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本文在对永磁同步电动机进行电磁分析设计的基础上，采用MATLABISIMULINK仿真工具对控制系统分别采用PID控制、神经网络控
制的情况进行了仿真分析。-Abstract In this paper, permanent magnet synchronous motor for electromagnetic analysis and design, based on the simulation tool used MATLABISIMULINK on the control system were used PID control, neural network control of a simulation analysis.
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Size: 2223104 |
Author: 王大钊 |
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Description: MATLAB风力发电机模型。小电机模型，可以进行相关修改-MATLAB model of wind turbine. Small electric models, can be related to modifications
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Size: 182272 |
Author: haiyan |
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Description: 运用神经网络预测风速，并提出算法，最后作出比较，说明神经网络是预测的良好模型-The use of neural network to predict wind speed, and algorithm, and finally make a comparison on neural network model is a good forecast
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Size: 634880 |
Author: 沈燕 |
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Description: 运用人工神经网络技术预测风速，主要介绍了神经网络的实现方法，以及预测结果的比较-The use of artificial neural network technology forecasting wind speed, mainly the realization of a neural network method and the comparison of predicted results
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Size: 189440 |
Author: 沈燕 |
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Description: 应用ＢＰ神经网络寻求风力发电机组的最优算法-BP neural network to find the optimal algorithm unit wind
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Size: 1024 |
Author: 王惠斌 |
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Description: 析了变速恒频双馈风力发电系统的工作原理。结合风力机特性和双馈发电机特性，说明了变速恒频运行方式下的最优风能捕获策略，并介绍了风力发电系统的滑模变结构控制、自适应控制、鲁棒控制和人工神经网络控制。总结了变速恒频风力发电系统的发展趋势。-Analysis of a Variable Speed Constant Frequency Wind Power Generation System works. Combination of wind turbine characteristics and the characteristics of doubly-fed generator, variable speed constant frequency shows the optimal operating mode to capture wind energy strategy, and introduced wind power generation system with variable structure control, adaptive control, robust control and artificial neural networks control. Summarizes the VSCF wind power system trends.
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Size: 429056 |
Author: wuxing |
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Description: Application of Neural Networks in Wind Power
(Generation) Prediction
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Size: 241664 |
Author: Aditya |
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Description: 利用新陈代谢灰色预测、样本自适应BP 神经网络和时间序列分析分别进行风电功率实时预测和日前预测，并采用熵值取权法确定组合权重，引入自控机制，构建反馈，提出组合预测法和基于时间序列的卡尔曼滤波法。研究结果表明，组合预测模型能减少各预测点较大误差的出现，而卡尔曼滤波能大幅消减原始序列的波动影响。-Use of metabolic gray forecast, sample adaptive BP neural network and time sequence analysis respectively conducted wind electric power real-time forecast and before prediction, and using the entropy take the right method to determine a combination of the right weight, the introduction of self-control mechanism, to build feedback, proposed combination forecasting method and based on the time sequence Kalman filtering method. The research results show that the combination forecasting model can reduce the prediction point error appears, the Kalman filter can significantly abatement fluctuations of the original sequence.
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Size: 1047552 |
Author: 刘行 |
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Description: 运用神经网络与时间序列分析对风电功率进行预测的一个matlab程序。-Using neural network and time series analysis forecast wind power
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Size: 41984 |
Author: 年兴 |
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Description: 基于人工神经网络法的风电功率预测matlab程序，可预测未来几十个小时内的风电功率。-Based on Artificial Neural Network Method wind power prediction matlab program, you can predict the future of dozens of hours of wind power.
