Performance Analysis Of Wind Turbine Research Articles

Advanced Methods for Wind Turbine Performance Analysis Based on SCADA Data and CFD Simulations

Deep comprehension of wind farm performance is a complicated task due to the multivariate dependence of wind turbine power on environmental variables and working parameters and to the intrinsic limitations in the quality of SCADA-collected measurements. Given this, the objective of this study is to propose an integrated approach based on SCADA data and Computational Fluid Dynamics simulations, which is aimed at wind farm performance analysis. The selected test case is a wind farm situated in southern Italy, where two wind turbines had an apparent underperformance. The concept of a space–time comparison at the wind farm level is leveraged by analyzing the operation curves of the wind turbines and by comparing the simulated average wind field against the measured one, where each wind turbine is treated like a virtual meteorological mast. The employed formulation for the CFD simulations is Reynolds-Average Navier–Stokes (RANS). In this work, it is shown that, based on the above approach, it has been possible to identify an anemometer bias at a wind turbine, which has subsequently been fixed. The results of this work affirm that a deep comprehension of wind farm performance requires a non-trivial space–time comparison, of which CFD simulations can be a fundamental part.

Multivariate Data-Driven Models for Wind Turbine Power Curves including Sub-Component Temperatures

The most commonly employed tool for wind turbine performance analysis is the power curve, which is the relation between wind intensity and power. The diffusion of SCADA systems has boosted the adoption of data-driven approaches to power curves. In particular, a recent research line involves multivariate methods, employing further input variables in addition to the wind speed. In this work, an innovative contribution is investigated, which is the inclusion of thirteen sub-component temperatures as possible covariates. This is discussed through a real-world test case, based on data provided by ENGIE Italia. Two models are analyzed: support vector regression with Gaussian kernel and Gaussian process regression. The input variables are individuated through a sequential feature selection algorithm. The sub-component temperatures are abundantly selected as input variables, proving the validity of the idea proposed in this work. The obtained error metrics are lower with respect to benchmark models employing more typical input variables: the resulting mean absolute error is 1.35% of the rated power. The results of the two types of selected regressions are not remarkably different. This supports that the qualifying points are, rather than the model type, the use and the selection of a potentially vast number of input variables.

Discussion of Wind Turbine Performance Based on SCADA Data and Multiple Test Case Analysis

This work is devoted to the formulation of innovative SCADA-based methods for wind turbine performance analysis and interpretation. The work is organized as an academia–industry collaboration: three test cases are analyzed, two with hydraulic pitch control (Vestas V90 and V100) and one with electric pitch control (Senvion MM92). The investigation is based on the method of bins, on a polynomial regression applied to operation curves that have never been analyzed in detail in the literature before, and on correlation and causality analysis. A key point is the analysis of measurement channels related to the blade pitch control and to the rotor: pitch manifold pressure, pitch piston traveled distance and tower vibrations for the hydraulic pitch wind turbines, and blade pitch current for the electric pitch wind turbines. The main result of this study is that cases of noticeable under-performance are observed for the hydraulic pitch wind turbines, which are associated with pitch pressure decrease in time for one case and to suspected rotor unbalance for another case. On the other way round, the behavior of the rotational speed and blade pitch curves is homogeneous and stable for the wind turbines electrically controlled. Summarizing, the evidence collected in this work identifies the hydraulic pitch as a sensible component of the wind turbine that should be monitored cautiously because it is likely associated with performance decline with age.

Blade Design and Performance Analysis of Wind Turbine

Abstract: This paper reviews the design optimization of wind turbine blades through investigating the design methods and analyzing the performance of the blades. The current research work in this area include wind turbine blade geometric design and optimization, aerodynamics analysis, wind turbine blade structural design and dynamics analysis. Blade geometric design addresses the design parameters, including airfoils and their aerodynamic coefficients, attack angles, design tip speed ratio, design and/or rated wind speed, rotor diameter, blade aerodynamic shape with chord length and twist distributions, so that the blade achieves an optimum powerperformance. The geometry of the blade is an aerodynamic shape with nonlinear chord and twist distribution, which can be obtained based on the BEM theory with respect to given aerofoil with known aerodynamic coefficients. In terms of blade aerodynamics analysis, there are four types of aerodynamic models which can be used to predict the aerodynamic performance of blades, including blade element momentum (BEM) model, lifting panel and vortex model, actuator line model, and computational fluid dynamics (CFD) model. Among the four, computational fluid dynamics (CFD) model has been used to calculate the aerodynamic effect on the bladeairfoil. Critical Reynolds number and constant wind speed has been considered during analysis under different turbulence models Viz, spallart-almaras, k-epsilon, invicid flow. During investigation it is observed that only k- epsilon showed efficient results than others and 14 degree angle of attack (AOA) is the optimum value at which there is much lift coefficient and minimum drag

