基于模型预测控制的MPPT控制策略

提出一种新的基于模型预测控制(MPC)的最大功率点跟踪(MPPT)优化算法。该目标控制算法把基于电流的改进型电导增量法与模型预测控制算法相结合,完成对光伏阵列最大输出功率的快速跟踪。在算法执行过程中,通过建立系统性能指标函数,评价与估算出未来控制变量的动作,从而决定P-U曲线的跟踪方向。仿真结果表明:该控制策略有效地解决了传统电导增量法在外界环境激烈变化时所产生的误判现象,在提高系统稳定性的同时,大大地减少了最大功率点跟踪时间和系统的能量损耗。     

基于粒子群优化和爬山法的MPPT算法

针对光伏发电系统在部分遮蔽情况下所具有的高度非线性、时变不确定性和多个局部功率峰值的特点,提出一种基于粒子群优化和爬山法的MPPT算法,粒子群优化用来快速定位近似最大功率点,爬山法可根据实际状况精确化最大功率点,克服太阳电池工程用数学模型与实际输出偏差或微小扰动而导致的功率损失。建立Matlab仿真模型,仿真结果表明在系统被部分遮蔽的情况下该方法具有迅速精确的跟踪能力。     

光伏电池最大功率点跟踪控制方法的对比研究及改进

光伏发电系统中光伏电池的输出特性具有唯一的最大功率点(MPP),需要对光伏电池的最大功率点进行跟踪(MPPT)。文中分析了几种常见的最大功率点跟踪控制方法对比分析了它们的优缺点。针对MPPT控制方法中存在的启动特性较差、跟踪过程不稳定、精度不高等特点,采用一种改进爬山法,该法以恒定电压法作为启动特性及采用变步长进行跟踪控制,并利用Matlab/Simulink搭建了改进爬山法的MPPT控制模型,仿真结果验证该方法的有效性。     

基于模糊自适应PI控制的光伏发电MPPT

介绍了光伏发电过程中最大功率点跟踪(MPPT)原理,并简要分析了常规控制算法在最大功率跟踪控制中的优缺点,提出将模糊自适应PI控制算法应用到光伏系统最大功率点跟踪的控制中,该控制方法能快速响应外界环境的变化,获得系统最大功率点,且可以有效消除系统在最大功率点附近的振荡现象,提高系统的稳定性。仿真结果表明,该方法能使系统稳定地工作在最大功率点,并且控制精度高,能灵敏反应外界环境的变化。     

基于改进量子粒子群算法的光伏多峰MPPT研究

针对光伏阵列在局部遮阴时呈现的功率多峰特性,提出一种改进DCWQPSO算法与INC算法相结合的光伏最大功率追踪(MPPT)控制算法.该算法采用改进DCWQPSO算法进行最大功率点的全局搜索,然后利用INC算法对最大功率点进行局部跟踪,可避免动态过程中功率的震荡.仿真结果表明:所提出的MPPT控制算法跟踪速度快、精度高、...     

基于混合逻辑动态的MPPT建模仿真

针对光伏阵列的输出特性,分析最大功率点跟踪的控制原理,通过建立混合逻辑动态模型,提出一种新的MPPT控制算法——基于混合逻辑动态的功率预测控制算法。与扰动观察法进行比较,仿真结果表明该算法不但可实现对最大功率点的跟踪,同时也可改善整个光伏系统的动态性能,保证最大功率点跟踪的精准性,实现整个系统控制的快速性,验证了该算法的优越性。     

自适应模糊算法在光伏系统MPPT中的应用

针对光伏电池的非线性特性,介绍了最大功率点跟踪的原理,并详细分析了常规控制算法在光伏系统最大功率跟踪控制中的优缺点,提出将自适应模糊控制算法应用到光伏系统最大功率点跟踪的控制中,自适应模糊控制能快速响应外界环境的变化,在最大功率点无明显振荡现象.实验结果表明,该方法能使系统稳定工作在最大功率点,同时能对外界环境的变化做出快速反应.     

