Статті в журналах: "Generator parameter estimation"

1

Berhausen, Sebastian, and Stefan Paszek. "Synchronous Generator Model Parameter Estimation Based on Noisy Dynamic Waveforms." Journal of Electrical Engineering 67, no. 1 (January 1, 2016): 21–28. http://dx.doi.org/10.1515/jee-2016-0003.

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Abstract In recent years, there have occurred system failures in many power systems all over the world. They have resulted in a lack of power supply to a large number of recipients. To minimize the risk of occurrence of power failures, it is necessary to perform multivariate investigations, including simulations, of power system operating conditions. To conduct reliable simulations, the current base of parameters of the models of generating units, containing the models of synchronous generators, is necessary. In the paper, there is presented a method for parameter estimation of a synchronous generator nonlinear model based on the analysis of selected transient waveforms caused by introducing a disturbance (in the form of a pseudorandom signal) in the generator voltage regulation channel. The parameter estimation was performed by minimizing the objective function defined as a mean square error for deviations between the measurement waveforms and the waveforms calculated based on the generator mathematical model. A hybrid algorithm was used for the minimization of the objective function. In the paper, there is described a filter system used for filtering the noisy measurement waveforms. The calculation results of the model of a 44 kW synchronous generator installed on a laboratory stand of the Institute of Electrical Engineering and Computer Science of the Silesian University of Technology are also given. The presented estimation method can be successfully applied to parameter estimation of different models of high-power synchronous generators operating in a power system.

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2

Sanin-Villa, Daniel, Oscar Danilo Montoya, Walter Gil-González, Luis Fernando Grisales-Noreña, and Alberto-Jesus Perea-Moreno. "Parameter Estimation of a Thermoelectric Generator by Using Salps Search Algorithm." Energies 16, no. 11 (May 24, 2023): 4304. http://dx.doi.org/10.3390/en16114304.

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Thermoelectric generators (TEGs) have the potential to convert waste heat into electrical energy, making them attractive for energy harvesting applications. However, accurately estimating TEG parameters from industrial systems is a complex problem due to the mathematical complex non-linearities and numerous variables involved in the TEG modeling. This paper addresses this research gap by presenting a comparative evaluation of three optimization methods, Particle Swarm Optimization (PSO), Salps Search Algorithm (SSA), and Vortex Search Algorithm (VSA), for TEG parameter estimation. The proposed integrated approach is significant as it overcomes the limitations of existing methods and provides a more accurate and rapid estimation of TEG parameters. The performance of each optimization method is evaluated in terms of root mean square error (RMSE), standard deviation, and processing time. The results indicate that all three methods perform similarly, with average RMSE errors ranging from 0.0019 W to 0.0021 W, and minimum RMSE errors ranging from 0.0017 W to 0.0018 W. However, PSO has a higher standard deviation of the RMSE errors compared to the other two methods. In addition, we present the optimized parameters achieved through the proposed optimization methods, which serve as a reference for future research and enable the comparison of various optimization strategies. The disparities observed in the optimized outcomes underscore the intricacy of the issue and underscore the importance of the integrated approach suggested for precise TEG parameter estimation.

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3

Berhausen, S., and S. Paszek. "Use of the finite element method for parameter estimation of the circuit model of a high power synchronous generator." Bulletin of the Polish Academy of Sciences Technical Sciences 63, no. 3 (September 1, 2015): 575–82. http://dx.doi.org/10.1515/bpasts-2015-0067.

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Abstract The paper presents the two-dimensional, field-circuit model of a high power synchronous generator verified by measurements. The model enables determining the waveforms of electromagnetic quantities in steady and transient states. Verification of the model was based on comparison of the measured and calculated waveforms after a disturbance in the voltage regulation system of a TWW-200-2 generator operating in Połaniec Power Plant. There are also presented the field methods for determining electromagnetic parameters (synchronous reactances and time constants) when using the distributions of static and quasi-static, magnetic and electromagnetic fields calculated by the finite element method (FEM). The set of these parameters was used as the starting parameters of the optimization algorithm for estimation of electromagnetic parameters of the synchronous generator circuit model. The dynamic waveforms under the generator load conditions calculated by the finite element method are the basis of parameter estimation. The parameter estimation of the generator model was performed with the use of the least squares method.

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4

Lai, Yening, Ling Zhu, Xueping Pan, Jinpeng Guo, Dazhuang He, and Wei Liang. "Online Estimation of the Mechanical Parameters of a Wind Turbine with Doubly Fed Induction Generator by Utilizing Turbulence Excitations." Energies 15, no. 6 (March 21, 2022): 2277. http://dx.doi.org/10.3390/en15062277.

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In this paper, a new method using wind turbulence excitation is proposed to estimate the parameters of the mechanical system (drivetrain and pitch angle controller) in a Doubly Fed Induction Generator (DFIG) Wind Turbine (WT). Firstly, simulations were carried out for a DFIG WT under turbulence excitations. The spectral contents of the responses imply that the transients of the electrical system (generator and converter), which are much faster than those of the mechanical system, can be neglected when estimating the mechanical parameters. Based on this, a simplified model related to the mechanical system of the DFIG WT was derived by applying the model reduction technique. Secondly, the parameter sensitivity of Power Spectral Density (PSD) was used to quantify the impacts of individual parameters on the dynamics of the mechanical system, and the influential parameters were selected on the basis of the sensitivity results. Finally, a weighted least-squares optimization problem, which is suitable for a system with close oscillation modes, was formulated for parameter estimation. The estimation results based on two different types of optimization methods were compared, and their estimation accuracies validate the effectiveness of the proposed method.