Performance analysis of wind turbines with leading-edge erosion and erosion-safe mode operation

For offshore wind turbines, Leading-Edge Erosion (LEE) due to rain is posing a serious risk to structural integrity and can lead to a performance loss of the order of a few percent of the Annual Energy Production (AEP). A proposed mitigation strategy is the so-called Erosion-Safe Mode (ESM). In this work, the AEP losses caused by LEE or by operating in the ESM are compared for two reference turbines, i.e. the IEA 15MW and the NREL 5MW turbines. For both turbines, the performance is evaluated in uniform and sheared inflow conditions. The effects of erosion are modeled by creating clean and rough airfoil polars in XFOIL. It is assumed that erosion occurs once a critical blade element section speed is exceeded. Power curves for LEE and ESM are calculated by using the free-wake vortex method CACTUS. Results show that LEE negatively affects the power production below rated capacity, while operating in ESM predominantly sheds performance at rated power of the turbine. This study, therefore, shows that a break-even point for the ESM exists. The AEP loss due to erosion can be successfully mitigated with the ESM at sites with low mean wind speed, however, at sites with higher mean wind speed, operation with erosion leads to a lower AEP loss. The break-even point shows little sensitivity to the blade design and to mean shear variations, but strongly depends on the frequency ESM needs to be applied. The latter is driven by the predicted amount of damaging rain events. In conclusion, erosion-optimal operation is strongly governed by the site characteristics and much less by turbine design, and the viability of an ESM strategy can be significantly expanded by a better understanding of blade damage mechanisms and improved forecasting of the related weather events.

Towards standards in the analysis of wind turbines operating in cold climate. Part B: Methodology for evaluating wind turbine alternative operational strategies

Alternative operational strategies are now being used to cope with the challenges of icing on wind turbines. However, there are currently no generally accepted standards for the performance analysis of wind turbines using such alternative operational strategies. Hence, this is an important research topic that needs to be addressed. The aforementioned alternative operational strategies include ice protection systems (installation or modification) and alternative turbine control strategies. The interest surrounding the performance analysis of such strategies is rising since, as the demand for ice protection systems from wind turbine original equipment manufacturer and retrofits providers is increasing worldwide, operators are requesting warranties surrounding their performance. Due to their novelty, operators often prefer to test alternative operational strategies on a few turbines before deploying them on every turbines of a wind farm. In those situations, a standard and robust method is needed to evaluate the strategy before a full-scale extension. This paper proposes a methodology based on the experience gathered on five undisclosed wind farms where different operational strategies were implanted. Through case studies, the current metrics used to assess the performance of alternative operational strategies are reviewed and two new metrics that address the main issues with the current indicators are proposed. These new metrics can estimate the energy reclaimed through the use of alternative operational strategies. This paper also presents a methodology for selecting the best turbines that will be used as a reference to evaluate the performance of the turbines with the alternative operational strategies. Standardized metrics with the right turbines used as a reference will help to provide a clearer overview of the performance of wind turbines in icing conditions. Furthermore, it will help to reduce the uncertainties on the gains achieved through alternative operational strategies. The proposed methodology can be used by operators to compute the payback and quantify the added value of such modifications on their wind farm. It also helps to understand when a strategy is efficient, therefore helping to improve the development of new alternative operational strategies. Finally, using this methodology, through a case study, we demonstrated that the three control turbines could have recovered between 54 and 56% of their icing losses if they were equipped with a Borealis Wind Ice Protection System (IPS).

Design and Development of Wind Turbine Performance Analysis System Modeling

Wind turbines have been subjected to alternating loads for a long time, and the working environment is harsh, and their performance gradually deteriorates over time. Therefore, it is very necessary to understand the operating status of each component of the wind turbine unit through detailed evaluation of its performance through the monitoring data of the wind turbine unit.This paper designs and develops a wind turbine performance analysis software system based on the related business processes and functional requirements of wind farms. The system can calculate all the indicators related to wind farm and generating capacity, lost electricity and performance of wind farm, helping operators and analysts to achieve more comprehensive, in-depth and professional performance analysis of wind farm, so as to achieve the purpose of intelligent operation and maintenance of enterprises.

