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1
Năstase, Eugen-Vlad. "Studies on the Design Models of Horizontal Axis Wind Turbines." Bulletin of the Polytechnic Institute of Iași. Machine constructions Section 67, no. 1 (March 1, 2021): 9–18. http://dx.doi.org/10.2478/bipcm-2021-0001.
Повний текст джерелаАнотація:
Abstract The aim of the paper is to present through a contrastive analysis the main models used in the analysis and design of horizontal axis wind turbines. The basis for designing a rotor for a wind turbine, which is the main element of a turbine that extracts energy from the wind, is the propeller theory. This theory incorporates mathematical models that describe the movement of fluid around the propeller. The paper presents three generically named models, model A, model B and model C respectively, used in the analysis and design of the horizontal axis wind turbine’s rotor.
2
Hyman, Mario, and Mohd Hasan Ali. "A Novel Model for Wind Turbines on Trains." Energies 15, no. 20 (October 15, 2022): 7629. http://dx.doi.org/10.3390/en15207629.
Повний текст джерелаАнотація:
Wind turbines that are consistently exposed to the air displaced by moving trains have a high potential for energy generation. Researchers have developed mathematical models to simulate wind energy generation from turbines on moving trains but there are significant gaps in the developed model theory. Most models do not consider the negative effects that additional aerodynamic drag, increased weight, and modified dimensions can have on the train’s operation. To overcome the drawbacks of existing models, this work proposes a novel approach of modeling the wind turbines on trains by considering wind turbine exposure only when the train is decelerating or stationary. There are no models that consider all of these realistic physical effects as a function of time. Real-time analysis and power-system simulations showed that the proposed model could produce over 3 MJ of net energy for favorable train trips. The simulated load profile met the demand of a 1 KW generator connected to onboard electrical components. Some recommendations on possible future research on wind turbines on trains are explained.
3
Omar, Othman A. M., Hamdy M. Ahmed, and Reda A. Elbarkouky. "Commercial wind turbines modeling using single and composite cumulative probability density functions." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 1 (February 1, 2021): 47. http://dx.doi.org/10.11591/ijece.v11i1.pp47-56.
Повний текст джерелаАнотація:
As wind turbines more widely used with newer manufactured types and larger electrical power scales, a brief mathematical modelling for these wind turbines operating power curves is needed for optimal site matching selections. In this paper, 24 commercial wind turbines with different ratings and different manufactures are modelled using single cumulative probability density functions modelling equations. A new mean of a composite cumulative probability density function is used for better modelling accuracy. Invasive weed optimization algorithm is used to estimate different models designing parameters. The best cumulative density function model for each wind turbine is reached through comparing the RMSE of each model. Results showed that Weibull-Gamma composite is the best modelling technique for 37.5% of the reached results.
4
Merizalde, Yuri, Luis Hernández-Callejo, Oscar Duque-Perez, and Víctor Alonso-Gómez. "Maintenance Models Applied to Wind Turbines. A Comprehensive Overview." Energies 12, no. 2 (January 11, 2019): 225. http://dx.doi.org/10.3390/en12020225.
Повний текст джерелаАнотація:
Wind power generation has been the fastest-growing energy alternative in recent years, however, it still has to compete with cheaper fossil energy sources. This is one of the motivations to constantly improve the efficiency of wind turbines and develop new Operation and Maintenance (O&M) methodologies. The decisions regarding O&M are based on different types of models, which cover a wide range of scenarios and variables and share the same goal, which is to minimize the Cost of Energy (COE) and maximize the profitability of a wind farm (WF). In this context, this review aims to identify and classify, from a comprehensive perspective, the different types of models used at the strategic, tactical, and operational decision levels of wind turbine maintenance, emphasizing mathematical models (MatMs). The investigation allows the conclusion that even though the evolution of the models and methodologies is ongoing, decision making in all the areas of the wind industry is currently based on artificial intelligence and machine learning models.
5
Saenz-Aguirre, Aitor, Ekaitz Zulueta, Unai Fernandez-Gamiz, Daniel Teso-Fz-Betoño, and Javier Olarte. "Kharitonov Theorem Based Robust Stability Analysis of a Wind Turbine Pitch Control System." Mathematics 8, no. 6 (June 12, 2020): 964. http://dx.doi.org/10.3390/math8060964.
Повний текст джерелаАнотація:
Wind energy has recently become one of the most prominent technologies among electrical energy generation systems. As a result, wind-based renewable energy generation systems are incessantly growing, and wind turbines of different characteristics are being installed in many locations around the world. One drawback associated with different characteristics of the wind turbines is that controllers have to be designed individually for each of them. Additionally, stable performance of the wind turbines needs to be ensured in the whole range of their operating conditions. Nowadays, there are many causes for uncertainties in the actual performance of a horizontal axis wind turbine, such as variations in the characteristics of the wind turbine, fabrication tolerances of its elements or non-linearities related to different operating-points. Hence, in order to respond to these uncertainties and ensure the stability of the wind turbine, robust control and stability theories have been gaining importance during recent years. Nevertheless, the use of robust stability analyses with complex wind turbine models still needs to be faced and remarkably improved. In this paper, a stability analysis of the pitch system control of a horizontal axis wind turbine based on the Kharitonov robust stability method is proposed. The objective was to assess the robust stability of a pitch controller in response to uncertainties arising from varying operating conditions of the National Renewable Energies Laboratory (NREL) 5 MW class IIA wind turbine. According to the results, the proposed method could satisfactorily respond to limited variations in the characteristics of the model, but could lack accuracy in cases of bigger variations or employment of high order complex mathematical models.
6
Tian, Xiange, Yongjian Jiang, Chen Liang, Cong Liu, You Ying, Hua Wang, Dahai Zhang, and Peng Qian. "A Novel Condition Monitoring Method of Wind Turbines Based on GMDH Neural Network." Energies 15, no. 18 (September 14, 2022): 6717. http://dx.doi.org/10.3390/en15186717.
Повний текст джерелаАнотація:
The safety of power transmission systems in wind turbines is crucial to the wind turbine’s stable operation and has attracted a great deal of attention in condition monitoring of wind farms. Many different intelligent condition monitoring schemes have been developed to detect the occurrence of defects via supervisory control and data acquisition (SCADA) data, which is the most commonly applied condition monitoring system in wind turbines. Normally, artificial neural networks are applied to establish prediction models of the wind turbine condition monitoring. In this paper, an alternative and cost-effective methodology has been proposed, based on the group method of data handling (GMDH) neural network. GMDH is a kind of computer-based mathematical modelling and structural identification algorithm. GMDH neural networks can automatically organize neural network architecture by heuristic self-organization methods and determine structural parameters, such as the number of layers, the number of neurons in hidden layers, and useful input variables. Furthermore, GMDH neural network can avoid over-fitting problems, which is a ubiquitous problem in artificial neural networks. The effectiveness and performance of the proposed method are validated in the case studies.
7
Podhurenko, V., Yu Kutsan, and V. Terekhov. "Modelling of cost indicators for wind turbines of multimegawatt class in various sizes." IOP Conference Series: Earth and Environmental Science 915, no. 1 (November 1, 2021): 012021. http://dx.doi.org/10.1088/1755-1315/915/1/012021.
Повний текст джерелаАнотація:
Abstract The choice of wind turbines to fit various specific wind conditions for the purpose of ensuring maximum generation of electric power at least investment expenditures is among the wind power sector overarching challenges. Solving this task involves the evaluation of cost indices for wind turbines of various sizes. A well-known and rather popular with investigators model, made by the National Renewable Energy Laboratory (USA) has been improved for the first time with the aim of determining the cost of wind turbines of various sizes on the basis of their main parameters (rated power, rotor diameter, hub height) for current conditions of application. The established correlation relationships between the cost of wind turbine and its main parameters made possible the transformation of a well-known complex model into a model with linear equations and minimization of computations. Based on the research studies of the evolution of wind turbines main parameters and an average (global) cost of 1 MW of their power, the authors have suggested the first-ever original linear mathematical models that enable evaluating the wind turbine cost for any year of research. In illustration of application of the first ever developed technique, we have made the assessment of operating efficiency of the US wind farms from 2010 to 2019. The results obtained convincingly indicate the high quality of the developed model.
