Turbine Performance Data Research Articles

Wind Speed Modeling under Quasi‐Linear Autoregressive Neural Network Model for Prediction of Production Power

Accurate wind speed modeling is beneficial for the design of wind energy conversion systems. Models of wind speed are used to assess the adequacy and dependability of a power supply. However, precise wind speed modeling is challenging due to the sporadic availability of wind speed. In this note, we propose a wind speed model with an autoregressive (AR) structure. A hybrid model is developed under linear and nonlinear parts based on a quasi‐linear autoregressive exogenous neural network (Q‐ARX‐NN). The model's structure is composed of a regression vector and its coefficients. The coefficients are divided into linear and nonlinear coefficients. A set of linear coefficients is identified under the algorithm of least square error (LSE), and a set of nonlinear coefficients is modeled by using a neural network to refine the residual error of the nonlinear part. Some artificial neural network (ANN) models can be set as nonlinear part sub‐models to sharpen the model's accuracy. The proposed model is tested for wind speed modeling to estimate wind energy production. Various nonlinear parts of the sub‐model are tested, such as neural networks, radial basis function networks, and ANN networks. Moreover, we evaluate the effects of the order of the model by varying hidden and output nodes, which can be summarized as the number of coefficients of the regression vector. Using specific wind turbine performance data, prediction models estimate production power. © 2024 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Model Design of Helical Type Vertical Shaft Wind Turbine with Capacity of 5 W

A vertical axis wind turbine (VAWT) is a power generator that uses wind power to generate torque. The VAWT can be pointed in any direction, meaning it doesn't need to be pointed into the wind to generate power. Thus, there is potential for large power plants using VAWTs as their size can be significantly increased. However, there are also some drawbacks to the VAWT. VAWT has the characteristics of self-starting. But still, an additional power source is needed to start the turbine rotation until a certain rotation speed is reached or it must operate at high wind speeds. The main objective of our work is to create a 5 W VAWT model (helical type) to optimize self-starting of vertical axis wind turbines. The outline of this report is regarding the design of our VAWT model, which will have self-starting characteristics. To increase the self-starting status, our efforts are to optimize the type, dimensions and material of the turbine blades. We also optimized the rotor dimensions. As a result, a model helical three-blade turbine was built and tested. The blade turbine made of composites has been balanced with the rotor prior to testing. The test uses 2 fans with a speed of 3-5m/s, the test is carried out to obtain wind turbine performance data.

Processing of offshore measurement data for multi-fidelity wake model performance assessments

Numerical wake models used for offshore wind farm developments are regularly evaluated through comparisons with field measurements of atmospheric conditions and turbine performance data. However, measurement data from offshore sites can be plagued by a variety of issues that are often neglected from data processing procedures and can strongly impact the reliability of the metrics used for model evaluation. While some of these issues have been addressed through assumptions, a variety of shortcomings are frequently overlooked. In this work, the issues found with measurement data used to compile an evaluation dataset to be applied for numerical wake model assessments are presented. The dataset contains long-term operational data from two neighboring offshore wind farms in the German Bight and meteorological data from a met mast located in between the wind farms. The methodologies used to overcome these issues with minimal impact on the reliability of the evaluation dataset for modelling are presented and discussed. Furthermore, the repercussions of overlooking such shortcomings are highlighted and future challenges posed by the planned expansions of offshore wind energy capacity are addressed.

A new base of wind turbine noise measurement data and its application for a systematic validation of sound propagation models

Abstract. Extensive measurements in the area of wind turbines were performed in order to validate a sound propagation model which is based on the Crank–Nicolson parabolic equation method. The measurements were carried out over a flat grass-covered landscape and under various environmental conditions. During the measurements, meteorological and wind turbine performance data were acquired and acoustical data sets were recorded at distances of 178, 535 and 845 m from the wind turbine. By processing and analysing the measurement data, validation cases and input parameters for the sound propagation model were derived. The validation includes five groups that are characterised by different sound propagation directions, i.e. downwind, crosswind and upwind conditions in varying strength. In strong upwind situations, the sound pressure levels at larger distances are overestimated because turbulence is not considered in the modelling. In the other directions, the model reproduces the measured sound propagation losses well in the overall sound pressure level and in the third octave band spectra. As in the recorded measurements, frequency-dependent maxima and minima are identified, and losses generally increase with increasing distance and frequency. The agreement between measured and modelled sound propagation losses decreases with distance. The data sets used in the validation are freely accessible for further research.