Wind turbine power curve modeling using radial basis function neural networks and tabu search

Wind turbine power curve (WTPC) modeling is of great importance for performance monitoring. This work proposes a new method for producing highly accurate non-parametric models for wind turbines based on artificial neural networks (ANNs). To achieve this, we employ networks belonging to the radial basis function (RBF) architecture, and feed them with additional important input variables besides wind speed. To further increase modeling accuracy, while at the same time keeping the computational cost at acceptable levels, we introduce a new training algorithm based on the successful non-symmetric fuzzy means (NSFM) approach, which in this work is hybridized with the tabu search (TS) metaheuristic technique, enabling the method to train efficiently datasets of high dimensionality. The resulting method is evaluated on real data from four wind turbines, whereas a comparison with numerous WTPC modeling schemes, including parametric and non-parametric models is conducted. The solution found by the proposed algorithm outperforms the results produced by its rivals in terms of both modeling accuracy and efficiency, while in most cases it also leads to simpler models. The resulting models can be used successfully, not only for accurate WTPC modeling, but also for constructing wind turbine performance analysis tools, e.g. 3-D power curves.

Wind turbine performance analysis for energy cost minimization

The use of wind energy worldwide has overgrown in recent years to reduce greenhouse gas emissions. Wind power is free, but the installation and maintenance of wind turbines remain very costly. The size of the installation of the wind turbine is not only determined by wind statistics at a given location, but also by turbine infrastructure and maintenance costs. The payback time of the turbine is dependent on turbine energy costs. This study estimates the wind power generation capacity of Northern and Southern Oman and discusses the selection of the most economical, efficient and reliable wind turbines in Oman. HOMER Pro Software was used in this paper to evaluate the wind energy data in the north and south of Oman and to provide well-informed guidance on the most suitable turbines for the power needs of each area. Six different standard wind turbines were measured and compared in terms of the cost of energy and performance. The simulation analysis reveals that the DW54 turbine is the best possible turbine to generate electricity in northern Oman at $0.119/kW. Due to the difference in the wind regime between the north and the south of Oman, the simulation showed that the Hummer H25.0–200 kW turbine is the best option for south Oman with power generation at $0.070/kW. The northern wind turbine plant can efficiently contribute to decarbonization of the energy sector in Oman, with a potential reduction of CO2 emission approximately 19,000 tons/year in comparison to natural gas and 28,000 tons/year in comparison to diesel. In the Southern Power Plant, carbon emissions are reduced by 18,000 and 12,000 tons/year compared to diesel and natural gas.

Aeroelastic Performance Analysis of Wind Turbine in the Wake with a New Elastic Actuator Line Model

The scale of a wind turbine is getting larger with the development of wind energy recently. Therefore, the effect of the wind turbine blades deformation on its performances and lifespan has become obvious. In order to solve this research rapidly, a new elastic actuator line model (EALM) is proposed in this study, which is based on turbinesFoam in OpenFOAM (Open Source Field Operation and Manipulation, a free, open source computational fluid dynamics (CFD) software package released by the OpenFOAM Foundation, which was incorporated as a company limited by guarantee in England and Wales). The model combines the actuator line model (ALM) and a beam solver, which is used in the wind turbine blade design. The aeroelastic performances of the NREL (National Renewable Energy Laboratory) 5 MW wind turbine like power, thrust, and blade tip displacement are investigated. These results are compared with some research to prove the new model. Additionally, the influence caused by blade deflections on the aerodynamic performance is discussed. It is demonstrated that the tower shadow effect becomes more obvious and causes the power and thrust to get a bit lower and unsteady. Finally, this variety is analyzed in the wake of upstream wind turbine and it is found that the influence on the performance and wake flow field of downstream wind turbine becomes more serious.

