance in determining the overall performance and efficiency of the entire wind turbine system. One essential aspect of blade design involves selecting an appropriate airfoil. Throughout history, numerous airfoil profiles have been developed for various applications. Notably, National Advisory Committee for Aeronautics (NACA) and National Renewable Energy Laboratory (NREL) airfoils have been tailored for aircraft and large-scale wind turbine blades, respectively. However, the quest for suitable airfoil types for small-scale wind turbine blades has been ongoing. This study delves into an examination of over 62 distinct NACA and NREL aerofoil types tailored for small horizontal-axis wind turbine blades. Employing specialized software, namely QBlade, specifically designed for modeling and simulating wind turbine blades, the study calculates key parameters such as power output, stress, deformation, and weight for each airfoil. Subsequently, based on the simulated data, the optimal airfoil is identified using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria selection approach. This selection process takes into account simulation results pertaining to power output, stress, deformation, and weight. The decision-making process involving multiple criteria is facilitated using Excel and Python. The findings of this study reveal that among the 62 airfoil types under consideration, the NACA 0024, NACA 2424, and NACA 4424 airfoils emerge as the most suitable choices for small horizontal-axis wind turbine blades.

Modelling and analysis of jute fiber reinforced epoxy composite in the development of wind blade for low intensity winds

Natural fibers show an increasing potential as reinforcement of polymeric composites, representing a promising concurrent to glass and carbon fibers extensively used in the construction of wind turbine blades synthetic fibers recyclability/disposability and high production energy cost have already been discussed in the main turbine producing centres. In particular, the development of wind turbines for low wind speed areas can increase the energy generation potential of regions not originally eligible for the installation of large turbines. This study proposes the evaluation of the use of jute fiber (Corchorus capsularis) reinforced epoxy composite in the construction of S1210 airfoil profile, of a small-scale wind turbine for low wind speed regions, considering the structural parameters, developed incorporating the Classical Laminate Theory (CLT) and Extended Bredt-Batho Shear Flow Theory (EBSFT).In order to raise the elastic properties and enable the use of the failure criteria, the composite blades were characterized according to ASTM standards. The mechanical properties surveyed, together with the elastic parameters of the cross section, torsional stiffness, axial stiffness, GJ 1873.6 N m2, EI 9.47 × 104 N m2, and flexural rigidity, Ely 4.97 × 104 N m2, Elz 1.45 × 106 N m2, respectively, demonstrated the feasibility of using the jute fiber reinforced epoxy composite in the blade construction, evaluated according to the maximum tension failure criterion.

Optimization of DC Microgrid Power and Energy Management in the Presence of Small-Scale Wind Turbine Integration and Renewable Load Shedding

Improvement of Direct Current Microgrid (DCM) Power and Energy Management is the methodical process of increasing the DCM system’s performance, dependability, and effectiveness. In this study, the suggested a Stochastic Dove Swarm Optimized Deep Reinforcement Learning Algorithm approach to estimate the availability of wind energy, allowing for proactive management tactics. Initially, the data was collected and preprocessed by performing min–max normalization to clean the unwanted data. Recursive Feature Elimination is used to determine the greatest informative attributes. This study analyzes the use of significant performance metrics, including accuracy (91%), precision (92%), recall (93%), Root Mean Square Error (0.154), Normalized Root Mean Square Error (0.0526), and Mean Absolute Percentage Error (4.21). The use of optimization methodology focuses on the seamless integration of SWTs and the application of renewable LS methods to ensure the efficient management of power and energy in DC microgrids. The intention is to keep operational expenses to a minimum while providing a stable and robust energy supply. To ensure power balance, which serves as the primary objective of the monitoring, it is considered imperative for carrying out electricity limitations in this instance of the energy excess generated by solar power plants and the small-scale wind turbine.

Geometry effects on wind fields and consequent wave generation in the Strait of Hormuz: A case study

This study investigates the impact of surface wind forcing on wave conditions in the Strait of Hormuz, a region with complex wave interactions. The WRF model is used to simulate the wind field with higher accuracy, enabling the generation of waves for both normal and storm conditions in 2011. A sensitivity analysis examines the WRF model's simulated wind field with variations in initial and boundary conditions, spatial resolutions, and adopting two static topographic datasets. Comparisons between simulated wave parameters and observed data from ADCPs at two stations flanking the strait reveal the importance of accurate wind forcing for obtaining a realistic estimation of wave conditions. Wave errors are found to be influenced by fetch length, with larger errors observed for shorter fetches (∼100 km). However, these errors gradually decrease as the distance from the coast increases. The study emphasizes the importance of incorporating accurate wind data and considering fetch characteristics when simulating wave conditions, which can enhance maritime safety, coastal engineering, and offshore operations in the Strait of Hormuz and other similar regions worldwide. In conclusion, small-scale wind and waves features over the Strait of Hormuz can be better captured with a combination of higher-resolution wind modeling and wave simulation grids with higher spatial resolution.

