Power Output Of Wind Turbine Research Articles

Ultra-Short-Term Wind Power Forecasting in Complex Terrain: A Physics-Based Approach

This paper proposes a method based on Computational Fluid Dynamics (CFD) and the detection of Wind Energy Extraction Latency for a given wind turbine (WT) designed for ultra-short-term (UST) wind energy forecasting over complex terrain. The core of the suggested modeling approach is the Wind Spatial Extrapolation model (WiSpEx). Measured vertical wind profile data are used as the inlet for stationary CFD simulations to reconstruct the wind flow over a wind farm (WF). This wind field reconstruction helps operators obtain the wind speed and available wind energy at the hub height of the installed WTs, enabling the estimation of their energy production. WT power output is calculated by accounting for the average time it takes for the turbine to adjust its power output in response to changes in wind speed. The proposed method is evaluated with data from two WTs (E40-500, NM 750/48). The wind speed dataset used for this study contains ramp events and wind speeds that range in magnitude from 3 m/s to 18 m/s. The results show that the proposed method can achieve a Symmetric Mean Absolute Percentage Error (SMAPE) of 8.44% for E40-500 and 9.26% for NM 750/48, even with significant simplifications, while the SMAPE of the persistence model is above 15.03% for E40-500 and 16.12% for NM 750/48. Each forecast requires less than two minutes of computational time on a low-cost commercial platform. This performance is comparable to state-of-the-art methods and significantly faster than time-dependent simulations. Such simulations necessitate excessive computational resources, making them impractical for online forecasting.

Axial hysterestic behavior of prestressed CFDST columns for lattice-type wind turbine towers

The escalating power outputs of wind turbines necessitate enhanced load-bearing capabilities in their support structures. A new type of prestressed concrete-filled double skin steel tubular (CFDST) lattice-type wind turbine tower has been proposed to replace the original steel-concrete hybrid tower. The corner columns of the tower are made of prestressed CFDST columns, with the prestressing steel strands situated within the hollow area. While numerous studies have researched the axial characteristics of concrete-filled steel tubular (CFST) columns, investigations into prestressed CFDST columns subjected to axial cyclic loading remain sparse. To address this research gap, this study carried out the experimental and finite element studies of eight prestressed CFDST columns under axial tensile, axial compressive, and tensile-compressive cyclic loads. Detailed analyses of failure modes, hysteresis curves, stiffness degradation, skeleton curves and ductility were conducted. The test results indicate that the prestressing enables the concrete to establish good contact with the steel tubes, thereby preventing the premature cracking. At a cost of approximately 6.8 % reduction in axial compressive load, the axial tensile load of the structure is enhanced by about 47.2 %. Furthermore, an advanced finite element (FE) model, refined based on the test, closely matched the experimental data, thereby validating its accuracy for subsequent mechanism and parameter investigation.

Adaptive fuzzy coordinated control design for wind turbine using gray wolf optimization algorithm

Due to the randomness and intermittency of wind speed, the actual output power curve of a wind turbine (WT) deviates greatly from the theoretical power curve, thereby reducing the power generation capacity of the WT. An adaptive fuzzy coordinated control (AFCC) of WT is presented in this study to improve the power generation of WT. Firstly, a multi-objective optimization model (MOOM) for WT output power, generator speed and pitch angle is established, and its optimal solution set is used as the input eigenvector of a novel effective wind speed soft sensor (NEWSSS) model, which is modeled with kernel extreme learning machine (KELM). Secondly, a novel improved gray wolf optimization (NIGWO) algorithm is presented by improving the convergence factor and adaptive weights, which is used to solve MOOM and optimize the parameters of KELM. A variable pitch control (VPC) is designed by estimating the effective wind speed. Finally, an adaptive fuzzy control (AFC) is presented for WT. Based on the AFC and VPC, an AFCC for pitch angle and generator torque is designed for WT. The high measuring precision of NEWSSS and the good robustness and dynamic performance of AFCC are demonstrated by the simulation results.

Investigation of wind turbine unsteady aerodynamics and trailing-edge noise characteristics under wake steering

In wake steering strategy, the shaft of an upstream wind turbine is yawed to deflect the wake and decrease the wake-swept area of the downstream wind turbine rotor. This intentional yaw misalignment increases the output power of the downstream wind turbine at the expense of some loss of upstream wind turbine power, consequently increasing the total wind farm power. However, the asymmetric non-uniform inflow into the downstream wind turbine due to the deflected wake causes unsteady aerodynamic loads and affects the wind turbine noise characteristics. In this study, the unsteady vortex lattice method coupled with the curled wake model is used to predict the unsteady aerodynamics of a downstream wind turbine in wake steering. Based on the unsteady aerodynamic results, the trailing-edge noise characteristics are predicted by a semi-empirical method. The impact of wake steering on trailing-edge noise level and amplitude modulation is evaluated. The results show that the asymmetric non-uniform inflow due to wake steering increases the amplitude modulation of the downstream wind turbine.