8
Wisatesajja, Wongsakorn, Wirachai Roynarin, and Decha Intholo. "Comparing the Effect of Rotor Tilt Angle on Performance of Floating Offshore and Fixed Tower Wind Turbines." Journal of Sustainable Development 12, no. 5 (September 29, 2019): 84. http://dx.doi.org/10.5539/jsd.v12n5p84.
Повний текст джерелаАнотація:
The development of Floating Offshore Wind Turbines (FOWTs) aims to improve the potential performance of the wind turbine. However, a problem arises due to the angle of tilt from the wind flow and the floating platform, which leads to a vertical misalignment of the turbine axis, thereby reducing the available blade area and lowering the capacity to capture energy. To address this problem, this paper seeks to compare the influence of the rotor tilt angle on wind turbine performance between fixed tower wind turbines and FOWTs. The models used in the experiments have R1235 airfoil blades of diameter 84 cm. The experiment was analyzed using a wind tunnel and mathematical modelling techniques. Measurements were obtained using an angle meter, anemometer and tachometer. Testing involved wind speeds ranging from 2 m/s to 5.5 m/s, and the rotational speeds of the two turbine designs were compared. The study found that the rotational speeds of the FOWTs were lower than those of the fixed tower turbines. Moreover, at tilt angles from 3.5° – 6.1° there was a loss in performance which varied between 22% and 32% at different wind speeds. The tilt angle had a significant effect upon FOWTs due to the angle of attack was continuously changing, thus altering the optimal position of the turbine blades. This changing angle of attack caused the effective area of the rotor blade to change, leading to a reduction in power output at suboptimal angles. The study finally makes recommendations for future studies.
9
Al-Quraan, Ayman, and Bashar Al-Mhairat. "Intelligent Optimized Wind Turbine Cost Analysis for Different Wind Sites in Jordan." Sustainability 14, no. 5 (March 6, 2022): 3075. http://dx.doi.org/10.3390/su14053075.
Повний текст джерелаАнотація:
Choosing the right wind site and estimating the extracted energy of the wind turbines are essential to successfully establishing a wind farm in a specific wind site. In this paper, a method for estimating the extracted energy of the wind farms using several mathematical models is proposed. The estimating method, which was based on five wind turbines, Q1, Q2, Q3, Q4, and Q5 and three wind distribution models, gamma, Weibull, and Rayleigh, was used to suggest suitable specifications of a wind turbine for a specific wind site and maximize the extracted energy of the proposed wind farm. An optimization problem, developed for this purpose, was solved using the whale optimization algorithm (WOA). The suggested method was tested using several potential wind sites in Jordan. The proposed wind farms at these sites achieved the maximum extracted energy, maximum capacity factor (CF), and minimum levelized cost of energy (LCoE) based on the solution of the developed optimization problem. The developed model with Q3 and the Rayleigh distribution function was validated with real measurement data from several wind farms in Jordan. Error analysis showed that the difference between the measured and estimated energy was less than 20%. The study validated the provided model, which can now be utilized routinely for the assessment of wind energy potential at a specific wind site.
10
Krysiński, Tomasz, Zbigniew Buliński, and Andrzej J. Nowak. "Numerical modeling and preliminary validation of drag-based vertical axis wind turbine." Archives of Thermodynamics 36, no. 1 (March 1, 2015): 19–38. http://dx.doi.org/10.1515/aoter-2015-0002.
Повний текст джерелаАнотація:
Abstract The main purpose of this article is to verify and validate the mathematical description of the airflow around a wind turbine with vertical axis of rotation, which could be considered as representative for this type of devices. Mathematical modeling of the airflow around wind turbines in particular those with the vertical axis is a problematic matter due to the complex nature of this highly swirled flow. Moreover, it is turbulent flow accompanied by a rotation of the rotor and the dynamic boundary layer separation. In such conditions, the key aspects of the mathematical model are accurate turbulence description, definition of circular motion as well as accompanying effects like centrifugal force or the Coriolis force and parameters of spatial and temporal discretization. The paper presents the impact of the different simulation parameters on the obtained results of the wind turbine simulation. Analysed models have been validated against experimental data published in the literature.
11
Chang, Se-Myong. "Mathematical Models of Environmental Problems on the Electromagnetic Interference for Wind Turbines." Journal of Environmental Science International 18, no. 8 (August 31, 2009): 911–18. http://dx.doi.org/10.5322/jes.2009.18.8.911.
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12
Long, Xiafei, Shengqing Li, Xiwen Wu, and Zhao Jin. "Wind Turbine Anomaly Identification Based on Improved Deep Belief Network with SCADA Data." Mathematical Problems in Engineering 2021 (November 30, 2021): 1–15. http://dx.doi.org/10.1155/2021/8810045.
Повний текст джерелаАнотація:
This article presents a novel fault diagnosis algorithm based on the whale optimization algorithm (WOA)-deep belief networks (DBN) for wind turbines (WTs) using the data collected from the supervisory control and data acquisition (SCADA) system. Through the domain knowledge and Pearson correlation, the input parameters of the prediction models are selected. Three different types of prediction models, namely, the wind turbine, the wind power gearbox, and the wind power generator, are used to predict the health condition of the WT equipment. In this article, the prediction accuracy of the models built with these SCADA sample data is discussed. In order to implement fault monitoring and abnormal state determination of the wind power equipment, the exponential weighted moving average (EWMA) threshold is used to monitor the trend of reconstruction errors. The proposed method is used for 2 MW wind turbines with doubly fed induction generators in a real-world wind farm, and experimental results show that the proposed method is effective in the fault diagnosis of wind turbines.
13
Wang, Lei, Tao Shen, and Chen Chen. "Multimodel Modeling and Predictive Control for Direct-Drive Wind Turbine with Permanent Magnet Synchronous Generator." Abstract and Applied Analysis 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/296436.
Повний текст джерелаАнотація:
The safety and reliability of the wind turbines wholly depend on the completeness and reliability of the control system which is an important problem for the validity of the wind energy conversion systems (WECSs). A method based on multimodel modeling and predictive control is proposed for the optimal operation of direct-drive wind turbine with permanent magnet synchronous generator in this paper. In this strategy, wind turbine with direct-drive permanent magnet synchronous generator is modeled and a backpropagation artificial neural network is designed to estimate the wind speed loaded into the turbine model in real time through the estimated turbine shaft speed and mechanical power. The nonlinear wind turbine system is presented by multiple linear models. The desired trajectory of the nonlinear system is decomposed to be suitable for the reference trajectory of multiple models that are presented by the linear models of the nonlinear system, which simplifies the nonlinear optimization problems and decreases the calculation difficulty. Then a multivariable control strategy based on model predictive control techniques for the control of variable-speed variable-pitch wind turbines is proposed. Finally, simulation results are given to illustrate the effectiveness of the proposed strategy, and the conclusion that multiple model predictive controller (MMPC) has better control performance than the PI control method is obtained.
14
Kovalnogov, Vladislav N., Yuriy A. Khakhalev, Ekaterina V. Tsvetova, and Larisa V. Khakhaleva. "MATHEMATICAL MODELING AND NUMERICAL STUDY OF ATMOSPHERIC BOUNDARY LAYER NEAR WINDFARMS." Автоматизация процессов управления 3, no. 65 (2021): 33–40. http://dx.doi.org/10.35752/1991-2927-2021-3-65-33-40.
Повний текст джерелаАнотація:
The article analyzes Russian and foreign sources relating to the interaction of wind turbines with the surface layers of the atmosphere. It specifies the main problems of mathematical modeling of the atmospheric boundary layer near the wind farms due to adverse meteorological conditions, in particular, constant zero crossings in the autumn-winter period, various precipitation, a wide time range, air parameters, terrain and other features. The authors analyze the evolution of mathematical models of turbulence to describe the boundary layer near wind turbines from earlier to rapidly developing and currently used. To achieve greater accuracy and naturalism, it is proposed to use high-performance efficient algorithms based on combining scales and physics of phenomena. The authors propose a mathematical model for studying the state of the atmospheric polydisperse boundary layer under conditions of the Ulyanovsk wind farm, taking into account the dispersed particles in the flow, surface curvature, pressure gradient and other influences.
15
Dehghan Manshadi, Mahsa, Milad Mousavi, M. Soltani, Amir Mosavi, and Levente Kovacs. "Deep Learning for Modeling an Offshore Hybrid Wind–Wave Energy System." Energies 15, no. 24 (December 14, 2022): 9484. http://dx.doi.org/10.3390/en15249484.