An Exploratory Wind Tunnel Study of Air Jet Wheel Spoilers

Wheels and wheelhouses are a significant source of aerodynamic drag on passenger cars. The use of air jets, in the form of an air curtain, to smooth the airflow around front wheel housings on cars has become common practice, as it produces a small drag benefit. This paper reports an initial small-scale wind tunnel study of an air jet employed as an effective wheel spoiler to reduce the drag produced by the front wheels and wheel housings of passenger cars. For this investigation, the air jet was created using an external compressed-air supply and was applied to a highly simplified car body shape. The data presented suggest that the air jet has some potential as a drag-reduction device.

A single current sensor based adaptive step size MPPT control of a small scale variable speed wind energy conversion system

Due to the limited size and lower environmental impact, a small-scale wind energy conversion system (WECS) is a promising alternative for remote locations and residential areas where installing large wind turbines is not feasible. This system employs a permanent magnet synchronous generator (PMSG) as a variable speed wind generator due to its advantages such as high torque density, gearless, and require no external excitation, etc. This article proposes a single load current sensor-based adaptive step size (LCAS) maximum power point extraction (MPPT) method which utilizes the load current information to track the maximum power. This method does not require rotor speed information and knowledge of the turbine parameters. Also, this article uses a simple and cost-effective switch mode rectifier topology (AC–DC and DC–DC boost converters) for the PMSG-based variable speed WECS. The proposed method is validated in a 1.5 kW test rig using an OPAL-RT digital signal controller and also compared with various fixed step size (FSS) MPPT algorithms at various operating conditions. Extensive experimental work has been carried out for the LCAS MPPT method that confirms the tracking efficiency is better and tracking speed is faster along with the improved steady state as well as transient performance.

Conceptual Design and Analysis of Small-Scale Wind Turbine for Household Usage in Malaysia

Wind energy is a valuable renewable resource that holds great potential for generating electrical power through wind turbines. However, there is a lack of practical and cost-effective small-scale wind turbines designed specifically for household usage. This study aims to address this need by focusing on the design and performance analysis of a small-scale vertical Darrieus wind turbine tailored for household applications in Malaysia. The objective is to propose an optimized turbine design that maximizes energy conversion efficiency. Computational fluid dynamics (CFD) simulations using ANSYS Fluent software are conducted to evaluate the turbine's performance, with the power coefficient (Cp) calculated at various tip speed ratios (TSR). Two 3D designs with different blade configurations are developed using SolidWorks for the CFD simulations. The findings from this study contribute to the design optimization and performance evaluation of vertical Darrieus wind turbines, providing a sustainable and viable alternative for residential energy needs. This research addresses the pressing demand for clean and affordable energy solutions in Malaysia and supports the transition towards renewable sources.

A wind tunnel study of adverse pressure gradient impact on wind turbine wake dynamics

Wind tunnel experiments were conducted to investigate the impact of an adverse streamwise pressure gradient on the wake dynamics of a small-scale horizontal-axis wind turbine. The study used high-frequency constant temperature hotwire anemometry to measure wake velocities up to 7 rotor diameters (dT) downstream. Two cases were studied: zero pressure gradient (ZPG) and adverse pressure gradient (APG). Experimental conditions included a Reynolds number based on the rotor diameter of Re≈6.7×104 and an inflow velocity of 7 m/s. The results show significant differences between the ZPG and APG cases as the wake progresses downstream. The APG case exhibits a higher maximum velocity deficit in the far wake and a more distorted, oval-shaped wake than the ZPG case. Turbulence intensity trends also differ, with a decreasing trend in the ZPG case and an increasing trend in the APG case. Energy spectra analysis at specific wake locations offers insights into flow structure development. In both cases, small-scale (high-frequency) energy decreases as the wake advances, while large-scale (low-frequency) energy increases. Specifically, the adverse pressure gradient attenuates certain large-scale flow structures λx/dT∈[0.05,0.2], corresponding to f∈[20,100]Hz near the rotor tip height and narrows downstream. Additionally, in the APG case, energy increases in the lower half of the wake for flow structures ranging from λx/dT∈[0.04,0.5], or f∈[10,100]Hz near the rotor, narrowing further downstream. The results suggest that an adverse pressure gradient enhances turbulence and hinders velocity recovery toward freestream conditions in the wake of a wind turbine.