A bi‐level optimization model and improved algorithm for wind farm layout

AbstractWind farm can obtain the maximize profit by optimizing micro‐locations and cables. The factors that affect profit include the power output of wind turbines, cost and et al., where power output is affected by wake effect, cable cost is related to the length and type of collector cable. The profit is calculated on the premise that the costs and power loss of collector cable are determined. Obviously, there is a hierarchical relationship between the above problems. Therefore, a bi‐level optimization model with constraints is constructed in this paper, where the upper‐level objective function is the maximum profit, and the lower‐level objective functions are consists of minimum the cable cost and the power loss of collector cable; Moreover, an improved algorithm (IDEDA), based on differential evolution and Dijkstra, is used to optimize above model; Finally, simulation experiments are carried out for IDEDA and four algorithms for two different wind conditions, and the results show that IDEDA performs better compared to the other four algorithms in terms of profit and cable cost.

Front Deflector Effects on the Aerodynamic Characteristics of Horizontal Axis Wind Turbines: A Reynolds‐Averaged Navier–Stokes Simulation Study

Flow control devices have garnered significant attention from domestic and international wind energy scholars. In an effort to capture more wind energy and boost the output power of wind turbines, this study incorporates flow control devices into the upstream area of the wind turbine. The study then assesses the impact of the spacing, tilt angle, and height of the flow control devices on the turbine's performance. The study demonstrates that the addition of flow control devices does lead to a notable enhancement in wind turbine power, with a maximum power output growth rate of 9.74%. The maximum growth rates for the average output power of the wind turbine due to the three factors (α, H, and Lw) are 4.20%, 3.76%, and 3.54%, respectively. The degree of influence of the three factors is as follows: α > H > Lw.

Fluctuating pressure gradients and corrugated surfaces effects on wind turbines power output

This paper investigates the effect of corrugated surfaces on the wind turbines power output for both laminar and turbulent flows. Conservation principles including continuity and momentum equations, wind turbine power equations, and the corrugated surface equation have been implemented to build up a theoretical model then which has been solved using MATLAB. This model simulates wind turbines power output and analyzes several case studies implementing different parameters such as air pressure wave amplitude (Po), air wave fluctuation frequency (n), and wind layer turbulence (b). Also, different complex terrains in two main scenarios representing two different positions (X) of the wind turbine are analyzed. This analysis indicates the importance of wind turbines micro siting. In addition, it is found that increasing the pressure ratio increased wind turbine power output, while increasing the frequency decreased the power ratio of the wind turbines for both laminar and turbulent flow conditions. Increasing turbulence for the turbulent model increased the power ratio.

Development of Active Wind Vane for Low-Power Wind Turbines

This paper proposes the development of an active control system to control the power output of a low-power horizontal-axis wind turbine (HAWT) when operating at wind speeds above the rated wind speed. The system is composed of an active articulated vane (AAV) in charge of the orientation of the wind turbine, which is driven by an electric actuator that changes the angle of the AAV to maintain a constant power output. Compared with the passive power regulation systems most often used in low-power HAWTs, active systems allow for better control and, therefore, greater stability of the delivered power, which reduces the structural stresses and allows for controlled braking in any wind condition or during system failures. The control system was designed and simulated using MATLAB R2022b software, and then built and evaluated under laboratory conditions. For the control design, the transfer function (TF) between the pulse width modulation (PWM) and the AAV angle (θ) was determined via laboratory tests using MATLAB’s PIDTurner tool. For the simulation, the relationship between the power output and the AAV angle was determined using the vector decomposition of the wind speed and wind rotor area. Wind speed step and ramp response tests were performed for proportional–integral–derivative (PID) control. The results obtained demonstrate the technical feasibility of this type of control, obtaining settling times (ts) of 6.7 s in the step response and 2.8 s in the ramp response.

Enhancing wind power with permanent magnet synchronous generator control strategies

AbstractDue to the substantial rise in wind power generation, the direct-drive permanent magnet synchronous generator has emerged as a leading technology for efficient variable speed operation, meeting grid demands effectively. This paper presents a comparative analysis of control strategies for permanent magnet synchronous generator based wind turbine using real variable wind speed data from a 2 MW of Tetouan wind farm in Morocco. The proposed approach is based on evaluating two primary control strategies: the adaptive fuzzy-proportional-integral controller and the conventional proportional-integral controller aimed at enhancing the wind turbine's output power. The simulation performed on MATLAB-Simulink indicates that pitch control mechanisms play a crucial role in optimizing power generation, also demonstrating its ability to achieve satisfactory performance.

