Techniques to Increase Power Efficiency from Wind Turbines

This study explores the influence of overlap ratio on performance two- and three-bladed Savonius hydrokinetic turbines to identify optimal configuration for enhanced efficiency. Utilizing computational fluid dynamics simulations in ANSYS Fluent, six distinct blade profiles were analysed under an inlet velocity 0.5 m/s, considering cases with without ratio. The employed unsteady sliding mesh technique accurate flow assessment. Results demonstrated that a 0.15 exhibited superior compared designs ratio, achieving maximum power coefficient 0.2 at tip speed 0.9. These findings underscore critical role geometric optimization, particularly enhancing efficiency turbines, thereby advancing their potential reliable effective energy generation.

Source

Dynamic modelling of wind turbines and their simulation is a very useful tool for studying behaviour. One the key elements concerning physical models power coefficient Cp, which acts as an efficiency in extraction from wind. Unfortunately, this often unknown priori, it does not usually appear information provided by manufacturers. This paper first describes methodology obtaining parameters commercial turbine model using curve manufacturer, indicates theoretical that can produce at each speed. To achieve this, parameter estimation problem formulated solved to determine parameters. Nevertheless, insufficient, requiring additional knowledge, such operational data, improve fit. Finally, new performed only real data measured process, validating proposed methodology. The dataset was obtained SMARTEOLE project France corresponds pitch-controlled variable-speed Senvion MM82/2050 turbine.

Source

The increasing integration of renewable energy, electric vehicles, and industrial applications demands efficient power converter control strategies that reduce switching losses while maintaining high waveform quality. This paper presents a Finite-Control-Set Model Predictive Control (FCS-MPC) strategy for three-phase, two-level voltage source inverters (VSIs), incorporating secondary objective frequency minimization. Unlike conventional MPC approaches, the proposed method optimally balances performance efficiency trade-offs by adjusting weighting factor (min). Real-time implementation using OPAL-RT platform validates effectiveness approach under both linear non-linear load conditions. Results demonstrate significant reduction in losses, accompanied improved tracking; however, distortion are observed scenarios. These findings provide insights into practical real-time predictive high-performance converters.

Source

Method for optimizing wind farm performance by coordinating wind turbine control in a wind farm. The method involves commanding an upstream wind turbine in a wind farm to steer its wake away from a downstream turbine, but only if load levels on the downstream turbine are below a threshold. This prevents excessive loads on the downstream turbine that can lead to maintenance issues. The threshold is adjusted based on demand to balance load reduction vs power loss. The upstream turbine can also perform induction control to weaken wakes, but this is separate from wake steering.

Source

This study explores optimal control strategies for integrating renewable energy sources into power grids, addressing challenges such as intermittency, grid stability, and demand-supply mismatch. The methodology combines model predictive control, robust optimization, load forecasting using machine learning algorithms. Data from solar wind outputs, along with historical demand, were analyzed to build regression models. results demonstrate that adaptive significantly enhance efficiency, reduce operational costs, improve reliability. Findings offer insights designing intelligent systems can dynamically respond fluctuating inputs while maintaining stability. Keywords: Renewable energy, integration, learning, efficiency

Source

Active wake control (AWC) has emerged as a promising strategy for enhancing wind turbine recovery, but accurately modelling its underlying fluid mechanisms remains challenging. This study presents computationally efficient model that provides end-to-end prediction capability from rotor actuation to recovery enhancement by capturing the coupled dynamics of meandering and mean flow modification, requiring only two inputs: reference without user-defined AWC strategy. The combines physics-based resolvent large-scale coherent structures an eddy viscosity small-scale turbulence. A Reynolds stress is introduced account influence both incoherent fluctuations, so time-averaged enhanced can be quantitatively predicted. Validation against large-eddy simulations (LES) across various approaches actuating frequencies demonstrates models predictive capability, AWC-specific frequency-dependent with less than 8 % error LES while reducing computational time thousands central-processing-unit hours minutes. efficiency accuracy makes it tool practical design optimization farms.