Повний текст джерелаАнотація:
The combination of an offshore wind turbine and a wave energy converter on an integrated platform is an economical solution for the electrical power demand in coastal countries. Due to the expensive installation cost, a prediction should be used to investigate whether the location is suitable for these sites. For this purpose, this research presents the feasibility of installing a combined hybrid site in the desired coastal location by predicting the net produced power due to the environmental parameters. For combining these two systems, an optimized array includes ten turbines and ten wave energy converters. The mathematical equations of the net force on the two introduced systems and the produced power of the wind turbines are proposed. The turbines’ maximum forces are 4 kN, and for the wave energy converters are 6 kN, respectively. Furthermore, the comparison is conducted in order to find the optimum system. The comparison shows that the most effective system of desired environmental condition is introduced. A number of machine learning and deep learning methods are used to predict key parameters after collecting the dataset. Moreover, a comparative analysis is conducted to find a suitable model. The models’ performance has been well studied through generating the confusion matrix and the receiver operating characteristic (ROC) curve of the hybrid site. The deep learning model outperformed other models, with an approximate accuracy of 0.96.
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Koronowicz, Tadeusz, and Jan A. Szantyr. "Comparative analysis of the theoretical models of ideal propulsor, ideal fluid brake, ideal screw propeller and ideal axial wind turbine." Polish Maritime Research 20, no. 2 (April 1, 2013): 3–12. http://dx.doi.org/10.2478/pomr-2013-0011.
Повний текст джерелаАнотація:
Abstract The article presents a detailed discussion of the theoretical models of four different fluid dynamic devices: an ideal propulsor, an ideal fluid brake, an ideal screw propeller and an ideal turbine. The four models are presented with all relevant mathematical formulae regarding the forces, the power and the efficiency. It is demonstrated that the application of the model of an ideal optimum fluid brake according to the Betz theorem for determination of the maximum effectiveness coefficient of an axial wind turbine is not correct. In the case of a turbine the inclusion of important rotational flow losses may increase the maximum value of the turbine effectiveness coefficient above the level defined by Betz. Therefore the model of an ideal turbine should be an inversion of the model of an ideal screw propeller. This conclusion is supported by numerical calculations. It may influence the design procedures of wind turbines and may lead to increase in their efficiency.
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Xie, Pu, Su Ning Zhang, Man Cao, and Rui Li. "Research on Designing and Modeling of the Hybrid Energy Power Supply System." Advanced Materials Research 805-806 (September 2013): 833–36. http://dx.doi.org/10.4028/www.scientific.net/amr.805-806.833.
Повний текст джерелаАнотація:
Based on traditional complementary power supply system, the actual wind-PV-diesel hybrid energy supply system comprising three energy sources, namely PV, wind and diesel generations based on dc bus is established. Each of the three energy sources is controlled so as to deliver energy at optimum efficiency. Then the designing and computing modeling of distributed sources such as wind turbines, photovoltaic array and battery is proposed. Models of wind turbines, photovoltaic array and characteristics of the battery, respectively established the mathematical model of them, and then the simulation model is respectively built by PSCAD/EMTDC. So a micro-network experiment and simulation platform is established, which can simulate any power of wind and solar power output characteristics.
18
Mazidi, Peyman, Mian Du, Lina Bertling Tjernberg, and Miguel A. Sanz Bobi. "A health condition model for wind turbine monitoring through neural networks and proportional hazard models." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 231, no. 5 (May 4, 2017): 481–94. http://dx.doi.org/10.1177/1748006x17707902.
Повний текст джерелаАнотація:
In this article, a parametric model for health condition monitoring of wind turbines is developed. The study is based on the assumption that a wind turbine’s health condition can be modeled through three features: rotor speed, gearbox temperature and generator winding temperature. At first, three neural network models are created to simulate normal behavior of each feature. Deviation signals are then defined and calculated as accumulated time-series of differences between neural network predictions and actual measurements. These cumulative signals carry health condition–related information. Next, through nonlinear regression technique, the signals are used to produce individual models for considered features, which mathematically have the form of proportional hazard models. Finally, they are combined to construct an overall parametric health condition model which partially represents health condition of the wind turbine. In addition, a dynamic threshold for the model is developed to facilitate and add more insight in performance monitoring aspect. The health condition monitoring of wind turbine model has capability of evaluating real-time and overall health condition of a wind turbine which can also be used with regard to maintenance in electricity generation in electric power systems. The model also has flexibility to overcome current challenges such as scalability and adaptability. The model is verified in illustrating changes in real-time and overall health condition with respect to considered anomalies by testing through actual and artificial data.
19
Borowski, Sylwester, Klaudiusz Migawa, Agnieszka Sołtysiak, Andrzej Neubauer, and Anna Mazurkiewicz. "Regression model in the operation of wind turbines." MATEC Web of Conferences 351 (2021): 01021. http://dx.doi.org/10.1051/matecconf/202135101021.
Повний текст джерелаАнотація:
The manuscript presents linear regression models used to predict the amount of energy produced in a wind turbine. As part of the own research, data obtained from the SCADA program for the Enercon E-82 wind turbine was analyzed. It has been shown that it is possible to build a mathematical model to determine the amount of energy generated from the average wind speed. This method can be used to forecast the production volume and balance the energy system. This is important due to the increasing share of renewable energy sources. The application of the developed method in practice will facilitate and accelerate the implementation of the decision-making process in electricity generation systems, while reducing the risk of error. This model can also be used to make wind turbine repowering decisions.
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Revana, Guruswamy, Amrutha D.E, Spandana D, and Anusha D. "SIMULATION BASED DESIGNING OF CONTROL SYSTEMS FOR WIND POWER GENERATION." International Journal of Engineering Technology and Management Sciences 4, no. 5 (September 28, 2020): 104–9. http://dx.doi.org/10.46647/ijetms.2020.v04i05.019.
Повний текст джерелаАнотація:
Wind power is a domestic source of energy, harnessing a limitless local resource and is a potential source of clean electricity generation. Wind is utilized to create electrical energy by means of the kinetic energy formed by air into movement. This energy is changed to electrical energy by wind speed turbines or also called as wind energy exchange systems. Wind speed power generation creates a progressively more significant position in the method the humans power the world. During the process of wind power generation, a variety of characteristics are to be controlled for efficient working of the system and to avoid failure of continuous power supply. In this project we are aiming to control a few such characteristic such as pitch angle, voltage sag and faults that influence wind power generation. The DC link voltage of the Doubly Fed Induction Generator (DFIG) is also monitored. In this wind turbine system consists of wind turbine, AC generator and controllers are considered. The major purpose of the paper is to find out the mathematical model of the wind turbine, authenticate it by simulation, and devise a suitable controller to present a common aim of outlook regarding the use of this type of clean energy production. Various rudiments are connected collectively and the complete arrangement is modelled and also simulated. The simulation results verify the accuracy of the mathematical models developed and can be utilized for a improved design of systems. Wind turbines make use DFIG which consists of wound rotor type induction generator and a PWM converter of IGBT bases of AC/DC/AC. The stator winding is connected directly to the 60 Hz grid while the rotor is fed at variable frequency through the AC/DC/AC converter. The DFIG machinery permits pulling out highest energy from the wind from lowest wind speeds and optimizing the speed of the turbine there by decreasing mechanical stresses on the turbine during gusts of wind. The most favourable turbine speed producing increased mechanical energy for a given speed of the wind which is directly proportional to the wind speed. The other merit of the DFIG expertise is the capability for the converters of power electronics to produce or take in reactive power, thereby reducing the need for putting in capacitor banks as done for the generators of squirrel-cage induction motor type.
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P. S, Divya, Lydia M, and Manoj G. "Minimization of the Cost of Energy of Wind Turbine through Various Power Models." International Journal of Applied Mathematics, Computational Science and Systems Engineering 4 (June 25, 2022): 14–20. http://dx.doi.org/10.37394/232026.2022.4.2.
Повний текст джерелаАнотація:
Wind energy is the world’s free form of energy, besides that it has expenses, because of the wind turbine construction and maintenance. The Cost of Energy (CoE) of the wind turbine is used to estimate the amount of time it takes to recover the cost of an investment by the wind farm owners. Hence optimization of the wind turbine CoE will make wind a very competent source of energy. In this article, the wind speed is modified using three alternative distributions in order to reduce the wind turbine CoE, and the turbine Annual Energy Production (AEP) is evaluated. Mathematical functions such as linear, quadratic and cubic have been used to model the wind power. This study enables us to figure out the minimum turbine CoE among the mathematical distributions, along with the optimum mathematical function for wind power modelling and to optimize the rotor radius of turbine.