A novel strategy to enhance power management in AC/DC hybrid microgrid using virtual synchronous generator based interlinking converters integrated with energy storage system

Hybrid microgrids (HMGs) have a flexible structure, higher reliability, and both AC and DC MG merits. However, in this type of MGs, there are challenges such as accurate power sharing, the voltage control of the DC link, the AC side voltage and frequency stability, the negative impact of telecommunication delay, and so on. Therefore, a power management scheme is presented here that can perform proper and precise power sharing in a hybrid AC/DC MG. This HMG consists of one energy storage system (ESS) along with two interlinking converters (ILC) based on a virtual synchronous generator (VSG). Besides, the physical inertia of a MG is less than that of a power grid, hence, changing the output power of wind turbines and photovoltaic (PV) arrays might make system unstable. To overcome this challenge, virtual inertia is used. As the virtual inertia can be embedded with the VSG method, in this scheme, the VSG strategy is implemented to enhance the system dynamic behavior by imitating the synchronous generator kinetic inertia. The VSG-based ILC1 converter is used to establish interlinking and energy exchange between AC and DC sub-grids and share power. Also, other interlink devices including a bidirectional half-wave DC/DC converter integrated with the ILC2 are considered, which aim to control the voltage of the DC link and exchange part of the power between the AC and DC sub-grids. An ESS is placed between the bidirectional DC/DC converters and the DC link of the ILC2. Such a structure is referred to as a two stage interlinking converter with an ESS (TSILC-ESS). The power management system employed in AC/DC HMG according to the ILC controller is utilized to form the DCMG along with controlling the TSILC-ESS, providing additional and auxiliary services to the power grid. To assess the introduced scheme of both AC and DCMG to investigate VSG-based ILC1 and ILC2 in grid-connected and islanded operational mods, various resource and load profiles are assumed. The simulation study is performed in MATLAB/ Simulink environment to confirm the proposed method.

Impact of incoming turbulence intensity and turbine spacing on output power density: A study with two 5MW offshore wind turbines

Turbulence intensity in offshore environments has significant effects on the performance of offshore wind turbines. To maximize output power of offshore wind turbines within a limited space, i.e., achieving maximum output power density, it is essential to investigate the influences of incoming turbulence intensity and turbine spacing on output power density. The Large Eddy Simulation coupled Actuator Line Method (LES-ALM) is used in this study to simulate two utility-scale NREL-5 MW wind turbines in different turbulent environments and turbine spacings. The optimal incoming turbulence intensity and turbine spacing are identified using an active learning method. The determined optimal parameters act as a benchmark for the impact analysis. The findings indicate that the increase of turbine spacing initially results in a considerable rise in the output power density of the two NREL-5 MW wind turbines, followed by a slight downward trend across various turbulent environments. The increase of the incoming turbulence leads to a steady rise of the output power density when the turbine spacing is less than 5.1D (D is the rotor diameter), while a rise followed by a decrease in the output power density is observed for the turbine spacing exceeding 5.1D. Notably, when the turbine spacing is 5.9D and the reference value of turbulence intensity is 15.2%, the output power density reaches its global maximum.

Urban energy transition in renewable energy management considering policy and law challenges and opportunities in the pursuit of clean and sustainable urban environments

This research presents a novel approach to enhance sustainable energy development based on wind turbine (WT) output power prediction through the development of a hybrid deep learning model, considering policy and law challenges associated with the problem. The proposed model integrates a Self-Supervised Generative Adversarial Network (GAN) with Attention-based Recurrent Neural Networks (RNNs). The Self-Supervised GAN contributes to improved feature representation learning, while Attention-based RNNs capture temporal dependencies for accurate WT output power forecasting considering political challenges. Additionally, a Modified Adaptive Flower Pollination Algorithm (AFPA) is introduced to optimize the selection of the GAN model structure in view of the legal and political objectives. This adaptive approach refines the architecture of the GAN, enhancing its ability to generate realistic and informative features for the subsequent Attention-based RNNs. The efficacy of the hybrid model is demonstrated through real-world applications in an urban area, emphasizing sensitivity and stability analyses. A thorough investigation into the sensitivity of key model parameters, including the number of hidden units in the Attention-based RNNs and GAN structures, is conducted to fine-tune the model's performance. Stability analysis is employed to assess the robustness of the proposed method under dynamic conditions, ensuring its reliability in practical scenarios. Results indicate that the hybrid model, guided by the Modified AFPA, outperforms existing approaches in WT output power prediction. The proposed methodology showcases the significance of combining state-of-the-art deep learning techniques with adaptive optimization algorithms for accurate and stable predictions in urban energy management applications.

