基于光伏电池输出特性的MPPT算法研究

为了寻找更好的实现光伏发电系统最大功率点跟踪控制方法,基于单个光伏电池的物理特性建立了太阳能光伏电池阵列的Matlab仿真模型,分析了太阳能光伏电池阵列所具有的随着光照强度和温度不同而变化的P-U和I-U非线性特性.基于光伏电池的动态特性,在最大功率点跟踪算法的设计中增加一个电流监测回路,并结合自寻优技术对电导增量法进行改进,提出了一种自适应变步长寻优算法.仿真结果表明,该算法能够快速准确的跟踪最大功率点.     

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。     

基于Newton插值的光伏发电最大功率点跟踪算法研究

通过对光伏电池数学模型的分析与推导,提出了基于Newton二次插值估算最大功率点的算法。该算法相比于La-grange二次插值算法,效率更高,更适合于单片机处理器。最后MATLAB仿真验证该算法的可行性。     

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.     

Maximum power point tracking （MPPT） control of a photovoltaic system based on dual carrier chaotic search

The output power of the photovoltaic (PV) array changes with the change in external environment and load.Therefore,maximum power point tracking (MPPT) technology is needed to maximize the efficiency of...     

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。     

遮挡下光伏电池最大功率跟踪算法的研究

传统的最大功率跟踪算法,都是在光伏组件光照强度均匀的前提下提出的。但是,实际情况中光伏组件会部分被遮挡,P—V曲线产生多个峰值点,使得现有算法跟踪失败。研究部分遮挡情况下,光伏组件的I—V,P—V特性曲线,并提出一种适用于遮挡情况下的最大功率点算法。     

基于模糊神经网络的光伏系统MPPT控制方法

在讨论分析现有光伏电源最大功率点跟踪(MPPT)控制方法的基础上,根据光伏电源系统的特性将补偿模糊神经网络方法应用在最大功率点跟踪控制上,能够根据外界环境变化及时进行调整,具有自学习和自适应能力,使系统始终稳定工作在最大功率点上,避免了使用传统方法时存在的最大功率点附近剧烈震荡的现象.     

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...     

基于光伏阵列模型预测的混合型MPPT研究

阴影条件下光伏阵列的输出特性曲线呈现多峰值特性,现有的在线式MPPT方法的追踪时间长,追踪过程中电压波动大,容易造成阵列失配.为解决这一问题,提出了一种基于模型预测的混合型MPPT算法,将初步寻优过程放入软件中处理,通过“检测—预测—再寻优”的过程完成多峰值情况下的MPPT.建模仿真证明:与现有MPPT方法相比,基于模型预测的混合型MPPT算法能够有效缩短系统的寻优时间,且电压波动更小,适用于阴影条件下光伏阵列的最大功率追踪.     

应用于光储系统中的改进型扰动观察MPPT算法

本文提出了一种改进的步长可变、稳态时无振荡的扰动观察MPPT算法,该改进算法在保持基本的扰动观察法简单以及便于实现特点的同时,还能停止稳态振荡并具备良好的追踪速度.该算法首先通过变步长实现快速跟踪最大功率点,当确定到达稳态之后,停止人工扰动,实现无振荡稳定输出功率,从而减少因振荡造成的功率损耗,提高了整个系统的效率.当...     

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。     

基于粒子群优化的光伏系统MPPT控制方法

局部遮阴条件下光伏阵列P-V特性引起的多个极值点使常规的最大功率点跟踪(MPPT)算法失效。针对上述问题,提出一种基于粒子群优化算法的控制方法,以解决局部遮阴下的最大功率跟踪问题。实验结果显示,光伏模板的输出电压被稳定地控制在最大功率点附近,证明算法是有效的。     

基于PSIM的光伏矩阵MPPT通用模型的设计与应用

基于光伏矩阵的物理特性,在PSIM仿真环境下,设计带有最大功率跟踪技术(MPPT)仿真算法的光伏矩阵仿真模型,应用于实际的单相光伏并网系统。测试数据表明,仿真模型可以模拟任意参数的光伏阵列,跟踪光照强度、环境温度的变化,为光伏发电系统动态仿真提供了良好的设计平台。     

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.     

基于自适应线性调节抗干扰PSO的光伏群体MPPT控制

光伏发电已成为新能源发电的主要研究方向,但当外界环境发生突变或由于遮挡使光伏阵列出现阴影时,传统的最大功率点跟踪(MPPT)算法会出现误判或因陷入局部最大功率点等问题而失效。针对这些问题,提出了一种自适应线性调节的粒子群(PSO)算法,并采用一个MPPT控制器同时实现多支路光伏阵列群体MPPT控制。最后,通过仿真验证所提控制策略的有效性。结果表明,自适应线性调节PSO群控方法振荡小,可实时精准跟踪最大功率点,控制电路较为简单,降低系统控制成本。     

Hybrid and Adaptive Cryptographic-based secure authentication approach in IoT based applications using hybrid encryption

The Internet of Things (IoT) in communication networks has gained major interest in recent decades. Accordingly, secure authentication of such individuals results in a major challenge due to the weakness in the authentication process. Hence, an effective Hybrid and Adaptive Cryptographic (HAC)-based secure authentication framework is designed in this research to perform an authentication process in IoT. The proposed approach uses cryptographic operations, like exclusive-or (Ex-or) operation, a hashing function, and hybrid encryption to accomplish the authentication process. However, the hybrid encryption function is carried out in two different ways: one depends on Advanced Encryption Standard (AES) as well as Elliptic Curve Cryptography (ECC), while other is based on Rivest Shamir Adleman (RSA) and AES. With a hybrid encryption function, security flaws can be effectively dealt through the cryptographic system. Moreover, the proposed approach provides high robustness with low complexity. The proposed HAC-based secure authentication approach obtained a minimum communication cost of 0.017sec, less computation time of 0.060sec, and minimum memory usage of 2.502MB, respectively.     

A hybrid intelligent GMPPT algorithm for partial shading PV system

Maximum power extraction for PV systems under partial shading conditions (PSCs) relies on the optimal global maximum power point tracking (GMPPT) method used. This paper proposes a novel maximum power point tracking (MPPT) control method for PV system with reduced steady-state oscillation based on improved particle swarm optimization (PSO) algorithm and variable step perturb and observe (P&O) method. Firstly, the grouping idea of shuffled frog leaping algorithm (SFLA) is introduced in the basic PSO algorithm (PSO–SFLA), ensuring the differences among particles and the searching of global extremum. Furthermore, adaptive speed factor is introduced into the improved PSO to improve the convergence of the PSO–SFLA under PSCs. And then, the variable step P&O (VSP&O) method is used to track the maximum power point (MPP) accurately with the change of environment. Finally, the superiority of the proposed method over the conventional P&O method and the standard PSO method in terms of tracking speed and steady-state oscillations is highlighted by simulation results under fast variable PSCs.     

混合动态系统有界性定理及应用

从连续系统的角度出发，提出并证明了混合动态系统的有界性定理，并以一类具体的数字反馈采样控制系统为例，详细阐述了有界性定理的具体应用，最终得到系统在其状态空间内有界的充分条件。