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Korobskyy, V., and A. Proskura. "Analysis of the state of hybrid wind power plants and their simulation." Energy and automation, no. 6(58) (November 24, 2021): 58–74. http://dx.doi.org/10.31548/energiya2021.06.058.
Повний текст джерелаАнотація:
The analysis of the provision of wind power plants of low power power supply to different consumers, taking into account the installed capacity and remoteness, is carried out. The expediency of using some design solutions of wind power plants with a horizontal axis of rotation, which are included in the power limitation up to 20 kW, is considered. It was found that low-power hybrid wind turbines equipped with storage devices are the most suitable option for providing power supply to consumers, where there is no centralized power grid within a radius of 20 km. It is noted that the most preferable for use are synchronous alternators over asynchronous or direct current generators. Two technical solutions for the operation of wind turbines are considered, one of which combines the traditional use of the installation with the consumer; and in the other - the connection of the wind turbine with an electric consumer using solar panels, a storage battery and a voltage inverter. It is noted that both options have their own advantages and disadvantages in practice, as well as a feature of the electromechanical system of wind turbines is the unpredictable and uncontrollable input of primary energy of a stochastic air flow, which leads to fluctuations in the output parameters (voltage and current frequency). Therefore, in order to eliminate this drawback and ensure the supply of electricity to consumers, the electricity generated by the generator will be used to charge the storage battery. It is noted that the disadvantages of traditional wind turbines create a significant contradiction, consisting in the emergence of the need to increase their energy efficiency of operation by improving the traditional design, on the one hand, and the inability of existing wind turbines to provide such an increase, on the other hand. In this case, the most rational solution may be the use of a wind turbine design with solar panels, which will ensure the operation of the wind turbine in a windless period and efficient adjustment of electrical payloads with increasing wind speed using the accumulated energy to power the current collectors. When conducting research in the field of wind energy, it is often necessary to use different models. The mathematical model describes a real object only with a certain degree of approximation (detail). In this case, the type of model depends both on the nature of the object under study and on the research tasks, modeling techniques, and the required accuracy of object description. The study proposes a simulation model of a wind power plant in the Simulink software application to estimate the generated power. The dependences of the design power of the wind turbine on the wind speed at three different radii of the wind turbine are obtained. Key words: wind power plant, consumer, installed capacity, renewable energy sources, wind speed, simulation, wind turbine, storage battery, generator, voltage inverter
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P. S, Divya, Vijila Moses, Manoj G, and Lydia M. "Wind Turbine Energy Cost Optimisation Using Various Power Models." WSEAS TRANSACTIONS ON POWER SYSTEMS 17 (September 9, 2022): 261–68. http://dx.doi.org/10.37394/232016.2022.17.27.
Повний текст джерелаАнотація:
In modern times, the worldwide wind turbine installations have developed swiftly resulting in the decrease of green gas emissions. Though wind is a free gift of nature, it is expensive to harness this energy for useful applications like electricity generation. The cost of installation of the wind turbine at a particular station does not depend only on the wind resource, but also on the structure of the turbine and the energy conversion technology. The wind turbine Cost of Energy (CoE) is used to estimate the payback time for the return on the investment made by the wind farm owners for the turbine. Meticulous research is required to optimize the turbine CoE which will make wind a very competent source of energy. In this article, in order to minimize the wind turbine CoE, the wind speed is modelled using three different distributions namely, Dagum, Gamma and Weibull and the evaluation of the turbine Annual Energy Production (AEP) is carried out. Mathematical functions such as linear, quadratic and cubic have been used to model the wind power. For the cost analysis of the turbine, the price model which was established by United States, National Renewable Energy Laboratory (NREL) is employed. The comparative study of the proposed methodology have been done for six different stations. The turbine CoE model is an element of two factors, the rated power Pr of a turbine and the rated wind speed Vr of a turbine. Based on the results obtained, a broad recommendation to reduce the turbine CoE is presented. This study enables us to figure out the minimum turbine CoE among the three discussed mathematical distributions, the finest distribution for wind speed modelling and the optimum mathematical function for wind power modelling. The suitable size of the wind turbine also can be found by optimizing the rotor radius R of the turbine for each data.
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Nachimuthu, Sathishkumar, Ming J. Zuo, and Yi Ding. "A Decision-making Model for Corrective Maintenance of Offshore Wind Turbines Considering Uncertainties." Energies 12, no. 8 (April 12, 2019): 1408. http://dx.doi.org/10.3390/en12081408.
Повний текст джерелаАнотація:
Maintenance optimization has received special attention among the wind energy research community over the past two decades. This is mainly because of the high degree of uncertainties involved in the execution of operation and maintenance (O&M) activities throughout the lifecycle of wind farms. The increasing complexity in offshore maintenance execution demands applied research and brings forth a need to develop problem-specific maintenance decision-making models. In this paper, a mathematical model is proposed to assist wind farm stakeholders in making critical resource- related decisions for corrective maintenance at offshore wind farms (OWFs), considering uncertainties in turbine failure information.
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Sun, Zexian, and Hexu Sun. "Health Status Assessment for Wind Turbine with Recurrent Neural Networks." Mathematical Problems in Engineering 2018 (December 5, 2018): 1–16. http://dx.doi.org/10.1155/2018/6972481.
Повний текст джерелаАнотація:
In order to improve the safety, efficiency, and reliability in large scale wind turbines, a great deal of statistical and machine-learning models for wind turbine health monitoring system (WTHMS) are proposed based on SCADA variables. The data-driven WTHMS have been performed widely with the attentions on predicting the failures of the wind turbine or primary components. However, the health status of wind turbine often degrades gradually rather than suddenly. Thus, the SCADA variables change continuously to the occurrence of certain faults. Inspired by the ability of recurrent neural network (RNN) in redefining the raw sensory data, we introduce a hybrid methodology that combines the analysis of variance for each sequential SCADA variable with RNN to assess the health status of wind turbine. First, each original sequence is split by different variance ranges into several categories to improve the generalized ability of the RNN. Then, the long short-term memory (LSTM) is procured on the normal running sequence to learn the gradually changing situations. Finally, a weighted assessment method incorporating the health of primary components is applied to judge the health level of the wind turbine. Experiments on real-world datasets from two wind turbines demonstrate the effectiveness and generalization of the proposed model.
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Rohr, Alexander, and Clemens Jauch. "Software-in-the-Loop Simulation of a Gas-Engine for the Design and Testing of a Wind Turbine Emulator." Energies 14, no. 10 (May 17, 2021): 2898. http://dx.doi.org/10.3390/en14102898.
Повний текст джерелаАнотація:
In order to investigate the grid integration of wind turbines (WT) of various scales and designs, a wind turbine emulator (WTE) is being built in Flensburg within the state-funded project GrinSH. The special feature of this WTE is the use of a large gas engine instead of an electric motor to emulate the behavior of a WT. In order to develop the controls of this innovative WTE and to design the upcoming test runs under safe conditions, a software in the loop model (SILM) was applied. This SILM contained a mathematical model of the wind turbine, mathematical models of the gas engine with an integrated controller, and a model of the generator and frequency converter unit, as well as a preventive modulator of the reference signal (PMRS). The PMRS module converts the reference signal of the emulated WT in such a way that the dynamics of the engine components can be calculated and balanced in advance to enable the required behavior of the entire SILM despite the dynamics of the gas engine. It was found that the PMRS module, developed and tested in this work, increased the ability of the WTE, based on a gas engine, to reproduce the dynamics of a WT.
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Grebenikov, Viktor, Rostyslav Gamaliia, and Vladimir Popkov. "Permanent magnet generator with axial magnetic flow for wind plants." Bulletin of NTU "KhPI". Series: Problems of Electrical Machines and Apparatus Perfection. The Theory and Practice, no. 1 (5) (May 28, 2021): 26–32. http://dx.doi.org/10.20998/2079-3944.2021.1.05.
