Fuzzy logic based intelligent control of a variable speed cagemachine wind generation system

The paper describes a variable speed wind generation system where fuzzy logic principles are used for efficiency optimization and performance enhancement control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which pumps power to a utility grid or can supply to an autonomous system. The generation system has fuzzy logic control with vector control in the inner loops. A fuzzy controller tracks the generator speed with the wind velocity to extract the maximum power. A second fuzzy controller programs the machine flux for light load efficiency improvement, and a third fuzzy controller gives robust speed control against wind gust and turbine oscillatory torque. The complete control system has been developed, analyzed, and validated by simulation study. Performances have then been evaluated in detail     

风力机功率控制器的研究

MPPT（Maxmin Power Point Tracking）控制方法在风力机功率控制器中处于核心地位,其控制策略的优劣影响整个系统的输出特性。本文构建了风力发电系统仿真模型,深入研究了风机输出特性,在此基础上对以往MPPT控制方法的改进提出自适应变步长控制策略,使其能够应用于小型风力发电系统中。     

风力发电机转速控制系统的建模与仿真

针对风力发电机非线性、随机性、扰动大等特点,设计基于带动量项的粒子群优化的支持向量机的风力发电机转速控制建模的新方法。利用支持向量机对小样本、高维度、非线性特性的映射能力,将风电系统的采样数据映射到高维的特征空间进行建模。支持向量机惩罚因子C和核参数σ的选择对建模效果影响较大,经验试凑的方法难以获得较好的参数,引入粒子群算法进行参数寻优。为了克服传统粒子群算法易陷入局部最优且收敛速度慢的缺陷,提出带动量项的改进粒子群算法寻优。以采集的风速、风力发电机转矩、桨距角作为输入信号,发电机转速数据作为输出信号,在Matlab环境中进行建模。实验结果表明,与传统算法相比,采用该方法的模型在准确性和收敛速度方面得到较大改善。     

小型风机最大功率点快速跟踪策略的仿真研究

风力发电系统的输出功率受外界因数和风速的影响。为了提高小型风机发电机组的转换效率,文中采用一种最大功率优化跟踪算法。以变步长来跟踪风速变化,当功率变化小于一个阈值时停止搜索,来实现最大功率收索的快速性和稳定性。以带齿轮箱6 kW的鼠笼异步式风力发电并网为基础,通过Matlab/Simulink软件仿真结果证实此种方法与定步长爬山法相比,能够达到快速跟踪最大功率点和避免达到最大功率点附近的时候频繁波动。     

A new algorithm for rapid tracking of approximate maximum power point in photovoltaic systems

This paper presents a new algorithm for tracking maximum power point in photovoltaic systems. This is a fast tracking algorithm, where an initial approximation of maximum power point is (MPP) quickly achieved using a variable step-size. Subsequently, the exact maximum power point can be targeted using any conventional method like the hill-climbing or incremental conductance method. Thus, the drawback of a fixed small step-size over the entire tracking range is removed, resulting in reduced number of iterations and much faster tracking compared to conventional methods. The strength of the algorithm comes from the fact that instead of tracking power, which does not have a one-to-one relationship with duty cycle, it tracks an intermediate variable /spl beta/, which has a monotonically increasing, one-to-one relationship. The algorithm has been verified on a photovoltaic system modeled in Matlab-Simulink software. The algorithm significantly improves the efficiency during the tracking phase as compared to a conventional algorithm. It is especially suitable for fast changing environmental conditions. The proposed algorithm can be implemented on any fast controller such as the digital signal processor. All the details of this study are presented.     

基于向后搜索的变速变加速算法研究与应用

在实际数控加工中,为实现数控系统的高速高精度加工性能,在对加工曲线进行前瞻处理并进行四次位移曲线规划的基础上,针对实际生产中的复杂加工提出了一种辨识复杂加工轨迹段特征的向后搜索算法,且在此基础上针对轨迹的不同特征采用变速变加速四次位移曲线算法,改变了四次曲线位移算法加速度的单一性,在加工中更加灵活,实现加工精度和加工速度的很好平衡,大大提高机床的性价比,满足加工时的高速高精度要求。     

永磁同步电机(PMSM)调速系统的智能控制算法研究

为了解决PMSM速度控制问题,文中提出了一种模糊自整定PI的控制方案,并用MATLAB对系统进行了建模仿真验证。仿真实验结果表明,该种新型控制算法与传统的PI控制相比较,具有很强的适应性,鲁棒性和抗干扰性。能快速跟踪设定速度,并且在改变负载时,能快速恢复到额定状态。     

光伏系统最大功率跟踪技术的研究

基于传统的滑膜控制算法,本文采用一种改进的指数趋近律方法,来实现最大功率跟踪,使得控制输出变量可以为连续变量,再通过调制器得到开关管的控制信号,实现控制,以弥补传统方法的参数灵敏度、适用范围受限制等方面的缺陷。通过对传统算法和改进算法的仿真比较,得出了改进的滑模控制法能够快速地跟踪最大功率点,振荡幅度较小,鲁棒性较好。     