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5

SANTANA, Danyelle. "A Novel Prony Approach for Synchronous Generator Parameter Estimation." PRZEGL�D ELEKTROTECHNICZNY 1, no. 1 (January 5, 2015): 52–56. http://dx.doi.org/10.15199/48.2015.01.09.

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6

Jaworski, Piotr. "On Truncation Invariant Copulas and their Estimation." Dependence Modeling 5, no. 1 (January 26, 2017): 133–44. http://dx.doi.org/10.1515/demo-2017-0009.

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AbstractThe paper deals with the family of irreducible left truncation invariant bivariate copulas, which admit a nontrivial lower tail dependence function. Such copulas, similarly as the Archimedean ones, are characterized by a functional parameter, a generator being an increasing convex function.We provide a nonparametric, piece-wise linear estimator of such generators.

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7

Moghadam, Farshad Gholami Nejad, Navid Taghizadegan, and Haghi Pour Meraj. "Method for Illconditioned Parameter Estimation Application in Synchronous Generators." Applied Mechanics and Materials 448-453 (October 2013): 2616–25. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.2616.

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Fault detection, isolation, and fault diagnosis for a synchronous generator is a desirable feature that could aid in better monitoring and automation of the machine behavior, and could have a significant impact in establishing an adequate maintenance schedule that ensures proper operation while taking into consideration cost and risk of having a large generator and its maintenance. This work looks in parameter estimation’s algorithm methods those can used in fault detection, isolation and diagnosis. In a broad sense, a fault is understood as any kind of anomaly or malfunction that leads to an undesired performance of the system under consideration.

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8

Karayaka, H. B., A. Keyhani, G. T. Heydt, B. L. Agrawal, and D. A. Selin. "Synchronous generator model identification and parameter estimation from operating data." IEEE Transactions on Energy Conversion 18, no. 1 (March 2003): 121–26. http://dx.doi.org/10.1109/tec.2002.808347.

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9

Nie, Yonghui, He Wang, Lei Gao, Chunying Wu, and Meng Xi. "Adaptive Parameter Estimation for Static Var Generators Based on Wind Speed Fluctuation of Wind Farms." International Transactions on Electrical Energy Systems 2022 (March 10, 2022): 1–12. http://dx.doi.org/10.1155/2022/3877777.

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The emergence of flexible AC transmission technology provides a new technical means for ensuring the reliable grid connection and stable operation of wind farms. Among them, the static reactive power generator has a fast response speed, which can accurately compensate for the reactive power of the wind farm and improve the power factor; this is widely used in wind farms. To obtain accurate static var generator (SVG) parameters to meet the reliability requirements of a power system, we propose an adaptive estimation method that considers the wind speed fluctuation of wind farms. First, analyzing the dynamic SVG characteristics allowed us to establish a mathematical model. Then, the corresponding relationship between the sensitivity values of the parameters to be identified and the fluctuating wind speed was established, and low and high wind speed models were constructed. Finally, for accurate estimation considering wind speed fluctuation, the parameter initial values are obtained by combining the low wind speed and high wind speed model identification parameters, and we introduce the multimode hybrid estimation of the SVG parameters, providing a new method for accurately identifying the SVG model parameters. The simulation results of the parameter estimation demonstrate the accuracy and stability of the proposed method.

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10

Ghahremani, E., M. Karrari, and O. P. Malik. "Synchronous generator third-order model parameter estimation using online experimental data." IET Generation, Transmission & Distribution 2, no. 5 (2008): 708. http://dx.doi.org/10.1049/iet-gtd:20080175.

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11

Geraldi, Edson L., Tatiane C. C. Fernandes, Artur B. Piardi, Ahda P. Grilo, and Rodrigo A. Ramos. "Parameter estimation of a synchronous generator model under unbalanced operating conditions." Electric Power Systems Research 187 (October 2020): 106487. http://dx.doi.org/10.1016/j.epsr.2020.106487.

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12

Sanin-Villa, Daniel, Oscar Danilo Montoya, and Luis Fernando Grisales-Noreña. "Material Property Characterization and Parameter Estimation of Thermoelectric Generator by Using a Master–Slave Strategy Based on Metaheuristics Techniques." Mathematics 11, no. 6 (March 9, 2023): 1326. http://dx.doi.org/10.3390/math11061326.

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Thermoelectric generators (TEGs) have gained significant interest as a sustainable energy source, due to their ability to convert thermal energy into electrical energy through the Seebeck effect. However, the power output of TEGs is highly dependent on the thermoelectric material properties and operational conditions. Accurate modeling and parameter estimation are essential for optimizing and designing TEGs, as well as for integrating them into smart grids to meet fluctuating energy demands. This work examines the challenges of accurate modeling and parameter estimation of TEGs and explores various optimization metaheuristics techniques to find TEGs parameters in real applications from experimental conditions. The paper stresses the importance of determining the properties of TEGs with precision and using parameter estimation as a technique for determining the optimal values for parameters in a TEG mathematical model that represent the actual behavior of a thermoelectric module. This methodological approach can improve TEG performance and aid in efficient energy supply and demand management, thus reducing the reliance on traditional fossil fuel-based power generation.