Повний текст джерелаАнотація:
The results of numerical and experimental studies of an electric generator with permanent magnets and axial magnetic flux for low-power wind turbines are presented. In order for wind turbines to successfully compete with sources of autonomous power supply based on solar energy, it is necessary to reduce the specific cost of electric generators. One of the possible ways to reduce the cost of a wind turbine is to replace a quiet-running multi-pole generator with a high-speed one, which is paired with a magnetic step-up gear. In this case, the electric generator can be designed for rotation frequency n = 1000 ÷ 3000 rpm. It is for this range of rotational speed that the optimal configuration and dimensions of the magnetic system of the electric generator have been determined, at which the maximum power value is reached. Comparisons of the calculated and experimental characteristics of the generator are carried out, the good coincidence of which confirms the adequacy of the developed mathematical models. These computer models are then used to study the dependence of the specific power of the generator on the height of the stator slots and the section of the winding wire made of copper tape. It is shown that for optimal geometrical parameters the magnetomotive force of the stator winding must be matched with the magnetomotive force of permanent magnets. Only for a certain range of slot heights is the maximum power at the rated current ensured. The characteristics of the investigated generators were calculated using the Simcenter MagNet software package.
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Xiao, Yancai, and Zhe Hua. "Misalignment Fault Prediction of Wind Turbines Based on Combined Forecasting Model." Algorithms 13, no. 3 (March 1, 2020): 56. http://dx.doi.org/10.3390/a13030056.
Повний текст джерелаАнотація:
Due to the harsh working environment of wind turbines, various types of faults are prone to occur during long-term operation. Misalignment faults between the gearbox and the generator are one of the latent common faults for doubly-fed wind turbines. Compared with other faults like gears and bearings, the prediction research of misalignment faults for wind turbines is relatively few. How to accurately predict its developing trend has always been a difficulty. In this paper, a combined forecasting model is proposed for misalignment fault prediction of wind turbines based on vibration and current signals. In the modelling, the improved Multivariate Grey Model (IMGM) is used to predict the deterministic trend and the Least Squares Support Vector Machine (LSSVM) optimized by quantum genetic algorithm (QGA) is adopted to predict the stochastic trend of the fault index separately, and another LSSVM optimized by QGA is used as a non-linear combiner. Multiple information of time-domain, frequency-domain and time-frequency domain of the wind turbine’s vibration or current signals are extracted as the input vectors of the combined forecasting model and the kurtosis index is regarded as the output. The simulation results show that the proposed combined model has higher prediction accuracy than the single forecasting models.
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Liu, Jui-Hung, and Nelson T. Corbita. "Performance analysis of different predictive models for condition monitoring of direct drive wind turbine generator." Measurement and Control 54, no. 3-4 (March 2021): 374–84. http://dx.doi.org/10.1177/00202940211003930.
Повний текст джерелаАнотація:
This paper presents a performance analysis of predictive models for the generator module which can be used as a reference for improvement in the condition monitoring system using wind turbines in a wind farm in Taiwan. With the generator being a critical component prone to failures, it is important to perform data analysis on its parameters that could be used for condition monitoring. The main innovative feature in this framework is the conduct of performance analysis before the development of the condition monitoring system. Also, the consistency of the performance between the different wind turbines in the wind farm is evaluated. The predictive models are generated using the neural network algorithm with a different combination of parameters from the SCADA system. The correlation of the parameters as well as the mean square error of the predictive models were then computed for analysis. Results showed that pairing of input parameters with a higher correlation to the output parameter would give better performance for the predictive model. Furthermore, the performance of the different models was consistent throughout the different wind turbines in the wind farm which indicates that the same model can be developed and used for wind turbines belonging to the same wind farm. Employing a preliminary performance analysis of different combinations of component parameters could help in optimizing predictive models for condition monitoring.
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Bobriakova, Elena, Artem Gundar, Sergiy Ivanov, Yurii Krashanytsya, Ivan Rudyk, Aleksandr Serbin, and Daniil Fedchenko. "Mathematical model of a vertical-axial wind motor in a viscous gas flow." Aerospace technic and technology, no. 1 (February 24, 2022): 12–24. http://dx.doi.org/10.32620/aktt.2022.1.02.
Повний текст джерелаАнотація:
The development of vertical axial wind turbines in Ukraine is in its infancy for many reasons: the lack of systematic theoretical and experimental studies of the aerodynamic characteristics of various schemes of wind turbines, the lack of an appropriate experimental base in technical universities, design organizations, insufficient number of available publications in foreign literature due to high competition between by monopoly firms. At present, various numerical methods are widely used to solve urgent problems of aero hydrodynamics, which are used for the approximate solution of boundary value problems in the form of differential forms of mathematical models. Their common disadvantages are the particularity and laboriousness of solutions, high requirements for computing resources, and, as a consequence, the complexity of solving optimization problems and economic feasibility. These problems can be avoided by using exact or approximate analytical dependences, which allow solving some urgent problems of studying the interaction of a viscous gas with the bearing elements of both aircraft and engineering structures. The existing methods for calculating the aerodynamic characteristics, based on the ideology of the mathematical model of the motion of an ideal medium without viscous interaction, do not correspond to the real processes and demands of practice. The article presents the ideology of determining the aerodynamic characteristics of the interacting system of solid profiles in the configuration of a vertical-axial wind turbine in a viscous gas flow. Based on generalized vector-tensor analysis, contour integral representations of solutions to the main problem of fluid and gas mechanics related to the determination of kinematic and dynamic characteristics of interaction have been constructed. In addition, the existence of a vector potential of the tensor of stresses and deformation velocities has been proved, reducing, in the simplest cases, the process of determining characteristics to integration. The limit values of these integral representations are a system of boundary integral equations, allow for elementary algorithmization, and lead to a system of linear algebraic equations having a single solution.
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Shirsath, Vaishali, and Prakash Burade. "Improvement of Wind Energy Systems by Optimizing Turbine Sizing and Placement to Enhance System Reliability." Iraqi Journal for Electrical and Electronic Engineering 18, no. 2 (July 1, 2022): 53–59. http://dx.doi.org/10.37917/ijeee.18.2.7.
Повний текст джерелаАнотація:
Wind energy and its conversion is part and parcel of renewable energy resources as cheaper and cleaner energy today even though the initial cost varies from place to place. Most of the government sector always promotes renewable energy with a provision of subsidies as observed worldwide. Wind energy is an actual solution over costlier conventional energy sources. If it is not properly placed and the selection of turbine design is not up to the mark, then investments may require more time to acquire Net Profit Value called as NPV. This research work is focused on the development of mathematical models to optimize the turbine size and locations considering all constraints such as the distance between the turbines, hub height, and investment in internal road and substation cost. Particle-Swarm-Optimization is an intelligent tool to optimize turbine place and size. The database management system is selected as the appropriate data storage platform for before and after optimization simulation. Various plots and excel outputs of .net programming are addressed for the success of optimization algorithms for the purpose of wind turbine placement and WTG design is suggested to manage wind energy such that power system reliability has been improved and the same is monitored through the reliability indices.
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Shahriari, Sayyed Ali Akbar. "Modelling and dynamic state estimation of a doubly fed induction generator wind turbine." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 39, no. 6 (September 11, 2020): 1393–409. http://dx.doi.org/10.1108/compel-07-2019-0277.
Повний текст джерелаАнотація:
Purpose This paper aims to propose an 18th-order nonlinear model for doubly fed induction generator (DFIG) wind turbines. Based on the proposed model, which is more complete than the models previously developed, an extended Kalman filter (EKF) is used to estimate the DFIG state variables. Design/methodology/approach State estimation is a popular approach in power system control and monitoring because of minimizing measurement noise level and obtaining non-measured state variables. To estimate all state variables of DFIG wind turbine, it is necessary to develop a model that considers all state variables. So, an 18th-order nonlinear model is proposed for DFIG wind turbines. EKF is used to estimate the DFIG state variables based on the proposed model. Findings An 18th-order nonlinear model is proposed for DFIG wind turbines. Furthermore, based on the proposed model, its state variables are estimated. Simulation studies are done in four cases to verify the ability of the proposed model in the estimation of state variables under noisy, wind speed variation and fault condition. The results demonstrate priority of the proposed model in the estimation of DFIG state variables. Originality/value Evaluating DFIG model to estimate its state variables precisely.
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Wiśniewski, Piotr, Francesco Balduzzi, Zbigniew Buliński, and Alessandro Bianchini. "Numerical Analysis on the Effectiveness of Gurney Flaps as Power Augmentation Devices for Airfoils Subject to a Continuous Variation of the Angle of Attack by Use of Full and Surrogate Models." Energies 13, no. 8 (April 12, 2020): 1877. http://dx.doi.org/10.3390/en13081877.