Experience with bicoherence of electrical power for conditionmonitoring of wind turbine blades

The authors explore the application of the normalised bispectrum or bicoherence to the problem of condition monitoring of wind turbine blades. Background information is provided on this type of condition monitoring, how it differs from more conventional condition monitoring of turbo machinery, and the motivation for selecting bicoherence. Bicoherence is defined and compared with the power spectral density. Complications in collecting suitable data, and estimating the bicoherence from that data are investigated; including the requirements of very long stationary data sets for consistent estimates, and computational difficulties in handling such large data sets. Bicoherence is then applied to electrical power output data obtained from a 45 kW wind turbine. The turbine is operated in three configurations to represent normal and fault conditions. A blade with less flapwise stiffness but identical outer dimensions to the matched set of blades was fitted to simulate a damaged blade. Comparison of the results from the power spectral density and bicoherence indicates how the bicoherence might be employed for condition monitoring purposes. Slices of the bicoherence with one frequency fixed at the rate of rotation show clear differences between the configurations and substantially reduce the computational effort required to calculate the estimate     

An efficient dynamic traffic light scheduling algorithm considering emergency vehicles for intelligent transportation systems

Traffic lights have been installed throughout road networks to control competing traffic flows at road intersections. These traffic lights are primarily intended to enhance vehicle safety while crossing road intersections, by scheduling conflicting traffic flows. However, traffic lights decrease vehicles’ efficiency over road networks. This reduction occurs because vehicles must wait for the green phase of the traffic light to pass through the intersection. The reduction in traffic efficiency becomes more severe in the presence of emergency vehicles. Emergency vehicles always take priority over all other vehicles when proceeding through any signalized road intersection, even during the red phase of the traffic light. Inexperienced or careless drivers may cause an accident if they take inappropriate action during these scenarios. In this paper, we aim to design a dynamic and efficient traffic light scheduling algorithm that adjusts the best green phase time of each traffic flow, based on the real-time traffic distribution around the signalized road intersection. This proposed algorithm has also considered the presence of emergency vehicles, allowing them to pass through the signalized intersection as soon as possible. The phases of each traffic light are set to allow any emergency vehicle approaching the signalized intersection to pass smoothly. Furthermore, scenarios in which multiple emergency vehicles approach the signalized intersection have been investigated to select the most efficient and suitable schedule. Finally, an extensive set of experiments have been utilized to evaluate the performance of the proposed algorithm.     

Iterative maximum entropy power spectrum estimation for multirate systems

In multirate systems, observations are generally insufficient to determine the power spectrum of the input signal. In this paper, we reformulate the problem using a novel matrix notation and the discrete entropy function. Then we present an iterative maximum entropy power spectrum estimation algorithm for the solution of this problem. Contrary to the existing solutions, the new algorithm is computationally efficient since it is based on fast Fourier transform (FFT) and simple matrix calculations. Furthermore, simulation results show that the new algorithm converges to the maximum entropy solution and can be successfully used in multirate statistical data estimation.     

MIMO-OFDM系统中一种高效的分子带自适应比特功率分配算法

自适应比特、功率分配(ABPA)可根据各子载波在频率选择性衰落信道中不同的瞬时增益,动态地分配数据比特和发射功率,从而达到优化系统性能,提高频率效率的目的。针对MIMO-OFDM系统中ABPA算法计算复杂度高的问题,本文提出了一种高效分子带ABPA算法,该算法采用新颖的分簇随机选取的方式进行子带划分及等效,将以子载波为分配单元的Fischer算法扩展为以子带为分配单元的ABPA算法,并对此算法进行改进,使其可在一次迭代过程中剔除多个比特数小于等于0的不可用簇。仿真结果表明,该算法能够在保持系统性能不变的前提下,提高筛选效率,同时可通过选择不同的簇宽度,进一步灵活地调整算法的复杂度,使其在性能与计算量之间取得良好的折衷。     

大数模幂乘算法的快速实现

大素数的选取是构造RSA密钥的关键 ,在素数的产生及测试是RSA公钥系统中的一个重要研究课题。描述了公钥密码体制中DSA、RSA等数据加密算法的原理及加密、解密过程 ,分析了各种算法的性能和适用的场合 ,针对上述算法的计算量巨大的问题 ,给出了实现数据加密较好的方法。理论和实验表明 ,该算法用于实现RSA算法 ,新算法的效率有明显的提高     

A fast bit-loading algorithm for high speed power line communications

Adaptive bit-loading is a key technology in high speed power line communications with the Orthogonal Frequency Division Multiplexing (OFDM) modulation technology. According to the real situation of the transmitting power spectrum limited in high speed power line communications, this paper explored the adaptive bit loading algorithm to maximize transmission bit number when transmitting power spectral density and bit error rate are not exceed upper limit. With the characteristics of the power line channel, first of all, it obtains the optimal bit loading algorithm, and then provides the improved algorithm to reduce the computational complexity. Based on the analysis and simulation, it offers a non-iterative bit allocation algorithm, and finally the simulation shows that this new algorithm can greatly reduce the computational complexity, and the actual bit allocation results close to optimal.     