Source

Controlling wind turbines using a predictive controller that improves load handling and avoids component failures by accurately modeling loads and constraints. The method involves using a wind turbine model with a predictive aeroelastic module to estimate future loads based on current operating data. A strength calculation module calculates secondary load parameters from the primary loads. Optimization over a finite period subjects to constraints on the secondary loads. Commands are generated to control the wind turbine actuators. This allows optimal actions to capture more power while avoiding overloads. The predictive modeling allows accounting for true limiting factors rather than conservative assumptions.

Source

Optimizing power output of wind farms with multiple wind turbines by dynamically adjusting the yaw angle of upwind turbines to mitigate wake effects on downwind turbines. The yaw steer is determined based on a net energy gain calculation that balances increased power from reduced wake with the cost of yaw adjustment. Clustering of turbines affected by wake is ranked based on net energy gain and only the best clusters receive yaw steers above a threshold. This prevents excessive yaw adjustment wear while maximizing overall farm power.

Source

The increasing integration of wind turbines into the power grid has reduced system frequency stability, necessitating energy storage systems in primary regulation. This paper proposes an MPC-based control method to optimize response a combined windstorage system. An evaluation is also developed characterize stability and guide dispatch. First, model state-space equations for MPC are established. Then, strategy proposed achieve objective minimizing variation deviation. Finally, assessed using MATLAB/Simulink case studies confirm effectiveness enhancing regulation performance. results show that this not only accelerates speed but reduces its fluctuations, thereby improving

Source

In this work, the optimization of wind turbines is considered by introducing a cylindrical blade with an activedeflector. The use metal (aluminum) deflector, compared plastic (polypropylene), significantly increasedthe aerodynamic efficiency blade. It shown that aluminum deflector reduces dragforce 1820 % and increases lifting force 2.7 times. maximum reached 2.16 N at awind speed 15 m/s deflector. addition, achieveda higher rotation up to 1100 rpm, which 10 polypropylenedeflector. improved performance due high rigidity minimal deformation aluminummaterial under influence air flow. active eliminates need for additionaltriggers, simplifying design reducing operating costs. results obtained indicate useof Magnus contributes developmentof renewable energy technologies.

Source

Distributed wind farm control using consensus estimates of local wind conditions to improve performance and resiliency. The technique involves having wind turbines in a farm communicate their measured wind data to nearby turbines. By comparing and averaging the local wind estimates, a consensus wind estimate is determined for each turbine. This consensus wind is then used as input to the turbine's own controller instead of its local measurement. It allows leveraging nearby turbine data to make better wind direction estimates and reduce unnecessary yaw motions.

Source

Adaptive wind farm control that optimizes power production and grid stability by dynamically adjusting the wind turbine control strategies based on the wind farm conditions. The control system has a wind farm state input to receive data like number of turbines, wind speeds, availability, etc. This farm state is used to modify the wind turbine controller parameters and structure to better suit the current operating conditions. This allows the turbines to adapt their control settings for optimal performance when factors like turbine count, wind variability, and grid stability change.

Source

Estimating when a component of a wind turbine needs replacement based on the remaining producible energy until failure rather than just remaining useful lifetime. This provides a more useful metric for optimizing turbine operation and maintenance scheduling because it relates directly to power yield. The method involves estimating the remaining energy until component replacement using machine learning with trained neural networks. The neural network is trained using data from multiple turbines to predict the remaining energy based on operational and environmental parameters. If the estimated remaining energy is below a threshold, it indicates the component needs replacement.

Source

This study was performed based on the previous work of this research group to promote practical engineering application trailing edge flaps. Specifically, established intelligent blade simulation platform used for calculations, bringing about achievement a significant load reduction effect in which standard deviation blade root pitching moment decreased by 12.4% under influence flap. Then, dynamic conditions wind turbine and flap active control, obtained from platform, were input into CFD further high-fidelity simulations. Additionally, method that allows real-time observation flow field optimized with as visualizer. approach assisted analyzing how affects characteristics around blade. The results reveal deflection generated new vortex structures. These structures interacted pre-existing Moreover, produced supplemented energy dissipation caused separation leeward surface blade, contributing weakening side affecting pressure exerted fluid surface, ultimately lowering blades load.

