FPGA based implementation of MPPT algorithms for photovoltaic system under partial shading conditions

In Photovoltaic (PV) systems, Maximum power point (MPPT) tracking has emerged as a crucial element of that guarantees PV arrays maximum power output in all environmental conditions. Almost regularly there is a shadowing effect that occurs on the PV arrays. This is done either in a manner that is partial or almost complete coverage through trees, poles, towers, building nearby or even passing clouds. Almost often there is a shadowing impact that happens on the PV arrays. This is often done either in a manner that is partial or almost complete coverage through trees, poles, towers, building nearby or even passing clouds. Under these conditions, multiple peaks occurs that increase the complexity of the PV characteristics which in turn results in difficulty in tracking Global Peak (GP). Therefore the proposed Periodic Power Hunt (PPH) MMPT technique permits in overcoming those problems which include lower observation efficiency under Partial Shading Conditions (PSCs) like in perturbing and observe (P&O) MPPT. The proposed PPH scheme PV array under PSCs shows various completed peaks. The tracking performance is also compared with P&O-MPPT algorithms. The control technique doesn't have any effect of explicit operating environments and results in better performance than ancient strategies with solar power harvesting. The FPGA based experimental implementation of proposed PPH MPPT solution in such a technique that does not involve particular measurement of open circuit voltage or short circuit current.     

一种可应用于小型光伏的MPPT技术

提出了一种基于FOCV方法应用在小型光伏系统中的新型太阳能电池MPPT技术。首先．将太阳能电池阵列改变为全串联、全并联或串并混联的组合方式,相同的环境下,这些阵列在理论上拥有相同的最大输出功率,但需要不同的负载与阻抗相匹配;其次,许多拥有不同阻值的负载电阻可以被选择连接到太阳能电池阵列中,使太阳能电池的输出功率最大化;最后,使用MCU测量每种模式的电压并使用FOCV方法来确定最大的功率状态。     

基于DSP的光伏并网系统MPPT算法研究

介绍了以DSP为主控芯片的光伏并网系统,它能跟踪光伏阵列最大输出功率点,实现光伏阵列和负载优化匹配,使负载获得最大功率。在光伏阵列输出功率最大为跟踪目标的定步长MPPT一阶差分算法的基础上,采用以使负载获得最大功率为跟踪目标的变步长寻优MPPT算法,能够更好地实现最大功率点的跟踪。实验结果表明:该系统能够快速准确地跟踪太阳能电池最大功率点,并自动同步跟踪电网频率和相位,实现并网电流的正弦波形以便与电网电压同频同相馈入电网,提高了系统逆变效率和可靠性。     

A new MPPT controller based on the Ant colony optimization algorithm for Photovoltaic systems under partial shading conditions

The Maximum Power Point Tracking controller (MPPT) is a key element in Photovoltaic systems (PV). It is used to maintain the PV operating point at its maximum under different temperatures and sunlight irradiations. The goal of a MPPT controller is to satisfy the following performances criteria: accuracy, precision, speed, robustness and handling the partial shading problem when climatic changes variations occur. To achieve this goal, several techniques have been proposed ranging from conventional methods to artificial intelligence and bio-inspired methods. Each technique has its own advantage and disadvantage. In this context, we propose in this paper, a new Bio- inspired MPPT controller based on the Ant colony Optimization algorithm with a New Pheromone Updating strategy (ACO_NPU MPPT) that saves the computation time and performs an excellent tracking capability with high accuracy, zero oscillations and high robustness. First, the different steps of the design of the proposed ACO_NPU MPPT controller are developed. Then, several tests are performed under standard conditions for the selection of the appropriate ACO_NPU parameters (number of ants, coefficients of evaporation, archive size, etc.). To evaluate the performances of the obtained ACO_NPU MPPT, in terms of its tracking speed, accuracy, stability and robustness, tests are carried out under slow and rapid variations of weather conditions (Irradiance and Temperature) and under different partial shading patterns. Moreover, to demonstrate the superiority and robustness of the proposed ACO_NPU_MPPT controller, the obtained results are analyzed and compared with others obtained from the Conventional Methods (P&O_MPPT) and the Soft Computing Methods with Artificial intelligence (ANN_MPPT, FLC_MPPT, ANFIS_MPPT, FL_GA_MPPT) and with the Bio Inspired methods (PSO) and (ACO) from the literature. The obtained results show that the proposed ACO_NPU MPPT controller gives the best performances under variables atmospheric conditions. In addition, it can easily track the global maximum power point (GMPP) under partial shading conditions.     