Повний текст джерелаАнотація:
The disclosing of new diffusion frontiers for wind energy, like deep-water offshore applications or installations in urban environments, is putting new focus on Darrieus vertical-axis wind turbines (VAWTs). To partially fill the efficiency gap of these turbines, aerodynamic developments are still needed. This work in particular focuses on the development of a mathematical model that allows predicting the possible performance improvements enabled in a VAWT by application of the Gurney flaps (GFs) as a function of the blade thickness, the rotor solidity and geometry of the Gurney flap itself. The performance of airfoil with GFs was evaluated by means of detailed simulations making use of computational fluid dynamics (CFD). The accuracy of the CFD model was assessed against the results of a dedicated experimental study. In the simulations, a dedicated method to simulate cycles of variation of the angle of attack similar to those taking place in a cycloidal motion (rather than purely sinusoidal ones) was also developed. Based on the results from CFD, a multidimensional interpolation based on the radial basis functions was conducted in order to find the GF design solution that provides the highest efficiency for a given turbine in terms of airfoil and solidity. The results showed that, for the selected study cases based on symmetric airfoils, the GF positioned facing outwards from the turbine, which provides the upwind part of the revolution, can lead to power increments ranging from approximately 30% for the lower-solidity turbine up to 90% for the higher-solidity turbine. It was also shown that the introduction of a GF should be coupled with a re-optimization of the airfoil thickness to maximize the performance.
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Cognet, V., S. Courrech du Pont, I. Dobrev, F. Massouh, and B. Thiria. "Bioinspired turbine blades offer new perspectives for wind energy." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 473, no. 2198 (February 2017): 20160726. http://dx.doi.org/10.1098/rspa.2016.0726.
Повний текст джерелаАнотація:
Wind energy is becoming a significant alternative solution for future energy production. Modern turbines now benefit from engineering expertise, and a large variety of different models exists, depending on the context and needs. However, classical wind turbines are designed to operate within a narrow zone centred around their optimal working point. This limitation prevents the use of sites with variable wind to harvest energy, involving significant energetic and economic losses. Here, we present a new type of bioinspired wind turbine using elastic blades, which passively deform through the air loading and centrifugal effects. This work is inspired from recent studies on insect flight and plant reconfiguration, which show the ability of elastic wings or leaves to adapt to the wind conditions and thereby to optimize performance. We show that in the context of energy production, the reconfiguration of the elastic blades significantly extends the range of operating regimes using only passive, non-consuming mechanisms. The versatility of the new turbine model leads to a large increase of the converted energy rate, up to 35%. The fluid/elasticity mechanisms involved for the reconfiguration capability of the new blades are analysed in detail, using experimental observations and modelling.
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Park, Rae-Jin, Jeong-Hwan Kim, Byungchan Yoo, Minhan Yoon, and Seungmin Jung. "Verification of Prediction Method Based on Machine Learning under Wake Effect Using Real-Time Digital Simulator." Energies 15, no. 24 (December 14, 2022): 9475. http://dx.doi.org/10.3390/en15249475.
Повний текст джерелаАнотація:
With the increase in the penetration rate of renewable energy sources, a machine-learning-based forecasting system has been introduced to the grid sector to improve the participation rate in the electricity market and reduce energy losses. In these studies, correlation analysis of mechanical and environmental variables, including geographical figures, is considered a crucial point to increase the prediction’s accuracy. Various models have been applied in terms of accuracy, speed calculation, and amount of data based on a mathematical model that can calculate the wake; however, it can be difficult to derive variables such as air density, roughness length, and the effect of turbulence on the structural characteristics of wind turbines. Furthermore, wake accuracy could decrease due to the excessive variables that come from the wake effect parameters. In this paper, we intend to conduct research to improve prediction accuracy by considering the wake effect of wind turbines using supervisory control and data acquisition (SCADA) data from the Dongbok wind farm. The wake divides the wind direction into four parts and then recognizes and predicts the affected wind turbine. The predicted result is the wake wind speed and its conversion to power generation by applying a power curve. We try to show the efficiency of machine learning by comparing the wake wind speed and the power generation in the wake model. This result shows the error rate using evaluation metrics of regression, such as mean squared error (MSE), root mean squared error (RMSE), and weighted absolute percentage error (WAPE), and attempts to verify power system impact and efficiency through a real-time digital simulator (RTDS).
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Ochoa, Danny, Sergio Martinez, and Paul Arévalo. "Extended Simplified Electro-Mechanical Model of a Variable-Speed Wind Turbine for Grid Integration Studies: Emulation and Validation on a Microgrid Lab." Electronics 11, no. 23 (November 29, 2022): 3945. http://dx.doi.org/10.3390/electronics11233945.
Повний текст джерелаАнотація:
The energy transition towards renewable energies is crucial for the sustainable development of a society based on hydrocarbons. The current level of penetration and growth of wind energy in electric power systems is evident and many researchers have presented new methods for simulating and representing the electrical and mechanical characteristics of variable-speed wind turbines. However, complete mathematical models developed and implemented, for example, in MATLAB/Simulink® software, require significant computational efforts that could make grid studies impractical when its scale tends to increase. To contribute to facing this issue, this paper proposes an extended simplified model for a variable-speed wind turbine that considers the dynamic behavior of its mechanical system and includes an approximate representation of the power electronic converter. This approach broadens the scope of studies related to grid frequency control and power quality (fast-frequency response, primary frequency control, and voltage control, among others), considerably reducing the computational burden. Several validations of the proposed simplified model are presented, including comparisons with a doubly fed induction generator-based wind turbine model (phasor type) from the MATLAB/Simulink® library, and laboratory experiments under controlled conditions. The results show a good fit of the proposed simplified model to the MATLAB/Simulink® model, with minimal delays about 3% of the wind turbine inertia constant. Moreover, with the proposal, the computational time is reduced by up to 80% compared to a detailed model. This time reduction is achieved without penalizing the numerical accuracy and the estimation quality of the real behavior of the variable-speed wind turbine.
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Jiang, Wenbo, and Mingyue Zhong. "Dynamic Equivalent Modeling of Wind Farm Based on Dominant Variable Hierarchical Clustering Algorithm." Mathematical Problems in Engineering 2021 (November 29, 2021): 1–10. http://dx.doi.org/10.1155/2021/7629414.
Повний текст джерелаАнотація:
The actual operating state of the wind turbine group is influenced by the wake effect and control mode; however, the current models cannot describe the actual operating state very well. A dynamic equivalent modeling method for a doubly fed wind power generator is proposed on the basis of ensuring the accurate description of the wind turbine group. As the clustering index, dominant variables are used in the hierarchical clustering algorithm, which are extracted by principal component analysis. Three dynamic equivalent models of 24 wind turbines are established using PSCAD software platform, which use 13 state variables, wind speed, and dominant variables as clustering indexes, respectively. Furthermore, the active power and reactive power output curves of wind farm are simulated in the case of the three-phase short-circuit fault on the system side or wind speed fluctuation, respectively. The simulation results demonstrate that it is reasonable and effective to extract slip ratio and wind turbine torque as clustering index, and the maximal relative error between the dominant variable equivalent model and 13-state-variable model is only 9.9%, which is greatly lower than that of the wind speed model, K-means clustering model, neural network model, and support vector machine model. This model is easy to implement and has wider application prospect, especially for characteristics analysis of large-scale wind farm connected to power grid.
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Becker, Marcus, Bastian Ritter, Bart Doekemeijer, Daan van der Hoek, Ulrich Konigorski, Dries Allaerts, and Jan-Willem van Wingerden. "The revised FLORIDyn model: implementation of heterogeneous flow and the Gaussian wake." Wind Energy Science 7, no. 6 (November 1, 2022): 2163–79. http://dx.doi.org/10.5194/wes-7-2163-2022.