Self-reconfiguration simulations of turbines to reduce uneven farm degradation

This study explored the concept of a floating offshore wind farm (FOWF) that self-reconfigures wind turbine (WT) positions. The self-reconfiguration (SR) mechanism moves degraded turbines to different farm positions to delay failures occurring and reduce power loss. A 40-turbine agent-based simulation was created utilising wind and turbine performance data. For the first time, the SR mechanism was designed and optimised with principles of self-engineering complexity. The paper demonstrates the effectiveness of the SR mechanism through an agent-based simulation approach. The optimised SR was used in FOWF simulations of 50 years of operation; SR balanced fatigue across the FOWF and led to an increased income of £5–40M at years 27–33 of operation; however, outside of these years, there is no net positive income, and by year 50 SR has cost the FOWF £4–7M more in movement costs. Lastly, simulations with repair and maintenance restricted to 10 months or less were conducted. SR delayed turbine failures, so they occurred in months when repair could be conducted. The SR reduced power loss and increased net income by up to £20M, indicating that SR could be useful when repair and maintenance times are limited. In the absence of significant operational data, a qualitative validation with experts confirmed the approach and the validity of the simulation model for a range of FOWF scenarios.

EXPERIMENTAL STUDY OF CIRCULAR CUT OFF ENDPLATE EFFECT ON THE SAVONIUS TURBINE

The Savonius turbine is widely used because it has a simple design. However, the Savonius turbine has a lower efficiency than the Horizontal Axis Wind Turbine (HAWT). Several studies have been conducted to increase the efficiency of the Savonius turbine. Turbine performance can be improved by reducing the negative vortex by creating a flushing effect. This experiment was conducted to determine the impact of circular cut-off end plates on the Savonius turbine. The research results are shown through turbine performance data on wind turbine angular speed, electric power, static torque, and efficiency. The wind turbines with circular cut-off endplates had higher angular velocities than conventional Savonius turbines. The angular velocity measurement is carried out when the turbine is unloading. Meanwhile, the electric power and static torque of a conventional turbine are more significant than a modified turbine. The measurement of electric power and static torque is carried out when the turbine is in a generator-loaded condition (loading).

Anomaly detection in wind turbine SCADA data for power curve cleaning

Wind turbine power curve cleaning, by way of removing curtailment, stoppage, and other anomalies, is an essential step in making raw data useable for further analysis, such as determining turbine performance, site characteristics, or improving forecasting models. Typically, data comes as SCADA (Supervisory Control and Data Acquisition) data, so contains not only environmental and turbine performance data but also the control action imposed on the turbine by the operator. Many different anomaly detection (AD) methods have been proposed to clean power curves; however, few papers have explored filtering explicit and obvious anomalies from the SCADA prior to running AD. This paper actively explores this filtering impact by comparing the performances of 4 different AD methods with/without filtering. These are: iForest, Local Outlier Factor, Gaussian Mixture Models, and k-Nearest Neighbours. Each approach is evaluated in terms of prediction error, data removal rates, and ability to maintain the underlying wind statistical characteristics. The results show the effectiveness of filtering with every technique showing improvement compared to its unfiltered counterpart. Furthermore, Gaussian Mixture Models are shown to provide favourable accuracy whilst maintaining wind variability, however, with the wide range of performances of methods, a user's choice may be different depending on their needs.

Evaluation of an offshore wind farm computational fluid dynamics model against operational site data

Modelling wind turbine wake effects at a range of wind speeds and directions with actuator disk (AD) models can provide insight but also be challenging. With any model it is important to quantify the level of error, but this can also present a challenge when comparing a steady-state model to measurement data with scatter. This paper models wind flow in a wind farm at a range of wind speeds and directions using an AD implementation. The results from these models are compared to data collected from the actual farm being modelled. An extensive comparison is conducted, constituted from 35 cases where two turbulence models, the standard k-ε and k-ω SST are evaluated. The steps taken in building the models as well as processes for comparing the AD computational fluid dynamics (CFD) results to real-world data using the regression models of ensemble bagging and Gaussian process are outlined. Turbine performance data and boundary conditions are determined using the site data. Modifications to an existing opensource AD code are shown so that the predetermined turbine performance can be implemented into the CFD model. Steady state solutions are obtained with the OpenFOAM CFD solver. Results are compared in terms of velocity deficit at the measurement locations. Using the standard k-ε model, a mean absolute error for all cases together of roughly 8% can be achieved, but this error changes for different directions and methods of evaluating it.