基于模糊控制MPPT的单相光伏并网发电系统

采用模糊控制算法实现光伏阵列最大功率点跟踪,利用软件锁相技术完成逆变器输出电流与电网电压的频率和相位同步。实验结果表明,该系统的设计能满足并网要求,而且模糊控制可有效消除最大功率点振荡现象。     

基于无线传感器网络的光伏系统MPPT应用研究

光伏电池输出的功率随外界环境条件的变化而变化,通常采用最大功率点跟踪技术以获得最大功率输出。结合无线传感器网络(WSNs)节点的工作方式与光伏系统的特点,提出了一种基于WSNs的光伏系统最大功率点跟踪技术。针对开路电压法的不足,利用WSNs节点的测温工作方式来进行温度补偿。当系统工作在最大功率点附近时,引入阻抗匹配算法,可有效消减光伏输出功率在最大功率点处的振荡现象,从而提高系统效率。仿真结果验证了该方法的可行性和有效性。     

物流云服务下基于改进蝙蝠算法的任务调度

针对物流云服务模式中调度任务多、信息量大、需求广的特点,提出了一种改进蝙蝠算法求解物流云服务调度问题的方案,其优化目标为最小化调度时间和最大化资源利用率.根据设计的算法流程,首先基于工件升序排列(ranked order value,ROV)规则对蝙蝠个体进行重新编码;然后调整初始化数据范围来减少分配任务超载和资源闲置现象,并在迭代过程中增加约束条件来均衡任务量,最终实现了资源与任务的智能调度.通过和遗传、粒子群以及基本蝙蝠算法的对比分析,体现了改进算法的优越性.最后利用Witness对方案进行仿真,证明了改进蝙蝠算法在解决物流云服务任务调度中的有效性,同时扩展了蝙蝠算法的应用领域.     

基于改进PSO算法的光伏发电系统MPPT控制策略

光伏发电系统运行在局部阴影条件下,其P-V曲线呈现多个峰值,为了保证光伏发电系统能够工作在最大功率点下,提出一种改进粒子群优化(PSO)算法的最大功率点跟踪(MPPT)的控制策略.改进算法采用非线性自适应的学习因子和加速因子同时采用随机惯性权重.仿真实验和真实实验验证所提出的算法在光伏发电系统的MPPT控制中具有较快的...     

An automatic acoustic bat identification system based on the audible spectrum

Nowadays the task of monitoring bat species is a very difficult task because of several factors. The main ones are the difficulty of creating databases automatically and the particularities of the vocalizations of bats. For this reason, it is common to extract bat calls manually from a recording and treat them individually. We propose a new form of identification and labeling process based on adapting bat calls to the audible spectrum and significantly reducing the noise of its spectrogram. This process can be performed automatically from a recording made in a natural area. Our database consists of 189 h of recordings obtained in various natural areas in Costa Rica. 50 bats calls of 7 different classes are extracted from this database. We have obtained an average error of 2.7% and 3 of the 7 classes have an error below 1%.     