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13

Saifuzam Jamri, Mohd, Muhammad Nizam Kamarudin, Mohd Luqman Mohd Jamil, and Muhammad Iqbal Zakaria. "Total power deficit estimation for isolated power system network using H∞ norm method." Bulletin of Electrical Engineering and Informatics 12, no. 5 (October 1, 2023): 3142–52. http://dx.doi.org/10.11591/eei.v12i5.4041.

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An isolated electrical network with an independent local distributed generator is very sensitive towards the contingencies between load demand and supply. Although the network system has less complexity in term of structure, its stability condition is crucial due to its stand-alone operating condition. Hence, to monitor the stability of the network, total power deficit is the only variable that can be estimated. This study proposed to utilize the filtering problem to design an estimator that can estimate the total power deficiency. For verification, the design estimator was tested under two cases which are nominal case and parameter uncertainty case. In nominal case, the system parameters are assumed to be known while in parameter uncertainty case the system has contaminated with uncertain parameter where its admissible value is laying in a given polytope. With complying the linear matrix inequality (LMI) constraint, the main objective function of the norm was guaranteed with minimum upper bound. The results show that the dynamical behaviors of designed estimator successfully trace the actual power deficit signal at steady state with minimal estimation error.

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14

Mercier, Thibaud, Jean-Melaine Favennec, and Alexandre Girard. "ICONE23-1442 DATA ASSIMILATION AND PWR PRIMARY PARAMETERS ESTIMATION : ENHANCEMENT OF A 0D MODEL AND CALIBRATION OF RANDOM PARAMETER GENERATOR FOR BACKGROUND TERMS EVALUATION." Proceedings of the International Conference on Nuclear Engineering (ICONE) 2015.23 (2015): _ICONE23–1—_ICONE23–1. http://dx.doi.org/10.1299/jsmeicone.2015.23._icone23-1_203.

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15

Ćalasan, Martin, Mihailo Micev, Ziad M. Ali, Ahmed F. Zobaa, and Shady H. E. Abdel Aleem. "Parameter Estimation of Induction Machine Single-Cage and Double-Cage Models Using a Hybrid Simulated Annealing–Evaporation Rate Water Cycle Algorithm." Mathematics 8, no. 6 (June 23, 2020): 1024. http://dx.doi.org/10.3390/math8061024.

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This paper presents the usage of the hybrid simulated annealing—evaporation rate water cycle algorithm (SA-ERWCA) for induction machine equivalent circuit parameter estimation. The proposed algorithm is applied to nameplate data, measured data found in the literature, and data measured experimentally on a laboratory three-phase induction machine operating as an induction motor and as an induction generator. Furthermore, the proposed method is applied to both single-cage and double-cage equivalent circuit models. The accuracy and applicability of the proposed SA-ERWCA are intensively investigated, comparing the machine output characteristics determined by using SA-ERWCA parameters with corresponding characteristics obtained by using parameters determined using known methods from the literature. Also, the comparison of the SA-ERWCA with classic ERWCA and other algorithms used in the literature for induction machine parameter estimation is presented. The obtained results show that the proposed algorithm is a very effective and accurate method for induction machine parameter estimation. Furthermore, it is shown that the SA-ERWCA has the best convergence characteristics compared to other algorithms for induction machine parameter estimation in the literature.

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16

de Souza, Rausley Adriano Amaral, Antonio Marcelo Oliveira Ribeiro та Dayan Adionel Guimarães. "On the Efficient Generation ofα-κ-μandα-η-μWhite Samples with Applications". International Journal of Antennas and Propagation 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/873890.

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This paper is concerned with a simple and highly efficient random sequence generator for uncorrelatedα-κ-μandα-η-μvariates. The algorithm may yield an efficiency of almost 100%, and this high efficiency can be reached for all special cases such asα-μ, κ-μ, η-μ, Nakagami-m, Nakagami-q, Weibull, Hoyt, Rayleigh, Rice, Exponential, and the One-Sided Gaussian. This generator is implemented via the rejection technique and allows for arbitrary fading parameters. The goodness-of-fit is measured using the Kolmogorov-Smirnov and Anderson-Darling tests. The maximum likelihood parameter estimation for theκ-μdistribution is proposed and verified against true values of the parameters chosen in the generator. We also provide two important applications for the random sequence generator, the first one dealing with the performance assessment of a digital communication system over theα-κ-μandα-η-μfading channels and the second one dealing with the performance assessment of the spectrum sensing with energy detection over special cases of these channels. Theoretical and simulation results are compared, validating again the accuracy of the generators.

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17

Chow, J. H., M. T. Glinkowski, R. J. Murphy, T. W. Cease, and N. Kosaka. "Generator and exciter parameter estimation of Fort Patrick Henry Hydro Unit 1." IEEE Transactions on Energy Conversion 14, no. 4 (1999): 923–29. http://dx.doi.org/10.1109/60.815009.

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18

Xu, Yijun, Lamine Mili, Mert Korkali, and Xiao Chen. "An Adaptive Bayesian Parameter Estimation of a Synchronous Generator Under Gross Errors." IEEE Transactions on Industrial Informatics 16, no. 8 (August 2020): 5088–98. http://dx.doi.org/10.1109/tii.2019.2950238.