Source

This paper presents a comprehensive study on the mathematical modeling, simulation, and experimental validation of electrical power output wind turbine system. The research begins with developing models to determine useful generated by under varying operational conditions. These are then simulated using MATLAB/Simulink predict system's performance. A physical prototype system is constructed collect data real-world Finally, results compared validate accuracy models. maximum relative error observed between 1.71 %, highlighting reliability proposed demonstrates effectiveness approach for predicting performance offers valuable insights into design optimization small-scale energy systems.

Source

Supplying power to an electrically isolated wind farm in low wind conditions using a smaller auxiliary power source. The method involves sequentially connecting the turbines to the auxiliary source instead of the grid when wind speeds are low. The first turbine is connected to the auxiliary source, then subsequent turbines one by one. This allows the auxiliary source to provide active power and reactive power to balance the turbines' requirements. The grid connection can be left open. The first turbine connects the auxiliary source to the turbine string. This avoids needing a large auxiliary source to handle the full turbine load since only the first turbine's needs are supplied.

Source

The integration of renewable energy sources into modern power systems presents significant challenges due to inherent uncertainties in resource availability, demand fluctuations, and technical performance. Monte Carlo simulation has emerged as a powerful tool for addressing these planning optimization. This paper comprehensive review applications across solar, wind, hybrid over the past two decades. Through systematic analysis 75+ peer-reviewed publications, we identify key methodological trends, implementation challenges, emerging opportunities. reveals that while methods have been extensively applied single-source systems, gaps exist correlated configurations real-time operational scenarios. We propose novel unified framework integrates machine learning-enhanced sampling techniques with traditional approaches improve computational efficiency maintaining accuracy. addresses five critical uncertainty dimensions: variability, stochasticity, equipment degradation, market price grid constraints. Case studies demonstrate proposed reduces time by 40-60% compared improving prediction accur... Read More

Source

This study investigates the optimum aerodynamic performance of small-scale Horizontal Axis Wind Turbines (HAWTs) utilizing a mixed-airfoil blade design. The QBlade software was employed for selection best performing airfoils based on lift-to-drag ratio and range operational performance. Additionally, Blade Element Momentum (BEM) theory deployed analysis blade's design Finally, in Computational Fluid Dynamics (CFD), SST k- turbulent model also applied better analysis. key findings demonstrated that optimal including SG6040 (root), NACA 4711 (middle), SG6043 (tip), were chosen their superior structural integrity. Furthermore, designed achieved power coefficients 0.454 (BEM), 0.432 (QBlade), 0.395 (CFD) at Tip Speed Ratio (TSR) 5.5, which are greater than conventional single-airfoil designs. It concluded configurations significantly enhance efficiency small scale wind turbines, future research torque control mechanism integration is essential to further optimize energy capture.

Source

Vertical-axis wind turbines (VAWTs) are increasingly recognized as the preferred choice for large-scale energy harvesting, particularly in offshore environments, due to their unique advantages, including omni-directional capability and lower installation maintenance costs. Variations terrain different phases of diurnal cycle create distinct atmospheric boundary layer (ABL) conditions, which inevitably have a significant impact on aerodynamic wake characteristics VAWTs. To systematically observe these effects, this study employs large-eddy simulation explore influence four representative ABL scenarios The results indicate that influences VAWT performance sensitive height. ABLs with higher shear coefficients (WSCs) result greater velocity deficits (VDs) near-wake regions, while turbulence intensity (TI) fluctuations increase rising WSC. Higher heights facilitate faster recovery both VD TI. Furthermore, vortex stability is affected by conditions height, WSCs or bring unsteady break positions closer rotor, thus enhancing turbulence. Modal decomposition reveals dominant mode frequency acr... Read More

Source

ABSTRACT In the present paper, a reinforcement learning (RL)based faulttolerant control scheme is developed for variablespeed wind turbines in event of actuator faults and disturbance torque. The designed controller law an aggregate two subcontrollers: equivalent to achieve maximum power capture RLbased robust mitigate impacts development RL controller, estimated fault term from observer utilized create adequate cost function so that rejection problem can be transformed into optimal problem. Then, by using online policy iteration algorithm minimize function, derived. stability closedloop system guaranteed via Lyapunov theorem. Simulation results demonstrate effectiveness proposed method compared some existing results.

Source