Modified Particle Swarm Optimization technique based Maximum Power Point Tracking for uniform and under partial shading condition

Generation of electricity from solar energy has gained worldwide acceptance due to its abundant availability and eco-friendly nature. Even though the power generated from solar looks to be attractive; its availability is subjected to variation owing to many factors such as change in irradiation, temperature, shadow etc. Hence, extraction of maximum power from solar PV using Maximum Power Point Tracking (MPPT) method was the subject of study in the recent past. Among many methods proposed, Hill Climbing and Incremental Conductance MPPT methods were popular in reaching Maximum Power under constant irradiation. However, these methods show large steady state oscillations around MPP and poor dynamic performance when subjected to change in environmental conditions. On the other hand, bio-inspired algorithms showed excellent characteristics when dealing with non-linear, non-differentiable and stochastic optimization problems without involving excessive mathematical computations. Hence, in this paper an attempt is made by applying modifications to Particle Swarm Optimization technique, with emphasis on initial value selection, for Maximum Power Point Tracking. The key features of this method include ability to track the global peak power accurately under change in environmental condition with almost zero steady state oscillations, faster dynamic response and easy implementation. Systematic evaluation has been carried out for different partial shading conditions and finally the results obtained are compared with existing methods. In addition, simulations results are validated via built-in hardware prototype.     

基于三维空间均匀矩形阵列的MIMO系统研究

主要研究MIMO天线阵列系统性能,包括MIMO空间时间相关性和天线阵列配置。推导了三维多径信道中均匀矩形阵列在多种角能量分布下空间衰落相关性公式。采用多重信号分类算法对MIMO系统波达信号方向进行空间谱估计,推导了多种天线阵列空间谱通用公式。通过计算机模拟仿真验证分析结果,仿真结果表明方位角扩展是天线间空间衰落相关性的主要决定因素,在低方位角扩展时,俯仰角扩展对性能影响也是明显的。结果表明在同样的参数情况下估计MIMO系统空间谱时,采用三维均匀矩形阵列是有优势的。     

The performance of multiwavelets based OFDM system under different channel conditions

In wireless communication reception, the reliability of orthogonal frequency division multiplexing (OFDM) is limited because of the time-varying nature of the channel. This causes inter-carrier interference (ICI) and increases inaccuracies in channel tracking. This can effectively be avoided at the cost of power loss and bandwidth expansion by inserting a cyclic prefix guard interval before each block of parallel data symbols. However, this guard interval decreases the spectral efficiency of the OFDM system as the corresponding amount. Recently, it was found that based on Haar-orthonormal wavelets, discrete wavelet-based OFDM (DWT-OFDM) is capable of reducing the inter symbol interference (ISI) and ICI, which are caused by the loss in orthogonality between the carriers. DWT-OFDM can also support much higher spectrum efficiency than discrete Fourier-based OFDM (DFT-OFDM). In this paper the DFT-OFDM is replaced by Multiwavelets OFDM (DMWT-OFDM) in order to further reduce the level of interference and increase spectral efficiency. It is found that proposed Multiwavelet design achieves much lower bit error rates, increases signal to noise power ratio (SNR), and can be used as an alternative to the conventional OFDM. The proposed OFDM system was modeled tested, and its performance was found under different channel conditions.     

Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions

Artificial bee colony (ABC) algorithm has several characteristics that make it more attractive than other bio-inspired methods. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a novel artificial bee colony based maximum power point tracking algorithm (MPPT) is proposed. The developed algorithm, does not allow only overcoming the common drawback of the conventional MPPT methods, but it gives a simple and a robust MPPT scheme. A co-simulation methodology, combining Matlab/Simulink™ and Cadence/Pspice™, is used to verify the effectiveness of the proposed method and compare its performance, under dynamic weather conditions, with that of the Particle Swarm Optimization (PSO) based MPPT algorithm. Moreover, a laboratory setup has been realized and used to experimentally validate the proposed ABC-based MPPT algorithm. Simulation and experimental results have shown the satisfactory performance of the proposed approach.     