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19

Challa, Kiran Kumar, and Gurunath Gurrala. "Dynamic State and Parameter Estimation of Synchronous Generator from Digital Relay Records." Electric Power Systems Research 189 (December 2020): 106743. http://dx.doi.org/10.1016/j.epsr.2020.106743.

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20

Boboń, A., A. Nocoń, S. Paszek, and P. Pruski. "Determination of synchronous generator nonlinear model parameters based on power rejection tests using a gradient optimization algorithm." Bulletin of the Polish Academy of Sciences Technical Sciences 65, no. 4 (August 1, 2017): 479–88. http://dx.doi.org/10.1515/bpasts-2017-0053.

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AbstractThe paper presents a method for determining electromagnetic parameters of different synchronous generator models based on dynamic waveforms measured at power rejection. Such a test can be performed safely under normal operating conditions of a generator working in a power plant. A generator model was investigated, expressed by reactances and time constants of steady, transient, and subtransient state in the d and q axes, as well as the circuit models (type (3,3) and (2,2)) expressed by resistances and inductances of stator, excitation, and equivalent rotor damping circuits windings. All these models approximately take into account the influence of magnetic core saturation. The least squares method was used for parameter estimation. There was minimized the objective function defined as the mean square error between the measured waveforms and the waveforms calculated based on the mathematical models. A method of determining the initial values of those state variables which also depend on the searched parameters is presented. To minimize the objective function, a gradient optimization algorithm finding local minima for a selected starting point was used. To get closer to the global minimum, calculations were repeated many times, taking into account the inequality constraints for the searched parameters. The paper presents the parameter estimation results and a comparison of the waveforms measured and calculated based on the final parameters for 200 MW and 50 MW turbogenerators.

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21

Khac, Tung Nguyen, Sergey M. Vlasov, and Anton A. Pyrkin. "Parameters estimation of multi-sinusoidal signal in finite-time." Cybernetics and Physics, Volume 11, 2022, Number 2 (September 30, 2022): 74–81. http://dx.doi.org/10.35470/2226-4116-2022-11-2-74-81.

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The problems of identifying the frequency and parameters of multi-sinusoidal signals with constant parameters are considered in finite time. The signal is represented as the output of a linear generator, where the parameters of the sinusoidal signal (amplitude, phase, and frequency) are unknown. The main idea is to apply the Jordan waveform and lag to parameterize the signal and obtain a linear regression model. Unknown parameters are estimated using DREM method. The performance of algorithms considered in the article is illustrated by computer modeling. Our main contribution is to propose a new approach for parameterization of multisinusoidal signals and finite time parameter estimation.

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22

Iriarte, Yuri A., Mário de Castro, and Héctor W. Gómez. "The Lambert-F Distributions Class: An Alternative Family for Positive Data Analysis." Mathematics 8, no. 9 (August 21, 2020): 1398. http://dx.doi.org/10.3390/math8091398.

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In this article, we introduce a new probability distribution generator called the Lambert-F generator. For any continuous baseline distribution F, with positive support, the corresponding Lambert-F version is generated by using the new generator. The result is a new class of distributions with one extra parameter that generalizes the baseline distribution and whose quantile function can be expressed in closed form in terms of the Lambert W function. The hazard rate function of a Lambert-F distribution corresponds to a modification of the baseline hazard rate function, greatly increasing or decreasing the baseline hazard rate for earlier times. Herein, we study the main structural properties of the new class of distributions. Special attention is given to two particular cases that can be understood as two-parameter extensions of the well-known exponential and Rayleigh distributions. We discuss parameter estimation for the proposed models considering the moments and maximum likelihood methods. Finally, two applications were developed to illustrate the usefulness of the proposed distributions in the analysis of data from different real settings.

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23

Klevtsov, I., and R. Crane. "Random Thermal Stress Oscillations and Fatigue Life Estimation for Steam Generator Tubes." Journal of Pressure Vessel Technology 116, no. 2 (May 1, 1994): 110–14. http://dx.doi.org/10.1115/1.2929563.

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A one-dimensional computation model was used to determine the temperature and stress fields under conditions corresponding to those found in once-through steam generator tubes. The random oscillatory nature of the water/steam convective boundary conditions in the transition boiling zone was simulated by postulating random variations in heat transfer coefficients or flow temperatures. Statistical parameters describing the tube temperatures and thermal stress oscillatory history are determined allowing appropriate fatigue life estimations to be made. The results indicate that the tube wall temperature oscillation parameter provides a strong influence on thermal stress and the predicted fatigue life. In contrast, Biot number variations provide only a relatively small effect. An improved method of determining the allowable thermal stress limitations due to certain wall temperature oscillations is proposed.

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24

Takahashi, Kosuke, Nyam Jargalsaikhan, Shriram Rangarajan, Ashraf Mohamed Hemeida, Hiroshi Takahashi, and Tomonobu Senjyu. "Output Control of Three-Axis PMSG Wind Turbine Considering Torsional Vibration Using H Infinity Control." Energies 13, no. 13 (July 5, 2020): 3474. http://dx.doi.org/10.3390/en13133474.