Using 2-bladed Savonius rotor to harvest highway wind energy at airport: A case study

ABSTRACTThe Savonius wind turbine (SWT) is a famous type of vertical axis wind turbine (VAWT) that accepts wind from all directions, particularly suitable for various applications including the design of small-scale wind turbines. This study evaluates the potential installation of a simple 2-bladed SWT on Queen Alya’ airport highway, Amman, Jordan. The strategic objective of this work was to design and install the SWT prototype at different sites along the airport road to define the most efficient location for capturing wind energy. The SWT rotor was fabricated via galvanized steel sheets. The self-starting ability of the rotor was examined by determining the torque coefficient at different angles of attack. The field tests were carried out by employing the turbine at three different locations along a six-lane highway (including the left, right, and middle sides of the highway). It was found that the proposed turbine has a cut-in wind speed of 2.5 m/s. Furthermore, the torque coefficient values indicated that the proposed rotor has a strong self-starting capacity. Field studies also revealed that the rotational speed of the turbine differs at various positions of the wind turbine. In addition, the results highlighted the significance of wind directions relative to vehicle directions for generating wind power on highways. The established Savonius rotor exhibited a maximum coefficient of performance of 0.25 with operational TSRs up to 0.7. Overall, a maximum enhanced rotational speed of about 53% was attained by positioning the turbine in the middle of six-way-lane highways.

Feasibility Study for the Development of Small Scale Low Speed Wind Tunnel for Supermileage Prototype Car

This paper presents the design and construction of a small-scale low-speed open circuit wind tunnel suitable for experimental testing and analysis of aerodynamic phenomena. The wind tunnel is specifically designed for low-speed applications, focusing on flows within velocities of 35 meters per second with turbulence conditions below 10 percent. The design process of a wind tunnel involves considerations such as dimensions, design parameters, and instrumentation to ensure accurate flow measurements, with key components including a settling chamber, contraction section, test section, diffuser, and drive system working together to remove disturbances, create uniform flow, minimize blockage effects, and generate required airflow for accurate aerodynamic testing. This paper highlights the design considerations, key components, construction techniques, and the significance of the wind tunnel for aerodynamic testing, validation of simulations, and education. The designed wind tunnel is capable of producing controlled and repeatable low-speed flow conditions, making it suitable for a wide range of applications, including aerodynamic testing of scaled- down models, validation of Computational Fluid Dynamics (CFD) simulations, and educational purposes. The small-scale design allows for cost-effective construction and operation while maintaining reliable results.

Development of a Hardware-in-the-Loop Platform for the Validation of a Small-Scale Wind System Control Strategy

The use of renewable energies contributes to the goal of mitigating climate change by 2030. One of the fastest-growing renewable energy sources in recent years is wind power. Large wind generation systems have drawbacks that can be minimized using small wind systems and DC microgrids (DC-µGs). A wind system requires a control system to function correctly in different regions of its operating range. However, real-time analysis of a physical wind system may not be feasible. An alternative to counteract this disadvantage is using real-time hardware in the loop (HIL) simulation. This article describes the implementation of an HIL platform in an NI myRIO 1900 to evaluate the performance of control algorithms in a small wind system (SWS) that serves as a distributed generator for a DC-µG. In the case of an SWS, its implementation implies nonlinear behaviors and, therefore, nonlinear equations, and this paper shows a way to do it by distributing the computational work, using a high-level description language, and achieving good accuracy and latency with a student-oriented development kit. The platform reproduces, with an integration time of 10 µs, the response of the SWS composed of a 3.5 kW turbine with a fixed blade pitch angle and no gear transmission, a permanent magnet synchronous generator (PMSG), and a three-phase full-bridge AC/DC electronic power converter. The platform accuracy was validated by comparing its results against a software simulation. The compared variables were the PMSG currents in dq directions, the turbine’s angular speed, and the DC bus’s voltage. These comparisons showed mean absolute errors of 0.04 A, 1.9 A, 0.7 rad/s, and 9.5 V, respectively. The platform proved useful for validating the control algorithm, exhibiting the expected results in comparison with a lab-scale prototype using the same well-known control strategy. Using a well-known control strategy provides a solid reference to validate the platform.