Повний текст джерелаАнотація:
Abstract. In this paper, a new version of the FLOw Redirection and Induction Dynamics (FLORIDyn) model is presented. The new model uses the three-dimensional parametric Gaussian FLORIS model and can provide dynamic wind farm simulations at a low computational cost under heterogeneous and changing wind conditions. Both FLORIS and FLORIDyn are parametric models which can be used to simulate wind farms, evaluate controller performance and can serve as a control-oriented model. One central element in which they differ is in their representation of flow dynamics: FLORIS neglects these and provides a computationally very cheap approximation of the mean wind farm flow. FLORIDyn defines a framework which utilizes this low computational cost of FLORIS to simulate basic wake dynamics. This is achieved by creating so-called observation points (OPs) at each time step at the rotor plane which inherit the turbine state. In this work, we develop the initial FLORIDyn framework further considering multiple aspects. The underlying FLORIS wake model is replaced by a Gaussian wake model. The distribution and characteristics of the OPs are adapted to account for the new parametric model but also to take complex flow conditions into account. To achieve this, a mathematical approach is developed to combine the parametric model and the changing, heterogeneous world conditions and link them with each OP. We also present a computationally lightweight wind field model to allow for a simulation environment in which heterogeneous flow conditions are possible. FLORIDyn is compared to Simulator for Offshore Wind Farm Applications (SOWFA) simulations in three- and nine-turbine cases under static and changing environmental conditions. The results show a good agreement with the timing of the impact of upstream state changes on downstream turbines. They also show a good agreement in terms of how wakes are displaced by wind direction changes and when the resulting velocity deficit is experienced by downstream turbines. A good fit of the mean generated power is ensured by the underlying FLORIS model. In the three-turbine case, FLORIDyn simulates 4 s simulation time in 24.49 ms computational time. The resulting new FLORIDyn model proves to be a computationally attractive and capable tool for model-based dynamic wind farm control.
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Diop, A. D., C. Nichita, J. J. Belhache, B. Dakyo, and E. Ceanga. "Error Evaluation for Models of Real Time Wind Turbine Simulators." Wind Engineering 24, no. 3 (May 2000): 203–21. http://dx.doi.org/10.1260/0309524001495567.
Повний текст джерелаАнотація:
This paper deals with errors inherent in modelling wind turbine simulators. Firstly, different wind turbine simulators are categorised. The work concerns simulators having a real-time soft simulator and an electromechanical tracking system, using any type of servomotor 15–17. Having presented the wind turbine linearised models, with respect to types of servomotor control (in speed or in torque), an analysis is made of simulator mathematical models and simulation performance evaluation, according to the dynamical behaviour of the electromechanical tracking systems. Next, the simulator performances calculation is presented, followed by a simulation error analysis for some particular cases, in order to highlight the differences between the speed and torque control structures. Finally, a servomotor choice principle is established, illustrated by numerical results obtained with the servomotor of a real time wind turbine simulator.
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González-Hernández, José Genaro, and Rubén Salas-Cabrera. "Representation and estimation of the power coefficient in wind energy conversion systems." Revista Facultad de Ingeniería 28, no. 50 (January 10, 2019): 77–90. http://dx.doi.org/10.19053/01211129.v28.n50.2019.8816.
Повний текст джерелаАнотація:
This paper aims at summarizing various methods used for representing and estimating the power coefficient in wind turbines, such as exponential, sinusoidal and polynomial models, as well as mathematical tools known as state observers. We present an exhaustive bibliographic review of the models used to calculate the power coefficient, given that this type of studies are scarce nowadays. In addition, we propose models that can be satisfactorily used for various analyzes of wind energy conversion systems, such as the representation by a polynomial function of fourth degree and the models based on the stochastic probability function. The relevance of this work is supported by the advantages and disadvantages of the various models and estimators of the power coefficient, which are presented at the end of the article in a comparative table with the purpose of offering to the reader a general summary. Ultimately, this review aims at helping researchers, students, university professors and those who wish to venture into this field, even though they do not have much experience, to establish a quick synthesized understanding of the different models and representations of the power coefficient.
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Feijoo, Andres, Jose Luis Pazos, and Daniel Villanueva. "Conventional Asynchronous Wind Turbine Models Mathematical Expressions for the Load Flow Analysis." International Journal of Energy Engineering 3, no. 6 (December 20, 2013): 269–78. http://dx.doi.org/10.5963/ijee0306008.
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Thelen, Andrew, Leifur Leifsson, Anupam Sharma, and Slawomir Koziel. "RANS-based design optimization of dual-rotor wind turbines." Engineering Computations 35, no. 1 (March 5, 2018): 35–52. http://dx.doi.org/10.1108/ec-10-2016-0354.
Повний текст джерелаАнотація:
Purpose An improvement in the energy efficiency of wind turbines can be achieved using dual rotors. Because of complex flow physics, the design of dual-rotor wind turbines (DRWTs) requires repetitive evaluations of computationally expensive partial differential equation (PDE) simulation models. Approaches for solving design optimization of DRWTs constrained by PDE simulations are investigated. The purpose of this study is to determine design optimization algorithms which can find optimal designs at a low computational cost. Design/methodology/approach Several optimization approaches and algorithms are compared and contrasted for the design of DRWTs. More specifically, parametric sweeps, direct optimization using pattern search, surrogate-based optimization (SBO) using approximation-based models and SBO using kriging interpolation models with infill criteria are investigated for the DRWT design problem. Findings The approaches are applied to two example design cases where the DRWT fluid flow is simulated using the Reynolds-averaged Navier−Stokes (RANS) equations with a two-equation turbulence model on an axisymmetric computational grid. The main rotor geometry is kept fixed and the secondary rotor characteristics, using up to three variables, are optimized. The results show that the automated numerical optimization techniques were able to accurately find the optimal designs at a low cost. In particular, SBO algorithm with infill criteria configured for design space exploitation required the least computational cost. The widely adopted parametric sweep approach required more model evaluations than the optimization algorithms, as well as not being able to accurately find the optimal designs. Originality/value For low-dimensional PDE-constrained design of DRWTs, automated optimization algorithms are essential to find accurately and efficiently the optimal designs. More specifically, surrogate-based approaches seem to offer a computationally efficient way of solving such problems.
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Merizalde, Yuri, Luis Hernández-Callejo, Oscar Duque-Pérez, and Víctor Alonso-Gómez. "Diagnosis of wind turbine faults using generator current signature analysis: a review." Journal of Quality in Maintenance Engineering 26, no. 3 (October 22, 2019): 431–58. http://dx.doi.org/10.1108/jqme-02-2019-0020.
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Purpose Despite the wide dissemination and application of current signature analysis (CSA) in general industry, CSA is not commonly used in the wind industry, where the use of vibration signals predominates. Therefore, the purpose of this paper is to review the use of generator CSA (GCSA) in the online fault detection and diagnosis of wind turbines (WTs). Design/methodology/approach This is a bibliographical investigation in which the use of GCSA for the maintenance of WTs is analyzed. A section is dedicated to each of the main components, including the theoretical foundations on which GCSA is based and the methodology, mathematical models and signal processing techniques used by the proposals that exist on this topic. Findings The lack of appropriate technology and mathematical models, as well as the difficulty involved in performing actual studies in the field and the lack of research projects, has prevented the expansion of the use of GCSA for fault detection of other WT components. This research area has yet to be explored, and the existing investigations mainly focus on the gearbox and the doubly fed induction generator; however, modern signal treatment and artificial intelligence techniques could offer new opportunities in this field. Originality/value Although literature on the use of GCSA for the detection and diagnosis of faults in WTs has been published, these papers address specific applications for each of the WT components, especially gearboxes and generators. For this reason, the main contribution of this study is providing a comprehensive vision for the use of GCSA in the maintenance of WTs.
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Alati, Natale, Giuseppe Failla, and Felice Arena. "Seismic analysis of offshore wind turbines on bottom-fixed support structures." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373, no. 2035 (February 28, 2015): 20140086. http://dx.doi.org/10.1098/rsta.2014.0086.
Повний текст джерелаАнотація:
This study investigates the seismic response of a horizontal axis wind turbine on two bottom-fixed support structures for transitional water depths (30–60 m), a tripod and a jacket, both resting on pile foundations. Fully coupled, nonlinear time-domain simulations on full system models are carried out under combined wind–wave–earthquake loadings, for different load cases, considering fixed and flexible foundation models. It is shown that earthquake loading may cause a significant increase of stress resultant demands, even for moderate peak ground accelerations, and that fully coupled nonlinear time-domain simulations on full system models are essential to capture relevant information on the moment demand in the rotor blades, which cannot be predicted by analyses on simplified models allowed by existing standards. A comparison with some typical design load cases substantiates the need for an accurate seismic assessment in sites at risk from earthquakes.