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Due to changes in wind, the torque obtained from the wind turbine always fluctuates. Here, the wind turbine and the rotor of the generator are connected by a shaft that is one elastic body, and each rotating body has different inertia. The difference in inertia between the wind turbine and the generator causes a torsion between the wind generator and the generator; metal fatigue and torsion can damage the shaft. Therefore, it is necessary to consider the axial torsional vibration suppression of a geared wind power generator using a permanent magnet synchronous generator (PMSG). In addition, errors in axis system parameters occur due to long-term operation of the generator, and it is important to estimate for accurate control. In this paper, we propose torque estimation using H ∞ observer and axial torsional vibration suppression control in a three inertia system. The H ∞ controller is introduced into the armature current control system (q-axis current control system) of the wind power generator. Even if parameter errors and high-frequency disturbances are included, the shaft torsional torque is estimated by the H ∞ observer that can perform robust estimation. Moreover, by eliminating the resonance point of the shaft system, vibration suppression of the shaft torsional torque is achieved. The results by the proposed method can suppress axial torsional vibration and show the effect better than the results using Proportional-Integral (PI) control.

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25

Ahmadi, Salman, Mehdi Karrari, and Om P. Malik. "Synchronous Generator Parameter Estimation Using Data Collected with Machine in Closed-loop Operation." Electric Power Components and Systems 43, no. 16 (August 31, 2015): 1859–71. http://dx.doi.org/10.1080/15325008.2015.1057882.

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Muhammad, Mustapha, Huda M. Alshanbari, Ayed R. A. Alanzi, Lixia Liu, Waqas Sami, Christophe Chesneau, and Farrukh Jamal. "A New Generator of Probability Models: The Exponentiated Sine-G Family for Lifetime Studies." Entropy 23, no. 11 (October 24, 2021): 1394. http://dx.doi.org/10.3390/e23111394.

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In this article, we propose the exponentiated sine-generated family of distributions. Some important properties are demonstrated, such as the series representation of the probability density function, quantile function, moments, stress-strength reliability, and Rényi entropy. A particular member, called the exponentiated sine Weibull distribution, is highlighted; we analyze its skewness and kurtosis, moments, quantile function, residual mean and reversed mean residual life functions, order statistics, and extreme value distributions. Maximum likelihood estimation and Bayes estimation under the square error loss function are considered. Simulation studies are used to assess the techniques, and their performance gives satisfactory results as discussed by the mean square error, confidence intervals, and coverage probabilities of the estimates. The stress-strength reliability parameter of the exponentiated sine Weibull model is derived and estimated by the maximum likelihood estimation method. Also, nonparametric bootstrap techniques are used to approximate the confidence interval of the reliability parameter. A simulation is conducted to examine the mean square error, standard deviations, confidence intervals, and coverage probabilities of the reliability parameter. Finally, three real applications of the exponentiated sine Weibull model are provided. One of them considers stress-strength data.

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El-Morshedy, Mahmoud, Muhammad H. Tahir, Muhammad Adnan Hussain, Afrah Al-Bossly, and Mohamed S. Eliwa. "A New Flexible Univariate and Bivariate Family of Distributions for Unit Interval (0, 1)." Symmetry 14, no. 5 (May 19, 2022): 1040. http://dx.doi.org/10.3390/sym14051040.

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We propose a new generator for unit interval which is used to establish univariate and bivariate families of distributions. The univariate family can serve as an alternate to the Kumaraswamy-G univariate family proposed earlier by Cordeiro and de-Castro in 2011. Further, the new generator can also be used to develop more alternate univariate and bivariate G-classes such as beta-G, McDonald-G, Topp-Leone-G, Marshall-Olkin-G and Transmuted-G for support (0, 1). Some structural properties of the univariate family are derived and the estimation of parameters is dealt. The properties of a special model of this new univariate family called a New Kumaraswamy-Weibull (NKwW) distribution are obtained and parameter estimation is considered. A Monte Carlo simulation is reported to assess NKwW model parameters. The bivariate extension of the family is proposed and the estimation of parameters is described. The simulation study is also conducted for bivariate model. Finally, the usefulness of the univariate NKwW model is illustrated empirically by means of three real-life data sets on Air Conditioned Failures, Flood and Breaking Strength of Fibers, and one real-life data on UEFA Champion’s League for bivariate model.

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Koloko, R. J. Koloko, P. Ele, R. Wamkeue, and A. Melingui. "Fault Detection and Classification of a Photovoltaic Generator Using the BES Optimization Algorithm Associated with SVM." International Journal of Photoenergy 2022 (November 8, 2022): 1–14. http://dx.doi.org/10.1155/2022/6841861.

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In this work, an innovative approach based on the estimation of the photovoltaic generator (GPV) parameters from the Bald Eagle Search (BES) optimization algorithm, associated with a support vector machine (SVM) classification algorithm, allowed to highlight a new tool for the classification of the signatures of shading and moisture PV defects. It recognizes signatures generated by the GPV in healthy and erroneous operation using the optimized parametric vector and classifies defects using the same optimized vector. The technique emphasizes the resilience of parameter estimate in terms of error on all parameters. The classification accuracy is 93%. The residuals between the estimated curve in healthy operation with a minimum error of the order of 10-4 and the one at fault are used as an indicator of faults.