Towards Efficient Energy Usage at Ain Shams University Campus

In the light of global energy transition to renewable resources and energy efficiency usage, Ain Shams University (ASU) developed an ambitious plan to transform its campus into Green Campus. From an energy perspective, energy consumption data were continuously collected and audited to calculate the university campus carbon footprint. An energy usage strategy was established to tackle various pillars such as electrifying the campuses’ transportation system, improving energy efficiency usage, generating Renewable Energy (RE) for self-consumption, etc. Extensive research has been initiated on electric vehicles, wind and solar Photovoltaic (PV) energy generation with students’ activities/competitions. Thus, electric cars and buses were manufactured at the Faculty of Engineering (FoE) for elderly people and staff movement in ASU campus. Solar PV lighting poles with batteries were installed in the main campus. A small-scale Wind Turbine (WT) is manufactured and installed at the FoE and a pilot solar PV system is installed as well. Currently, an energy efficiency project is under implementation in various buildings/faculties and a parking lot that targets energy efficiency and solar PV energy generation. An energy efficiency measure is under implementation through replacing lamps with LED lamps, installing motion sensors, setting up a control center for monitoring and operation that is supported by Artificial Intelligence decision making algorithms. Rooftop solar PV energy systems are under design with smart meters. The project is targeting energy saving and bill reduction by at least 30% and as a result a reduction of carbon footprint will be achieved following the COP27 recommendations.

Stator current signal crossing for fault diagnosis of self-excited induction generators

This paper presents a novel method for modelling and diagnosis of electrical and mechanical faults in fixed-Speed Self-Excited Induction Generators (SEIGs) operating in autonomous mode in a small-scale wind energy system. The proposed method is validated using the finite element method. After the selection of the magnetising capacitors, the self-excitation process is performed under no-load conditions. Once the stator voltage is established, a symmetrical three-phase load is connected. The fault detection method introduced here is called Stator Current Signal Crossing (SCSC). The SCSC extracts a new signal from the stator currents, that enables the detection of stator inter turn shortcircuits, broken rotor bars, and dynamic eccentricity faults in SEIGs. A spectral analysis of SCSC using the Fast Fourier Transform (FFT) algorithm is used to precisely locate the induced fault components. What sets this fault-tracking method apart from its predecessors is its exceptional ability to detect faults of any magnitude by analysing the modulation of the SCSC signal. These faults are directly identified by the presence of distinct harmonics, each indicative of a specific type of fault. This study also focuses on the SEIG in a wind energy system, whereas previous works have mainly addressed the induction machine in motor mode. In contrast, previous methods involved analysing a single current signal and isolating specific harmonics from a wide frequency range. The effectiveness of the proposed fault detection method and the self-excitation process are illustrated by simulation results and spectral analysis.

REFRIGERADOR PORTÁTIL ALIMENTADO POR ENERGIA RENOVÁVEL

This study is about the design of a portable refrigerator powered by renewable energy. Research is done on small scale solar and wind energy availability. The refrigeration is generated by thermoelectric modules, also known as Peltier modules. A successful refrigeration project begins with the correct calculation of the heating load. These calculations are based on local data from the intended area of operation (Tramandaí). The Peltier module selection is done through a heat transfer analysis based on the heat sinks used on the design and using the datasheet provided by the module manufacturer. The software EnergyPlus is used to calculate the available power provided by the photovoltaic panel during operation. Finally a brief study about the system electric components is done and its connections are represented in a simplified drawing. The design of the portable refrigerator has some physical and energetic constraints, like the large size and weight of its components, great energy consume by the Peltier modules and the low rate of energy powered by the renewable sources, adding a limitation to the heating. However, when the product is placed at 5 °C in the refrigerator, the temperature is preserved, and the refrigerator works within its limitations energy.