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Yousefzadeh, Meysam, Shahin Hedayati Kia, Mohammad Hoseintabar Marzebali, Davood Arab Khaburi, and Hubert Razik. "Power-Hardware-in-the-Loop for Stator Windings Asymmetry Fault Analysis in Direct-Drive PMSG-Based Wind Turbines." Energies 15, no. 19 (September 21, 2022): 6896. http://dx.doi.org/10.3390/en15196896.
Повний текст джерелаАнотація:
This article studies the stator windings asymmetry fault in direct-drive permanent magnet synchronous generator(PMSG)-based wind turbines (WTs), having passive converters at the generator side, through developing a power-hardware-in-the-loop (P-H-i-L) system. It is based on a digital real-time simulation (DRTS) of turbine blades, a wind generator in the abc reference frame, and a three-phase diode rectifier mathematical models. The DC voltage, provided by the model of the three-phase diode rectifier, is linked to a one-level hardware boost converter by using a programmable DC power supply. Furthermore, the maximum power point tracking technique, based on the optimal torque, is evaluated when the one-level boost converter supplies a resistive load. Stator windings asymmetry fault in the PMSG is identified by analyzing the rectifier output voltage, the rotor speed, and the electrical signatures of the boost converter. It shows that this kind of fault clearly gives rise to the amplitudes of both 2·fs and 4·fs frequency components in the mentioned signatures, where fs is the main frequency component of the stator current. DRTSs are compared with digital offline simulations (DoSs), based on a Matlab/Simulink Simscape physical model, to demonstrate the efficacy of the proposed framework.
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Shen, Yingjun, Zhe Song, and Andrew Kusiak. "Enhancing the generalizability of predictive models with synergy of data and physics." Measurement Science and Technology 33, no. 3 (December 29, 2021): 034002. http://dx.doi.org/10.1088/1361-6501/ac3944.
Повний текст джерелаАнотація:
Abstract Wind farms require predictive models for predictive maintenance. There is a need to predict values of non-observable parameters beyond ranges reflected in available data. A predictive model developed for one machine many not perform well for another similar machine. This is usually due to a lack of generalizability of data-driven models. To increase the generalizability of predictive models, this research integrates data mining with first-principle knowledge. Physics-based principles are combined with machine learning algorithms through feature engineering, strong rules and divide-and-conquer. The proposed synergy concept is illustrated with a wind turbine blade icing prediction and achieves significant predictive accuracy across different turbines. The proposed process should be widely accepted by wind energy predictive maintenance practitioners because of its simplicity and efficiency. Furthermore, the testing scores of KNN, CART and DNN algorithms are increased by 44.78%, 32.72% and 9.13%, respectively, with our proposed process. We demonstrate the importance of embedding physical principles within the machine learning process, and also highlight an important point that the need for more complex machine learning algorithms in industrial big data mining is often much less than it is in other applications, making it essential to incorporate physics and follow the ‘less is more’ philosophy.
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Thelen, Andrew, Leifur Leifsson, Anupam Sharma, and Slawomir Koziel. "Variable-fidelity shape optimization of dual-rotor wind turbines." Engineering Computations 35, no. 7 (October 1, 2018): 2514–42. http://dx.doi.org/10.1108/ec-12-2017-0502.
Повний текст джерелаАнотація:
Purpose Dual-rotor wind turbines (DRWTs) are a novel type of wind turbines that can capture more power than their single-rotor counterparts. Because their surrounding flow fields are complex, evaluating a DRWT design requires accurate predictive simulations, which incur high computational costs. Currently, there does not exist a design optimization framework for DRWTs. Since the design optimization of DRWTs requires numerous model evaluations, the purpose of this paper is to identify computationally efficient design approaches. Design/methodology/approach Several algorithms are compared for the design optimization of DRWTs. The algorithms vary widely in approaches and include a direct derivative-free method, as well as three surrogate-based optimization methods, two approximation-based approaches and one variable-fidelity approach with coarse discretization low-fidelity models. Findings The proposed variable-fidelity method required significantly lower computational cost than the derivative-free and approximation-based methods. Large computational savings come from using the time-consuming high-fidelity simulations sparingly and performing the majority of the design space search using the fast variable-fidelity models. Originality/value Due the complex simulations and the large number of designable parameters, the design of DRWTs require the use of numerical optimization algorithms. This work presents a novel and efficient design optimization framework for DRWTs using computationally intensive simulations and variable-fidelity optimization techniques.
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Wang, Jin, Yinke Dou, Guangyu Zuo, Musheng Lan, Xiaomin Chang, Bo Yang, Zhiheng Du, Miaoyuan Yu, and Qingyang Mao. "Application and effect analysis of renewable energy in a small standalone automatic observation system deployed in the polar regions." AIP Advances 12, no. 12 (December 1, 2022): 125218. http://dx.doi.org/10.1063/5.0128256.
Повний текст джерелаАнотація:
Considering the difficulty of power supply for automatic observation equipment in the polar regions, this paper introduced a small standalone renewable energy system with wind–solar co-generation as the energy supply scheme. Mathematical models were given, including solar photovoltaic panels, wind turbines, solar irradiance, wind energy density, and renewable energy assessment. ERA-Interim atmospheric reanalysis data were used to evaluate solar energy resources, and the synergistic effect of wind–solar resources on renewable energy was also analyzed and discussed. The system composition of the small standalone renewable energy system was proposed in this study. This system deployed near Zhongshan Station was taken as the object of investigation to analyze the operation performance of each component of the system in different months, and the technical feasibility of the system has also been verified. The results showed that the wind–solar resources in the polar regions had a synergistic effect, which can provide an effective and feasible scheme for the power supply of automatic observation equipment. Through research and analysis, it was found that each component of the renewable energy system, including photovoltaic panels, wind turbines, and batteries, could meet the long-term power supply requirements of automatic observation regardless of the polar periods, polar day or polar night. This paper can not only provide theoretical and data support for the application of small independent renewable energy systems in the polar regions but also provide feasible solutions for clean energy supply of the systems and equipment for independent observation stations deployed in uninhabited islands and alpine regions.
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Muskulus, M. "Simplified rotor load models and fatigue damage estimates for offshore wind turbines." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373, no. 2035 (February 28, 2015): 20140347. http://dx.doi.org/10.1098/rsta.2014.0347.
Повний текст джерелаАнотація:
The aim of rotor load models is to characterize and generate the thrust loads acting on an offshore wind turbine. Ideally, the rotor simulation can be replaced by time series from a model with a few parameters and state variables only. Such models are used extensively in control system design and, as a potentially new application area, structural optimization of support structures. Different rotor load models are here evaluated for a jacket support structure in terms of fatigue lifetimes of relevant structural variables. All models were found to be lacking in accuracy, with differences of more than 20% in fatigue load estimates. The most accurate models were the use of an effective thrust coefficient determined from a regression analysis of dynamic thrust loads, and a novel stochastic model in state-space form. The stochastic model explicitly models the quasi-periodic components obtained from rotational sampling of turbulent fluctuations. Its state variables follow a mean-reverting Ornstein–Uhlenbeck process. Although promising, more work is needed on how to determine the parameters of the stochastic model and before accurate lifetime predictions can be obtained without comprehensive rotor simulations.
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Inoue, Tomoya, Ahmad Adilah, Kazuhiro Iijima, Sho Oh, and Hideyuki Suzuki. "Discussion on Coupling Effect in Structural Load of FOWT for Condensing Wind and Wave Bins for Spectral Fatigue Analysis." Journal of Marine Science and Engineering 8, no. 11 (November 18, 2020): 937. http://dx.doi.org/10.3390/jmse8110937.
Повний текст джерелаАнотація:
Floating Offshore Wind Turbines (FOWTs) are subject to combined wind and wave loads. The response is not given as a simple sum of the wind-only response and wave-only response due to nonlinear coupling effects, which makes the structural analysis more complex and time-consuming. When a spectral approach for the structural fatigue analysis is considered, it is necessary to accurately estimate the variance of the combined stress taking account of the coupling effect. In this study, firstly the characteristics of the combined response are investigated. It is found out the coupling effects are two-fold; one is the aerodynamic exciting load increase for the forced motion in the wave frequency range. The other is the aerodynamic damping effect due to the increase of the relative wind speed, which is prominent in the structural vibration frequency range. Mathematical models to account for these coupling effects are developed. Then, a series of simulations are performed on three types of FOWTs to validate the models. It is shown that the characteristics of the combined response are different among the three types of the platforms and the developed model can explain the increase/decrease of the variance of the combined stress when compared with two decoupled wave-only and wind-only simulations.