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Filip, Ioan, Florin Dragan, and Iosif Szeidert. "Considerations about Parameters Estimation into a Minimum Variance Control System." Applied Sciences 11, no. 13 (July 2, 2021): 6165. http://dx.doi.org/10.3390/app11136165.

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The starting point to design a minimum variance control law consists in identifying a linearized mathematical model (valid around an operating point) of a nonlinear process, respectively the on-line estimation of the parameters of this model. This paper presents a comparative study regarding the estimation of these parameters for the case when the process operates in open-loop, respectively the process is integrated into a closed-loop system specific to a minimum variance control. The comparison is made both analytically (for the general case) and through a validation study (by simulation) particularized for the case of an induction generator integrated into a wind energy conversion system. The main contribution of this paper consists in proving the fact that, in closed-loop (under the constraints imposed by the control law), the process parameters estimates differ from the real ones identified in open-loop (in free operating mode, without constraints). In addition, as a novelty, the paper demonstrates that, in steady-state, the process gain estimates are identical, both in closed-loop and open-loop, even though they are calculated based on different estimates of these linear model parameters. Thus, based on parameters estimates in closed-loop, the parameter estimator rather allows the estimation of the real process gain, although it does not accurately estimate the real values of the linearized model parameters (correctly estimated only in open-loop).

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30

Duong, Van Minh, Jiri Vesely, Petr Hubacek, Premysl Janu, and Nhat Giang Phan. "Detection and Parameter Estimation Analysis of Binary Shift Keying Signals in High Noise Environments." Sensors 22, no. 9 (April 21, 2022): 3203. http://dx.doi.org/10.3390/s22093203.

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In this paper, a new method for detecting and estimating the parameters of a binary phase shift keying (BPSK) signal, based on a cross-correlation function, is proposed. The proposed method consists of two stages. The first stage is used to detect or estimate a signal carrier frequency, and the second stage is used to estimate its pulse width or symbol rate. Firstly, the proposed method is investigated by use of a simulated BPSK signal in the form of Barker Codes 7, 11, and 13 in the MATLAB environment. Based on the simulation results, the functionality of this method is verified using a real-time BPSK signal generated by an E8267C generator. This is described in the second part of this paper. The experimental test results confirm that the proposed method is able to detect and estimate the parameters of all BPSK signals with SNR≥−21 dB.

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31

S. Hassan, Amal, Saeed E. Hemeda, Sudhansu S. Maiti, and Sukanta Pramanik. "The Generalized Additive Weibull-G Family of Distributions." International Journal of Statistics and Probability 6, no. 5 (August 3, 2017): 65. http://dx.doi.org/10.5539/ijsp.v6n5p65.

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In this paper, we present a new family, depending on additive Weibull random variable as a generator, called the generalized additive Weibull generated-family (GAW-G) of distributions with two extra parameters. The proposed family involves several of the most famous classical distributions as well as the new generalized Weibull-G family which already accomplished by Cordeiro et al. (2015). Four special models are displayed. The expressions for the incomplete and ordinary moments, quantile, order statistics, mean deviations, Lorenz and Benferroni curves are derived. Maximum likelihood method of estimation is employed to obtain the parameter estimates of the family. The simulation study of the new models is conducted. The efficiency and importance of the new generated family is examined through real data sets.

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32

Kang, Seong-Hyun, Seong-Mi Park, Hwa-Chun Lee, and Sung-Jun Park. "Performance Improvement of Synchronous Generator using Exciter Control with Field Coils Parameter Estimation Technique." Journal of the Korean Institute of Illuminating and Electrical Installation Engineers 27, no. 4 (April 30, 2013): 31–40. http://dx.doi.org/10.5207/jieie.2013.27.4.031.

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33

Susperregui, Ana, Josu Jugo, Ibone Lizarraga, and Gerardo Tapia. "Automated control of doubly fed induction generator integrating sensorless parameter estimation and grid synchronisation." IET Renewable Power Generation 8, no. 1 (January 2014): 76–89. http://dx.doi.org/10.1049/iet-rpg.2013.0045.

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34

Farias, Ecyo R. C., Elmer P. T. Cari, Istvan Erlich, and Fekadu Shewarega. "Online Parameter Estimation of a Transient Induction Generator Model Based on the Hybrid Method." IEEE Transactions on Energy Conversion 33, no. 3 (September 2018): 1529–38. http://dx.doi.org/10.1109/tec.2018.2808238.

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35

Burth, M., G. C. Verghese, and M. Velez-Reyes. "Subset selection for improved parameter estimation in on-line identification of a synchronous generator." IEEE Transactions on Power Systems 14, no. 1 (1999): 218–25. http://dx.doi.org/10.1109/59.744536.

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36

Pan, Xueping, Ping Ju, Feng Wu, and Yuqing Jin. "Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator." Frontiers of Mechanical Engineering 12, no. 3 (March 30, 2017): 367–76. http://dx.doi.org/10.1007/s11465-017-0429-y.

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37

Elbatal, I., and Naif Alotaibi. "Modelling to Engineering Data Using a New Class of Continuous Models." Journal of Function Spaces 2021 (November 24, 2021): 1–12. http://dx.doi.org/10.1155/2021/1148618.