Direct wind-powered vertical axis brackish water desalination system

The supply of freshwater based on wind-powered desalination is technically feasible, but energetic losses associated with conventional systems necessitate new approaches. This study explores a direct wind-powered desalination (D-WPD) system using a small-scale vertical axis wind turbine (VAWT) for reverse osmosis via a high-pressure pump without electricity generation or a system controller. A comprehensive parametric study examined the effects of feed water salinity, loading, and wind speed on the system's performance, demonstrating high efficiency under various operating conditions. A stand-alone system demonstrated operation at effectively constant system efficiency, approximately 13.5 %, and low specific energy consumption for a wide range of wind speeds and salinities. Despite the turbine's small projected area of 0.8 m2, the D-WPD system yielded a daily permeate production of up to 0.6 m3/day at an average wind speed of 6 m/s. The D-WPD system surpassed previous wind-powered desalination studies in terms of specific energy consumption, relative efficiency, and relative desalination capacity. Leveraging the environmental benefits of the slow-spinning VAWT, this D-WPD offers a cost-effective off-grid solution for small-scale desalination.

An adaptive nested dynamic downscaling strategy of wind-field for real-time risk forecast of power transmission systems during tropical cyclones

High winds from tropical cyclones can cause significant damages to power transmission system and lead to widespread power outages resulting in tangible socio-economic losses. Meteorological numerical weather prediction (NWP) models can provide real-time wind-field forecasts, making it possible to conduct real-time risk forecasts of regional-scale power transmission systems in order to inform proactive risk mitigation interventions. However, the operationally employed NWP simulates wind-fields at mesoscales (1∼10km) which is too coarse to capture the wind dynamics of transmission towers (generally covering an area of 25m*25m or less) and conductors over complex terrains. While dynamic downscaling can resolve topographic features into mesoscale wind-field to obtain small-scale (100m∼1km) or micro-scale (10∼100m) wind predictions, it requires practically unattainable computational resources for regional-scale operations in real-time. To address these challenges, we propose an Adaptive Nested Dynamic Downscaling (ANDD) strategy, which (i) spatially considers terrain features, and topology and failure mechanisms of transmission systems; and (ii) temporally adapts to the evolution of an approaching cyclone in real time, enabling the downscaling domains to be reconfigured based on the latest mesoscale NWP. The advantages of the ANDD strategy are illustrated through the power transmission system in Zhejiang Province (105,500 km2), China, during Super Typhoon Lekima of 2019.

Experimental study on the evolution of wind turbine wake under streamwise pressure gradients

Wind tunnel experiments were conducted to explore how streamwise pressure gradients, commonly encountered in complex terrains, influence the wake behavior of a small-scale horizontal-axis wind turbine. The study involved measuring the wake characteristics up to 8 rotor diameters downstream in three pressure gradient scenarios: adverse (APG), favourable (FPG), and zero (ZPG) pressure gradients, assessed using the pressure coefficient (Cp) and its spatial gradient (ΔCp/Δx). These experiments were conducted at a rotor diameter Reynolds number of 96,000 with an inflow velocity of 10 m/s. The results indicate that while the pressure gradients have a more substantial impact on the wake’s velocity deficit, they have a minor effect on its velocity distribution. Nevertheless, non-zero pressure gradients cause significant deformations in the wake’s shape and vertical displacement of its center. Specifically, the FPG case demonstrates enhanced wake velocity recovery, whereas the APG case exhibits slower recovery than the ZPG case. Turbulent kinetic energy decreases as the wake progresses downstream in all cases, with the APG case consistently showing higher values at all measurement locations. Moreover, a consistent pattern of axial vorticity is observed close to the rotor across different pressure gradient cases, with the FPG case displaying notable organisation and amplification of axial vorticity.

An Optimal Operation Strategy for Collaborative Flexibility Provision of a Carbon Capture and Utilization Process With Wind Energy

Improving power system flexibility by responsive demand is essential for integrating wind energy with a high level of variability in power systems. Carbon dioxide-based chemical processes as energy-intensive industrial loads may offer a vast potential of new forms of flexible operation due to their existing control infrastructure and storage capabilities. However, a collaborative decision model is needed for optimal energy sharing among the chemical plant and the grid under the variations and uncertainties of wind power. This study develops an optimal two-stage stochastic programming model for a novel flexible operation strategy of the chemical process coupled with wind turbines. In the proposed control scheme, a small-scale wind farm provides the power input of a chemical plant. Wind turbines are connected to the grid and actively participate in the day-ahead energy and reserve markets, considering the chemical plant as a source of flexibility. An equivalent scenario-based model of the proposed optimization problem is suggested using the Group Method of Data Handling (GMDH) for a data-driven prediction of stochastic variables. Simulation results demonstrate the effectiveness and significance of the proposed approach for an optimal and collaborative contribution in ancillary market of a carbon dioxide-based chemical plant supplied by wind energy.