基于构件技术的嵌入式GUI系统

随着嵌入式设备硬件条件的提高,嵌入式系统对GUI的需求越来越高,嵌入式GUI的地位至关重要。CAR构件技术是具有中国自主知识产权的“和欣”操作系统的关键技术。基于CAR(CarefreeApplicationRun-Time)构件技术的嵌入式GUI系统具有灵活性和高效性特点。该系统采用了模块化CAR构件技术,和用来处理输入输出事件的独特的回调事件机制,能够很好地实现人机交互界面。     

基于改进黏菌优化算法的光伏多峰MPPT控制策略

当光伏阵列在局部阴影遮挡条件下时,传统最大功率点追踪控制策略易陷入局部最优解,降低光伏系统发电效率.为解决该问题,本文提出了一种基于改进黏菌优化算法的最大功率点追踪策略.该策略在黏菌优化算法的基础上,基于光伏阵列特性提出了新的边界条件,减小超出边界黏菌的迭代次数,增大算法的收敛速度;同时,引入了L■vy飞行策略优化其收敛准则,提升算法的随机搜索能力,进一步提高了算法的追踪速度.仿真和实验结果表明,该策略拥有较高的追踪速度和追踪精度,在各个光照条件下均能快速追踪到最大功率点,有效提高光伏系统的发电效率.     

基于改进电导增量法MPPT控制仿真研究

基于光伏电池典型单二极管等效电路,建立了数学模型。在M ATLAB仿真环境下,开发了可以模拟任意光照强度、环境温度和电池参数的光伏电池通用仿真模型,在基于改进电导增量法的MPPT控制方法的基础上搭建了独立光伏系统,并在环境因素和负载变化的不同条件下进行了仿真,检验了最大功率跟踪控制策略的效果以及系统独立供电的合理性与可行性。     

基于均匀分簇的正三角模型节点轮换路由算法

针对节点随机分布的无线传感器网络能耗问题,提出一种在均匀分簇后采用正三角模型对簇内节点进行调度的低能耗路由算法。该算法首先计算网络内节点总能耗最小时的分簇数目,再由Sink节点选择相应数目的剩余能量最大、地理位置最优的节点为簇首,完成均匀分簇。簇内节点采用正三角模型和节点覆盖概率进行工作节点的选择。仿真结果表明,该路由算法可以均衡节点能耗,延长网络工作轮数,降低网络延迟,并体现出了更优的网络鲁棒性。     

基于蝙蝠算法的电力恢复机组选择多目标优化

目前电力系统恢复机组选择的优化目标通常单一地追求发电量最大,忽视系统的安全稳定运行、机组重要性与恢复机组在系统的全局分布情况。在实际情况下尚不足以保证电力系统恢复的可靠与高效地进行。通过建立联合考虑电压相关安全指标、机组重要性与最大发电量的目标函数,将优化问题抽象为一个多目标组合优化背包问题。通过一定约束条件进行机组预选之后,由蝙蝠算法求解出优化模型的Pareto最优解集。通过算例进行仿真建模与其他算法进行多方面对比后,验证说明了蝙蝠算法在解决此多目标决策问题上的合理性与有效性。     

改进型内模控制系统的稳定性与鲁棒跟踪条件

为了改善系统的响应性能或解决常规内模控制不能用于不稳定对象的问题,通常在常规内模控制结构中增设一个反馈环节,但这种改进型内模控制系统的性能分析尚缺乏系统的、令人满意的结果．为此,利用基于传递函数互质分解的频域理论,系统地分析了这种改进型内模控制系统的稳定性和稳态性能,得到了保证系统内稳定和鲁棒跟踪的一般性结论,并且无论控制对象稳定与否、系统连续或离散,该结论都适用．     

基于视频技术的嵌入式交通信息采集系统

简要分析了交通信息采集技术的发展状况,并结合当前智能交通系统的应用需求,设计并实现了一种基于高性价比DSP硬件平台的嵌入式交通信息采集系统。本系统是一种基于视频图像分析和模式识别技术,对交通信息进行实时采集和分析的嵌入式集成系统,具有很好的稳定性和实时性。