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In this paper, a new flexible generator of continuous lifespan models referred to as the Topp-Leone Weibull G (TLWG) family is developed and studied. Several mathematical characteristics have been investigated. The new hazard rate of the new model can be “monotonically increasing,” “monotonically decreasing,” “bathtub,” and “J shape.” The Farlie Gumbel Morgenstern (FGM) and the modified FGM (MFGM) families and Clayton Copula (CCO) are used to describe and display simple type Copula. We discuss the estimation of the model parameters by the maximum likelihood (MLL) estimations. Simulations are carried out to show the consistency and efficiency of parameter estimates, and finally, real data sets are used to demonstrate the flexibility and potential usefulness of the proposed family of algorithms by using the TLW exponential model as example of the new suggested family.

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38

Shi, Hong-Jun, and Xu-Chen Nie. "Composite control for disturbed direct-driven surface-mounted permanent magnet synchronous generator with model prediction strategy." Measurement and Control 54, no. 5-6 (April 29, 2021): 1015–25. http://dx.doi.org/10.1177/00202940211010829.

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In order to obtain the best power in the wind energy conversion system (WECS) of the direct-driven surface-mounted permanent magnet synchronous generator (SPMSG), active disturbance rejection control (ADRC) is introduced to track the motor speed in real time. The control algorithm provides a new design concept and an inherent robust controller component that requires very little system information. Aiming at the problem of system parameter mutation caused by internal factors and external environment changes, an adaptive controller with multi parameter identification is designed, and the disturbance caused by parameter changes is compensated in real time. The model predictive current control (MPC) technology for the sudden change of external environment is designed to accelerate the response speed of the current loop, so as to weaken the estimation of the current disturbance by the active disturbance rejection controller, and make the speed estimation more accurate. Simulation results show that the proposed control strategy is effective and satisfactory.

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39

Niranjan, R. K., A. K. Singh, and C. B. Rama Rao. "High Accuracy Parameter Estimation for Advanced Radar Identification of Electronic Intelligence System." Defence Science Journal 70, no. 3 (April 24, 2020): 278–84. http://dx.doi.org/10.14429/dsj.70.15105.

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Radar identification is one of the vital operations in an electronic intelligence system. The conventional methods based on basic parameters comparison of unique identification of a radar in a cluster of similar radars, is prone to ambiguities. To meet the current tactical requirements of unique identification of a radar, the methodology needs to be based on better feature extraction, even in low SNR conditions. The paper explores a novel technique based on moving autocorrelation for the extraction of intra-pulse and inter-pulse radar parameters. Extensive simulation and empirical studies have been carried out to establish the approach to extend accurate radar parameters in noisy and low SNR conditions. The technique is found to be promising even in field data conditions. The paper describes the methodology, simulation results, FPGA implementation using system generator and resource utilisation summary.

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40

Sommer, Alexander, Ulrich Schwanecke, and Elmar Schoemer. "Real-time Light Estimation and Neural Soft Shadows for AR Indoor Scenarios." Journal of WSCG 31, no. 1-2 (July 2023): 71–79. http://dx.doi.org/10.24132/jwscg.2023.8.

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We present a pipeline for realistic embedding of virtual objects into footage of indoor scenes with focus on real-time AR applications. Our pipeline consists of two main components: A light estimator and a neural soft shadow texture generator. Our light estimation is based on deep neural nets and determines the main light direction, light color, ambient color and an opacity parameter for the shadow texture. Our neural soft shadow method encodes object-based realistic soft shadows as light direction dependent textures in a small MLP. We show that our pipeline can be used to integrate objects into AR scenes in a new level of realism in real-time. Our models are small enough to run on current mobile devices. We achieve runtimes of 9ms for light estimation and 5ms for neural shadows on an iPhone 11 Pro.

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41

Choi, Hyung-Joo, In-Soo Kim, and Heung-Ho Lee. "A Study on Parameter Estimation of the Synchronous Generator System based on the Modified PSO." Transactions of The Korean Institute of Electrical Engineers 64, no. 1 (January 1, 2015): 8–15. http://dx.doi.org/10.5370/kiee.2015.64.1.008.

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42

Kyriakides, E., and G. T. Heydt. "An observer for the estimation of synchronous generator damper currents for use in parameter identification." IEEE Transactions on Energy Conversion 18, no. 1 (March 2003): 175–77. http://dx.doi.org/10.1109/tec.2002.808413.

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43

BERHAUSEN, Sebastian. "Assessment of the accuracy of synchronous generator model parameter estimation based on noisy dynamic waveforms." PRZEGLĄD ELEKTROTECHNICZNY 1, no. 7 (July 5, 2015): 18–22. http://dx.doi.org/10.15199/48.2015.07.06.

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44

Cisneros-González, M., C. Hernandez, R. Morales-Caporal, E. Bonilla-Huerta, and M. A. Arjona. "Parameter Estimation of a Synchronous-Generator Two-Axis Model Based on the Standstill Chirp Test." IEEE Transactions on Energy Conversion 28, no. 1 (March 2013): 44–51. http://dx.doi.org/10.1109/tec.2012.2236433.

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45

Khalili, Ramtin, Hadi Rabieyan, Abolfazl Khodadadi, Behrooz Zaker, Mehdi Karrari, and Shahab Karrari. "Mathematical Modelling and Parameter Estimation of an Industrial Steam Turbine-Generator Based on Operational Data." IFAC-PapersOnLine 51, no. 2 (2018): 214–19. http://dx.doi.org/10.1016/j.ifacol.2018.03.037.