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Size: 15360 |
Author: yunhai |
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Description: Pitch angle control in wind turbines above the rated wind speed by multi-layer perceptron and radial basis function neural networks
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Size: 449536 |
Author: ouissam |
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Description: 采用最先进的殖民竞争算法Imperialist competition algorithm优化BP神经网络的初始权值、阈值，进行风电功率预测，带数据和实例，ica为主程序-Using the most advanced colonial competitive algorithm Imperialist competition algorithm to optimize the initial weights of BP neural network, threshold, carry wind power prediction with data and examples, ica-based program
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Size: 17408 |
Author: Victoria |
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Description: 采用粒子群算法PSO优化BP神经网络，进行风电功率预测，含实际数据和案例-Particle swarm optimization PSO BP neural network for wind power prediction, including the actual data and case
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Size: 11264 |
Author: Victoria |
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Description: 含NWP数值天气预报和不含NWP数值天气预报的BP神经网络预测风电功率两种方法进行比较，含数据，实际案例。-With and without NWP NWP Numerical Weather Prediction NWP BP neural network prediction of wind power are two methods were compared with the data, the actual case.
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Size: 17408 |
Author: Victoria |
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Description: 基于最小二乘支持向量机理论,结合某风电场实测风速数据,建立了最小二乘支持向量机风速预测模型。对该风电场的风速进行了提前1h的预测,其预测的平均绝对百分比误差仅为8.55 ,预测效果比较理想。同时将文中的风速预测模型与神经网络理论、支持向量机(support vector machine,SVM)理论建立的风速预测模型进行了比较。仿真结果表明,文中所提模型在预测精度和运算速度上皆优于其他模型。
-Based on least squares support vector machine theory, combined with a wind farm measured wind speed data, the establishment of a wind vector machine forecasting model of least squares support. The velocity of the wind farm were predicted in advance 1h, the mean absolute percentage error of only 8.55 of its forecast, forecast effect is ideal. While the text of the wind speed forecasting models and neural networks, support vector machines (support vector machine, SVM) wind speed prediction models were compared with established theories. Simulation results show that our proposed model on prediction accuracy and computing speed are superior to other models.
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Size: 862208 |
Author: 杰 |
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Description: 这是一篇关于利用改进的粒子群优化算法来构造多层人工神经网络的文章，可用于预测风力和天气。-This is an article on the use of improved particle swarm optimization algorithm to construct a multilayer artificial neural network of the article, can be used to predict the wind and weather.
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Size: 1024000 |
Author: 棉花糖 |
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Description: This paper describes a small wind generation system where neural network principles are applied for wind speed estimation and robust maximum wind power extraction control against potential drift of wind turbine power coefficient curve. The new control system will deliver maximum electric power to a customer with lightweight, high efficiency, and high reliability without mechanical sensors. A turbine directly driven permanent magnet synchronous generator (PMSG) is considered for the proposed small wind generation system in this paper. The new control system has been developed, analyzed and verified by simulation studies. Performance has then been uated in detail. Finally, the proposed method is also applied to a 15 kW variable speed cage induction machine wind generation (CIWG) system and the experimental results are presented. -This paper describes a small wind generation system where neural network principles are applied for wind speed estimation and robust maximum wind power extraction control against potential drift of wind turbine power coefficient curve. The new control system will deliver maximum electric power to a customer with lightweight, high efficiency, and high reliability without mechanical sensors. A turbine directly driven permanent magnet synchronous generator (PMSG) is considered for the proposed small wind generation system in this paper. The new control system has been developed, analyzed and verified by simulation studies. Performance has then been uated in detail. Finally, the proposed method is also applied to a 15 kW variable speed cage induction machine wind generation (CIWG) system and the experimental results are presented.
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Size: 691200 |
Author: shatha |
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Description: BP神经网络预测风电场功率，利用BP神经网络对风电场未来48小时内的功率进行预测-Wind power prediction for wind farm with BP neural network
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Size: 123904 |
Author: Kenny |
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Description: Considering the randomness and volatility of wind, a method based on B-spline neural network optimized by particle swarm
optimization is proposed to predict the short-term wind speed
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Size: 2032640 |
Author: Ephraim Admassu |
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Description: 是使用BP神经网络进行风电功率超短期预测，数据为5分钟一点，预测结果为一次预测4小时15分钟一点。-Ultra- short- term Forecasting Program of Wind Power Based on BP Neural Network
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Size: 1024 |
Author: 杨修 |
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