Assessment and Performance Evaluation of a Wind Turbine Power Output

Estimation errors have constantly been a technology bother for wind power management, often time with deviations of actual power curve (APC) from the turbine power curve (TPC). Power output dispersion for an operational 800 kW turbine was analyzed using three averaging tine steps of 1-min, 5-min, and 15-min. The error between the APC and TPC in kWh was about 25% on average, irrespective of the time of the day, although higher magnitudes of error were observed during low wind speeds and poor wind conditions. The 15-min averaged time series proved more suitable for grid management and energy load scheduling, but the error margin was still a major concern. An effective power curve (EPC) based on the polynomial parametric wind turbine power curve modeling technique was calibrated using turbine and site-specific performance data. The EPC reduced estimation error to about 3% in the aforementioned time series during very good wind conditions. By integrating statistical wind speed forecasting methods and site-specific EPCs, wind power forecasting and management can be significantly improved without compromising grid stability.

Solar Gas Turbine Systems with Centrifugal Particle Receivers, for Remote Power Generation

There is a growing demand from remote communities in Australia to increase the amount of decentralised renewable energy in their energy supply mix in order to decrease their fuel costs. In contrast to large scale concentrated solar power (CSP) plants, small solar-hybrid gasturbine systems promise a way to decentralise electricity generation at power levels in the range of 0.1-10MWe, and reduce to cost of energy production for off-grid, isolated communities. Thermal storage provides such CSP systems with an advantage over photovoltaic (PV) technology as this would be potentially cheaper than adding batteries to PV systems or providing stand-by back-up systems such as diesel fuelled generators. Hybrid operation withconventional fuels and solar thermal collection and storage ensures the availability of power even if short term solar radiation is not sufficient or the thermal storage is empty. This paper presents initial modellingresults of a centrifugal receiver (CentRec)system, using hourly weather data of regional Australia for a 100 kWemicroturbine as well as a more efficient and cost effective 4.6MWe unit. The simulations involve calculation and optimisation of the heliostat field, by calculating heliostat by heliostat annual performance. This is combinedwith a model of the receiver efficiency based on experimental figures and a model of the particle storage system and turbine performance data. The optimized design for 15 hours of thermal storage capacity results in a tower height of 35m and a solar field size of 2100m2 for the 100 kWe turbine, and a tower height of 115m and solar field size of 50 000m2 for the 4.6MWe turbine. The solar field provides a greater portion of the operational energy requirement for the 100kWe turbine, as the TIT of the 4.6MWe turbine (1150°C) is greater than what the solar system can provide. System evaluations of the two particle receiver systems, with a selection of cost assumptions, are then compared to the current conventional means of supplying energy in such remote locations.

Innovative Wind Turbine Selection Method using Modified Weibull Probability Function

In this work, a three-year wind data for some sites in Jordan was analyzed. Two sites showed highly promising potential. Both predicted more than 1.0 MWh/m2.y. This work modified the probability function of Weibull – Hiester and Pennel to produce more accurate potential speed values for the wind. Results showed that this modification enhanced energy potential by 30%. The interaction of wind turbine performance data with site wind data was then discussed. The yearly output energy of different machines was the objective function for an optimization process with rating velocity (Vr) as the main variable. The resulted optimum energy was found to depend on the two variables of the Wiebull function. Optimum Vr was found to range from 4.2 to 5.6 for the sites considered. The optimum Vr can be used as a selection parameter for the best suitable turbine.

1003 車両過給機用タービンの広作動域性能計測に関する研究

In an automotive turbocharger development, a wide range turbine performance data is required for a precise of an engine matching with a turbocharger. In order to obtain a wide range turbine performance accurately, a wide range operation procedure was introduced in this study by controlling a compressor power which is installed coaxially with a turbine. A variable inlet guide vane which was set on a compressor and could adjust a compressor Euler head and also varying a compressor inlet pressure could adjust a compressor mass flow rate. Applying these procedures, it was confirmed experimentally that a turbine operating range was enhanced more than twice of an ordinal procedure.