分组空时块码系统中的排序最大信噪比检测算法

提出并比较了应用于分组空时块码（G—STBC）系统中两种不同信道模型的排序最大信噪比（MaxSNR）检测算法。该系统在发端对发射天线分组，每组进行独立的空时块码编码；在收端应用排序最大信噪比算法进行检测。由于空时块码提供了额外的时域约束，所以可以利用这个约束对信道模型进行变换，得到一个等效信道模型，然后再使用排序MaxSNR检测；当然也可以直接利用原有的信道模型，即非等效信道模型进行检测。仿真结果表明：当接收天线数不少于发射天线数的一半时，采用等效信道模型下的排序MaxSNR算法，系统的误码曲线就能保持陡降性；并且在收发天线数相同时，其性能总是优于非等效信道模型。     

基于OIV算法的风电机数据预处理方法探究

针对风电机组各部件性能分析过程繁琐低效、预测精度不高以及经济效益不足的异常风电机组状态问题,文章提出一种用于后期预测的数据预处理方法,结合基本的网络工具进行实验,提高了风电机组中发电机定子温度预测的准确性。     

Neural networks for wind turbine supervision

Wind energy converters are generally working under very variable conditions which require high maintenance costs. Therefore, it is important to supervise their behavior in order to provide an accurate and reliable forecasts of the energy production. The aim of this paper is to demonstrate a monitoring system for wind turbines which will result in a cost reduction of maintenance and an improvement of the cost/benefit ratio of wind energy. As it is very difficult to define the faulty behavior, we propose to use autoassociators networks in order to process the information which is available under operating conditions. These networks are used to detect any modification of the behaviour of the wind converter. This system complements the standard monitoring equipment of the wind energy converters to yield detailed on-line information on the state of the machines.     

An exact maximum likelihood registration algorithm for data fusion

Data fusion is a process dealing with the association, correlation, and combination of data and information from multiple sources to achieve refined position and identity estimates. We consider the registration problem, which is a prerequisite process of a data fusion system to accurately estimate and correct systematic errors. An exact maximum likelihood (EML) algorithm for registration is presented. The algorithm is implemented using a recursive two-step optimization that involves a modified Gauss-Newton procedure to ensure fast convergence. Statistical performance of the algorithm is also investigated, including its consistency and efficiency discussions. In particular, the explicit formulas for both the asymptotic covariance and the Cramer-Rao bound (CRB) are derived. Finally, simulated and real-life multiple radar data are used to evaluate the performance of the proposed algorithm     

An LMS style variable tap-length algorithm for structure adaptation

Searching for the optimum tap-length that best balances the complexity and steady-state performance of an adaptive filter has attracted attention recently. Among existing algorithms that can be found in the literature, two of which, namely the segmented filter (SF) and gradient descent (GD) algorithms, are of particular interest as they can search for the optimum tap-length quickly. In this paper, at first, we carefully compare the SF and GD algorithms and show that the two algorithms are equivalent in performance under some constraints, but each has advantages/disadvantages relative to the other. Then, we propose an improved variable tap-length algorithm using the concept of the pseudo fractional tap-length (FT). Updating the tap-length with instantaneous errors in a style similar to that used in the stochastic gradient [or least mean squares (LMS)] algorithm, the proposed FT algorithm not only retains the advantages from both the SF and the GD algorithms but also has significantly less complexity than existing algorithms. Both performance analysis and numerical simulations are given to verify the new proposed algorithm.     

考虑风电并网的电力系统时滞稳定性分析

文中提出一种考虑风电并网的电力系统随机时滞稳定性分析方法。以双馈异步电机为例,首先,建立适用于时滞稳定分析的双馈风机降阶电磁模型,同时选取风机机械功率作为随机激励,用随机过程对其进行建模,进而建立用随机微分方程描述的系统状态方程,克服了常微分方程无法从本质上描述随机过程的缺点。利用Wiener过程建立随机风功率的机械系统模型,在此基础上,推导基于微分方程(SDE)描述的互联系统状态方程,然后,构造考虑风功率随机性的Lyapunov-Krasovskii泛函,结合自由权方法,同时,借助伊藤微分公式求解泛函的弱无穷小生成算子,并据此得到随机激励下互联系统随机时滞稳定性判据。最后通过数值仿真验证了文章所提方法的有效性。