Performance Analysis of Wind Turbine Monitoring Mechanism Using Integrated Classification and Optimization Techniques

The advanced improvements in the techniques utilized in the field of energy generation using the wind mills has led to the remarkable minimization in its capital investments and the cost incurred in its operation. This has even enhanced the prominence of the winds farms worldwide and has raised the market share of the energy produced using the wind mills. Thus leading to the increase in the necessity for capable monitoring mechanisms that is cost effective to report the conditions of the wind turbines regularly. So that it would be helpful in early diagnosis of any fault that has occurred in the wind turbines. To have an accurate monitoring and minimized maintenance cost the paper integrates the Support Vector machine based Cuckoo Search Algorithm. The incorporation of the SVM with the CSO is validated in MATLAB under the gain-factor and the fixed value types of faults that are liable to occur in the wind turbines and the results acquired are compared with the other existing methods such as the SVM-PSO and K-NN. The results observed shows that the SVM based CSO is more accurate in predicting the fault models than the other existing models.

Performance analysis of wind turbines at low tip-speed ratio using the Betz-Goldstein model

Analyzing wind turbine performance at low tip-speed ratio is challenging due to the relatively high level of swirl in the wake. This work presents a new approach to wind turbine analysis including swirl for any tip-speed ratio. The methodology uses the induced velocity field from vortex theory in the general momentum theory, in the form of the turbine thrust and torque equations. Using the constant bound circulation model of Joukowsky, the swirl velocity becomes infinite on the wake centreline even at high tip-speed ratio. Rankine, Vatistas and Delery vortices were used to regularize the Joukowsky model near the centreline. The new formulation prevents the power coefficient from exceeding the Betz-Joukowsky limit. An alternative calculation, based on the varying circulation for Betz-Goldstein optimized rotors is shown to have the best general behavior. Prandtl’s approximation for the tip loss and a recent alternative were employed to account for the effects of a finite number of blades. The Betz-Goldstein model appears to be the only one resistant to vortex breakdown immediately behind the rotor for an infinite number of blades. Furthermore, the dependence of the induced velocity on radius in the Betz-Goldstein model allows the power coefficient to remain below Betz-Joukowsky limit which does not occur for the Joukowsky model at low tip-speed ratio.

Wind turbine performance analysis based on multivariate higher order moments and Bayesian classifiers

A data-driven model based on Bayesian classifiers and multivariate analysis of the power curve (wind speed vs. power) for monitoring wind farms' performance is presented. A new outlier detection criterion and various control bounds on the skewness and kurtosis of the data for cluster separation and classification of turbines' faulty and normal state of operation are introduced. Further continuous monitoring is addressed with Hotelling's T2 and Bayesian network approaches, and it is proven that under certain conditions, the outcomes of these two methods are equivalent. The Bayesian approach, however addresses the likelihood of classification, making supervised controls more flexible.

Performance Analysis of Wind Turbine as a Distributed Generation Unit In Distribution System

In this paper, the performance analysis of wind turbine as a distributed generation unit is presented. In this study a model of wind power is driven by an induction machine. Wind power that is distributed generation is capable of supplying power to ac power distribution network. Wind power generation system is modeled and simulated using Matlab Simulink software such that it can be suitable for modeling some kind of induction generator configurations. To analyze more deeply the performance of the wind turbine system, both normal and fault conditions scenarios have been applied. Simulation results prove the excellent performance of the wind power unit under normal and fault conditions in the power distribution system.

On-line monitoring of power curves

A data-driven approach to the performance analysis of wind turbines is presented. Turbine performance is captured with a power curve. The power curves are constructed using historical wind turbine data. Three power curve models are developed, one by the least squares method and the other by the maximum likelihood estimation method. The models are solved by an evolutionary strategy algorithm. The power curve model constructed by the least squares method outperforms the one built by the maximum likelihood approach. The third model is non-parametric and is built with the k-nearest neighbor ( k-NN) algorithm. The least squares (parametric) model and the non-parametric model are used for on-line monitoring of the power curve and their performance is analyzed.

Modelling Approaches for Flow over a Wind Turbine Blade

This work models the aerodynamic performance of a wind turbine blade using computational fluid dynamics and strip theory. The wind turbine blade design was supplied by Twin Turbines Ltd. It is a constant tip-speed ratio design, using stall regulation for power control in winds above the rated speed. The analysis uses the commercial computational fluid dynamics program CFX-5. The software model of the wind turbine blade includes rotation simulated using a rotating domain. The results from this model are compared to the solutions obtained using the strip theory method for wind turbine performance analysis. Finally, the stall regulation of the blade at high wind speeds is investigated, using both CFX and the strip theory model. The results from the two methods show good agreement with each other, and indicate that the regulation effect is likely to be smaller than had been expected by the intended manufacturer, Twin Turbines Ltd.