Investigation of Self-Starting Capability of Vertical Axis Wind Turbines Using a Computational Fluid Dynamics Approach

Vertical axis wind turbines have always been a controversial technology; claims regarding their benefits and drawbacks have been debated since the initial patent in 1931. Despite this contention, very little systematic vertical axis wind turbine research has been accomplished. Experimental assessments remain prohibitively expensive, while analytical analyses are limited by the complexity of the system. Numerical methods can address both concerns, but inadequate computing power hampered this field. Instead, approximating models were developed which provided some basis for study; but all these exhibited high error margins when compared with actual turbine performance data and were only useful in some operating regimes. Modern computers are capable of more accurate computational fluid dynamics analysis, but most research has focused on horizontal axis configurations or modeling of single blades rather than full geometries. In order to address this research gap, a systematic review of vertical axis wind-power turbine (VAWT) was undertaken, starting with establishment of a methodology for vertical axis wind turbine simulation that is presented in this paper. Replicating the experimental prototype, both 2D and 3D models of a three-bladed vertical axis wind turbine were generated. Full transient computational fluid dynamics (CFD) simulations using mesh deformation capability available in ansys-CFX were run from turbine start-up to operating speed and compared with the experimental data in order to validate the technique. A circular inner domain, containing the blades and the rotor, was allowed to undergo mesh deformation with a rotational velocity that varied with torque generated by the incoming wind. Results have demonstrated that a transient CFD simulation using a two-dimensional computational model can accurately predict vertical axis wind turbine operating speed within 12% error, with the caveat that intermediate turbine performance is not accurately captured.

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Productivity of Ocean-Wave-Energy Converters: Turbine Design

A study was undertaken to identify which of a range of advanced Wells turbine configurations would maximize wave power productivity. The productivity is estimated of a monoplane with fixed guide vanes, a monoplane with variable-pitch blades, and a high- and low-solidity biplane with counterrotating rotors. Two control mechanisms are investigated for the variable pitch configuration. Raleigh distributions based on a mean annual pneumatic power rating of 500 kW are utilized to generate the short and long-term variations of input power to be matched with experimental turbine performance data obtained from a steady-state test rig. It was found that productivity was relatively insensitive to turbine configuration but that a low-solidity counterrotating turbine had the best performance characteristic providing high peak efficiency and gradual onset of stall.

A study on performance estimations for hot water turbines. Turbine performance.

A Series of tests, including nozzle single tests, blade single tests and single-stage turbine tests, are conducted to study the practical applications of hot water turbines. Hot water turbines are considered to be very useful for waste heat recovery plants and geothermal power plants. In this report, single-stage hot water turbine performance data are presented. A hot water turbine performance estimation method covering both nozzle and blade performance is introduced, and this calculation is shown to accord well with the turbine performance test results. Further, it is confirmed both theoretically and experimentally that a high nozzle inlet pressure and assist steam improve turbine performance.

Corrections for the Performance of Gas Turbines under Varying Atmospheric Conditions

Internal combustion engines are affected in their performance by varying atmospheric conditions, namely the atmospheric temperature, pressure and humidity. For gas turbines, however, performance correction formulae are not available as they are for gasoline engines. The purpose of this paper is to analyze the effects of atmospheric conditions on the performance of gas turbines, and to develop a theoretical correction formula by which gas turbine performance can be corrected from arbitrary atmospheric conditions to standard atmospheric conditions. In this paper, first, as a standard for comparision, the author shows the performance characteristics of three types of gas turbines under standard conditions at standard atmospheric temperature, pressure and humidity. Then he considers the performance of gas turbines under varying atmospheric conditions and, from the thermodynamic point of view, analyzes the effects of various atmospheric factors. Finally, the theoretical values obtained are compared with practical gas turbine performance data.

CFD Analysis on Pumps Working as Turbines

Reverse running centrifugal pumps are an effective source of reducing the equipment cost in small hydropower plants. The manufacturers do not provide any information on the performance and fow characteristics when pumps are operated in turbine mode. Lack of Pump as Turbine (PAT) performance data is a signifcant barrier to the wider use of PAT. Application of Computational Fluid Dynamics (CFD) is a recent attempt for predicting the performance of PAT. CFD analysis is an effective design tool for predicting the performance of reverse running operation of centrifugal pumps. But some deviationsstill exist in experimental and CFD results of reverse operation of pumps. Future works in the feld of computational analysis can further improve the prediction of pumps in reverse operation. Key words: Pump as Turbine (PAT); Computational Fluid Dynamics (CFD); PumpDOI: 10.3126/hn.v6i0.4191 Hydro Nepal Vol 6, January 2010 Page : 35-37 Uploaded Date:24 January, 2011