Experimental Study on Aerodynamic Characteristics of Downwind Bionic Tower Wind Turbine.

The vibrissae of harbor seals exhibit a distinct three-dimensional structure compared to circular cylinders, resulting in a wave-shaped configuration that effectively reduces drag and suppresses vortex shedding in the wake. However, this unique cylinder design has not yet been applied to wind power technologies. Therefore, this study applies this concept to the design of downwind wind turbines and employs wind tunnel testing to compare the wake flow characteristics of a single-cylinder model while also investigating the output power and wake performance of the model wind turbine. Herein, we demonstrate that in the single-cylinder test, the bionic case shows reduced turbulence intensity in its wake compared to that observed with the circular cylinder case. The difference in the energy distribution in the frequency domain behind the cylinder was mainly manifested in the near-wake region. Moreover, our findings indicate that differences in power coefficient are predominantly noticeable with high tip speed ratios. Furthermore, as output power increases, this bionic cylindrical structure induces greater velocity deficit and higher turbulence intensity behind the rotor. These results provide valuable insights for optimizing aerodynamic designs of wind turbines towards achieving enhanced efficiency for converting wind energy.

Lattice Boltzmann simulation for wake interactions of aligned wind turbines using actuator line model with turbine control

A wind turbine wake causes a decrease in wind speed and an increase in turbulence intensity. The wind turbine wake interaction is essential for predicting the power output of a wind farm consisting of many wind turbines. This research proposes a CFD method able to reproduce wake interactions and power outputs of multiple wind turbines with high speed and accuracy. Large eddy simulations with the lattice Boltzmann method are used for fluid calculations, specifically for large-scale CFD simulations. The wind turbines are represented using an actuator line model. Optimal power generation efficiency is achieved by controlling the rotor speed and blade pitch angle. Large-scale simulations of eight aligned wind turbines are conducted using 1.75 billion grid points and 40 GPUs. We compare two cases with and without control to investigate the effect of turbine control on wake and power output. Both the instantaneous and mean streamwise velocities confirm that the turbine control reduces the wake velocity deficit of the downwind wind turbine. High-speed inflow of wind to the downstream turbines augments their power output. With implementation of turbine control, the power outputs of the downstream turbines agree well with the observation data obtained in an earlier study. The results demonstrate the importance of controlling the rotational speed and pitch angle for actuator line simulations.

Estimating the performance of wind turbines misaligned with respect to the wind direction using a simplified CFD based approach

Wind direction in atmospheric boundary layer changes constantly. As such, the power extracted from the wind turbines in a wind farm is subjected to change. This change in wind direction impacts the wake pattern which in turn affects the power output of the downstream wind turbines. Empirical wind farm models are useful in such cases to assess the overall performance of the wind farms. However, the results provided by these models can be made more useful if fluid-structure interaction (FSI) effects are also considered. In the present work, we begin by looking at the potential flow model and the issues associated with it and used a modified model with constant vorticity to analyze the wind power available to the downstream wind turbines in a wind farm misaligned with respect to wind direction for irrotational flow. A simplified FSI based approach is used to carry out the simulations without the need of modelling the complicated wind turbine geometry.

Time-Series Based Surrogate Model For Wind Farm Performance Prediction

Aeroelastic codes are state-of-the-art simulation tools in both industry and academia for the modelling of wind turbine loads and power output. Although these codes are widely used for the analysis of individual turbines, they are in general computationally too expensive for the calculation of all turbines within a wind farm. Engineering models that are computationally cheaper but also provide a lower fidelity are therefore typically used for wind farm power performance predictions. In this paper, an alternative approach to simulate wind farm performance is presented: the use of a data-driven surrogate model that is trained on time series that were generated by the in-house aeroelastic tool BHawC. This surrogate model provides results with potentially higher fidelity than more simplistic engineering models but is computationally much cheaper than BHawC simulations.