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46

EL-Morshedy, Mahmoud, Fahad Sameer Alshammari, Abhishek Tyagi, Iberahim Elbatal, Yasser S. Hamed, and Mohamed S. Eliwa. "Bayesian and Frequentist Inferences on a Type I Half-Logistic Odd Weibull Generator with Applications in Engineering." Entropy 23, no. 4 (April 10, 2021): 446. http://dx.doi.org/10.3390/e23040446.

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In this article, we have proposed a new generalization of the odd Weibull-G family by consolidating two notable families of distributions. We have derived various mathematical properties of the proposed family, including quantile function, skewness, kurtosis, moments, incomplete moments, mean deviation, Bonferroni and Lorenz curves, probability weighted moments, moments of (reversed) residual lifetime, entropy and order statistics. After producing the general class, two of the corresponding parametric statistical models are outlined. The hazard rate function of the sub-models can take a variety of shapes such as increasing, decreasing, unimodal, and Bathtub shaped, for different values of the parameters. Furthermore, the sub-models of the introduced family are also capable of modelling symmetric and skewed data. The parameter estimation of the special models are discussed by numerous methods, namely, the maximum likelihood, simple least squares, weighted least squares, Cramér-von Mises, and Bayesian estimation. Under the Bayesian framework, we have used informative and non-informative priors to obtain Bayes estimates of unknown parameters with the squared error and generalized entropy loss functions. An extensive Monte Carlo simulation is conducted to assess the effectiveness of these estimation techniques. The applicability of two sub-models of the proposed family is illustrated by means of two real data sets.

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47

Mairesse, François, and Marilyn A. Walker. "Controlling User Perceptions of Linguistic Style: Trainable Generation of Personality Traits." Computational Linguistics 37, no. 3 (September 2011): 455–88. http://dx.doi.org/10.1162/coli_a_00063.

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Recent work in natural language generation has begun to take linguistic variation into account, developing algorithms that are capable of modifying the system's linguistic style based either on the user's linguistic style or other factors, such as personality or politeness. While stylistic control has traditionally relied on handcrafted rules, statistical methods are likely to be needed for generation systems to scale to the production of the large range of variation observed in human dialogues. Previous work on statistical natural language generation (SNLG) has shown that the grammaticality and naturalness of generated utterances can be optimized from data; however these data-driven methods have not been shown to produce stylistic variation that is perceived by humans in the way that the system intended. This paper describes Personage, a highly parameterizable language generator whose parameters are based on psychological findings about the linguistic reflexes of personality. We present a novel SNLG method which uses parameter estimation models trained on personality-annotated data to predict the generation decisions required to convey any combination of scalar values along the five main dimensions of personality. A human evaluation shows that parameter estimation models produce recognizable stylistic variation along multiple dimensions, on a continuous scale, and without the computational cost incurred by overgeneration techniques.

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48

Hayashi, Ryota, Kenji Kashine, Akira Tokuchi, Fumihiro Tamura, Arata Watabe, Takahiro Kudo, Kazumasa Takahashi, et al. "Estimation on Achievable Parameter Regime of Warm Dense Matter Generated by Isochoric Heating Discharge using Intense Pulsed Power Generator." Journal of Physics: Conference Series 688 (March 2016): 012028. http://dx.doi.org/10.1088/1742-6596/688/1/012028.

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49

Angulo, J. R., L. A. Conde, E. Muñoz, J. de la Casa, and J. A. Töfflinger. "PV generator nominal power estimation using a ground sensor and the PVLIB online irradiance database." Journal of Physics: Conference Series 2180, no. 1 (January 1, 2022): 012005. http://dx.doi.org/10.1088/1742-6596/2180/1/012005.

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Abstract The nominal power of a photovoltaic generator is a crucial parameter. For instance, it is a required input parameter for modelling the energy produced by a PV system. Determining the nominal power in-situ requires measuring the irradiance and module temperature. Usually, the irradiance is measured with a sensor placed on the ground and at the plane of the array. The present work first compares the irradiance measurements of a calibrated PV module with the openly available irradiance database PVLIB. Second, it contrasts the daily estimated nominal power values considering both irradiance sources. The results indicate that the irradiance database is suitable to calculate the nominal power.

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50

Esmaeili, Hamid, Fazlollah Lak, and Emrah Altun. "The Ristic-Balakrishnan odd log-logistic family of distributions: Properties and Applications." Statistics, Optimization & Information Computing 8, no. 1 (February 17, 2020): 17–35. http://dx.doi.org/10.19139/soic-2310-5070-715.

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This paper investigates general mathematical properties of a new generator of continuous distributions with two extra parameter called the Ristic-Balakrishnan odd log-logistic family of distributions. We present some special models and investigate the asymptotes. The new density function can be expressed as a linear combination of exponentiated densities based on the same baseline distribution. Explicit expressions for the ordinary and incomplete moments, generating functions and order statistics, which hold for any baseline model, are determined. Further, we discuss the estimation of the model parameters by maximum likelihood and present a simulation study based on maximum likelihood estimation. A regression model based on proposed model was introduced. Finally, three applications to real data were provided to illustrate the potentiality of the family of distributions.

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