CFD simulation of a multi-rotor system using diffuser augmented wind turbines by lattice Boltzmann method

A diffuser-augmented wind turbine (DAWT) achieves greater power generation efficiency by increasing wind speed through the diffuser. Nevertheless, scaling up this technology is difficult because of the considerable amount of wind drag on the diffusers. To overcome this difficulty, a multi-rotor system with two or more wind turbines on the same structure is one approach to increasing wind turbine power output. This research proposes a computational fluid dynamics (CFD) method to evaluate the hydrodynamic performance of a large-scale multi-rotor system of DAWTs. Compared to conventional wind turbines, CFD simulations of DAWTs necessitate higher computational costs because of the need of high-resolution meshes for the diffuser. Furthermore, the computational cost of a multi-rotor system increases with the number of rotors. To address the issue of high computational cost, we use the Lattice Boltzmann Method (LBM), which is well suited to large-scale CFD simulations. A wind turbine is modeled as an actuator line model and a diffuser as a wall boundary. An adaptive mesh refinement approach generates higher resolution meshes near the rotor and diffuser. LBM simulations were conducted for a single DAWT and a multi-rotor system with five DAWTs. The LBM results of the wake velocity and pressure distributions were in agreement with those obtained from wind tunnel experiments and general CFD methods in earlier studies. To investigate the diffuser gap effects, we simulated five DAWTs with diffuser gaps of 5%–25% of the diffuser diameter. The power gain of each DAWT was assessed. Great performance improvements were found with diffuser gaps of 20% and 25% of the diffuser diameter. On average, the five DAWTs achieved a power gain of more than 10%. These findings confirmed the accurate evaluation capability of the proposed CFD method for hydrodynamic characteristics of multi-rotor systems using DAWTs.

Frequency Regulation Adaptive Control Strategy of Wind Energy Storage System for Wind Speed Uncertainty

In order to reduce the negative influence of wind speed randomness and prediction error on frequency modulation, the reliability of the wind storage system was assessed effectively. In the wind storage frequency modulation system, a state of charge (SOC) adaptive adjustment method for wind speed randomness is proposed. Firstly, through the correlation analysis between the standby capacity of frequency modulation and the output power of wind turbine, the uncertainty of its frequency modulation capacity is revealed. Secondly, in view of the uncertainty of wind turbine frequency modulation, the output power of energy storage frequency modulation is optimized with the goal of minimizing the frequency modulation power deviation of the wind storage front under the framework of model predictive control, and the improved whale optimization algorithm (WOA) is used to solve the problem. Finally, the simulation results show that, under the given 5 min continuous disturbance, the root mean square of frequency regulation of the proposed restoration method is reduced by 56.65% compared to the SOC recovery base point set to 0.5. Under continuous large perturbations, the maximum frequency deviation is reduced by 0.0455 Hz. This effectively shows that this method can not only improve the frequency modulation reliability of wind power system but also improve the continuous frequency modulation capability of energy storage system.

Research on fault detection and remote monitoring system of variable speed constant frequency wind turbine based on Internet of Things

In order to study the operating characteristics of variable speed constant frequency wind turbine under different working conditions and the monitoring system of wind turbine. In this paper, the simulation model of each component system of wind turbine is established by MATLAB/Simulink module, and the influence law of different wind speed and ground fault types on the output power of wind turbine is studied. The active power of wind turbines under different short-circuit fault types is compared. At the same time, in order to realize real-time monitoring of wind turbine speed and output power, an online monitoring system for wind turbine operation based on industrial Internet of Things is proposed, and the composition and operation characteristics of this remote monitoring system are given. The practical application shows that the on-line monitoring system can accurately and remotely monitor the running status of the wind turbine and avoid the unstable running of the wind turbine. The research conclusions of this paper can provide reference for the design and construction of wind turbines and the operation of connecting to the power grid.

RANS representation of transition and separation over a low-Re number blade section at high angle of attack

Systems based on wind energy harvesting can successfully meet part of the increasing green energy demand worldwide. However, wind turbines operation might be undermined by varying atmospheric conditions, which could result in an increase of angle of attack and consequent onset of flow separation phenomena, especially at low Reynolds numbers. Such conditions are strongly influenced by blades geometry, and they negatively affect structural integrity and power output of wind turbines. For this reason, it is crucial to define a tool capable of swiftly allowing numerical investigations on different geometrical configurations to delay and mitigate flow separation occurrence. The present work aims at modelling laminar-turbulent transition and turbulent flow separation over a wind turbine blade section operating at angle of attack = 15°, Re = 66000 and Pr = 0.71 by means of a steady RANS approach. Turbulence is treated by means of the Transition SST k-ω and the Transition k-kL-ω models. The main aerodynamic and thermal coefficients are evaluated and compared against a high-order accurate DNS database for validation. The results highlight, for the present test case, a better capability of the Transition SST k-ω of perceiving the main thermo-fluid dynamic features of the separated flow over the blade section.