基于改进功率预测算法的变步长光伏MPPT研究

光伏阵列最大功率点跟踪是目前光伏发电应用的研究重点。文章针对传统功率预测算法在光照非匀速变化时出现误判这一问题,利用光照变化率的概念,使光照条件变化过程的建模更加精确,改进了传统功率预测算法。同时,通过增加步长调整系数,提高算法的跟踪速度。最后搭建光伏发电系统的最大功率点跟踪模型,对比仿真结果表明,改进算法能更迅速、更准确的实现最大功率点追踪。     

基于fuzzy-PI双模控制的光伏发电系统最大功率点跟踪仿真研究

为了提高太阳电池阵列的工作效率和整个光伏发电系统的稳定性,在光伏发电系统中需要对光伏电池的最大功率点进行跟踪。为了消除常规模糊跟踪算法在最大功率点附近出现的振荡问题,在分析光伏电池伏安特性的基础上,提出了fuzzy-PI双模控制策略,分析了该控制算法的原理,并对控制系统做了设计。Matlab/Simulink仿真表明fuzzy-PI双模控制能够快速、准确地跟踪最大功率点,避免了最大功率点处的振荡,提高了系统稳定性和能量转换效率,从而使整个双模控制兼有了MPPT精确性与快速性。     

新型MPPT算法在两级式光伏并网系统中的应用

以光伏发电系统为研究对象,分别结合相应的控制算法建立了一种带有最大功率点跟踪(MPPT)功能的光伏并网系统,并利用Matlab软件进行了仿真。仿真结果表明,前级Boost电路基于新型算法——变步长扰动观察法实现了最大功率点跟踪的功能;后级逆变电路采用电压外环、电流内环的双闭环控制方式,使逆变器的输出能准确、快速地跟踪电网电压变化,并与电网电压保持同频、同相。该系统的输出为纹波较少的正弦波形,功率因数接近于1,可满足光伏并网对逆变器的要求。     

A novel maximum power point tracker based on analog and digital control loops

In this paper, a new maximum power point tracking (MPPT) system for photovoltaic applications is presented. The proposed system consists of two analog loops, a current and a voltage loop, built around a boost converter and a digital loop for the computation of the maximum power point. The analog loops provide a fast response to sudden changes of irradiance conditions while the digital loop, enhancing the accuracy, allows the implementation of various MPPT algorithms and facilitates the integration of additional control and monitoring features. Different existing systems are simulated and compared. A small signal model for the proposed system is developed and a novel compensation method is found. The compensation is designed in such a way that it makes the system independent of the input panel used and also of the load connected at the output. In order to have fast simulation results, a macromodel is developed allowing comparison between different algorithms. Furthermore the “perturb and observe” (P&O) algorithm is improved to obtain a better response for changing irradiance conditions.     

Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system

This paper presents an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and irradiance conditions. First, for the purpose of comparison and because of its proven and good performances, the perturbation and observation (P&O) technique is briefly introduced. A fuzzy logic controller based MPPT (FLC) is then proposed which has shown better performances compared to the P&O MPPT based approach. The proposed FLC has been also improved using genetic algorithms (GA) for optimisation. Different development stages are presented and the optimized fuzzy logic MPPT controller (OFLC) is then simulated and evaluated, which has shown better performances.     

A photovoltaic powered electrolysis converter system with maximum power point tracking control

One of the main problems for renewable and other innovative energy sources is the storage of energy for sustainability. This study focuses on two different scenarios to benefit from solar energy more efficiently. Photovoltaic (PV) energy is converted to the desired voltage level using a buck converter for generating hydrogen with electrolysis process. A maximum power point tracking (MPPT) algorithm is used to benefit from the photovoltaic sources more efficiently. The basic electrolysis load for hydrogen production needs low voltage and high current and controlled sensitively to supply these conditions. The photovoltaic powered buck converter for electrolysis load was simulated in MATLAB/Simulink software using a perturb and observe (P and O) MPPT algorithm and PI controller. The simulation results show that in normal, short circuit and open circuit working conditions the PV and load voltages are stabilized. The efficiency of the proposed system is reached more than 90% for high irradiance levels.     

A novel photovoltaic maximum power point tracking technique based on grasshopper optimized fuzzy logic approach

The maximum power point tracking (MPPT) in the PV system has become complex due to the stochastic nature of the load, intermittency in solar irradiance and ambient temperature. To address this problem, a novel Grasshopper optimized fuzzy logic control (FLC) approach based MPPT technique is proposed in this paper. In this proposed MPPT, grasshopper optimization is used to tune the membership functions (MFs) of FLC to handle all uncertainties caused by variable irradiances and temperatures. The performance of the proposed grasshopper optimized FLC based MPPT is studied under rapidly changing irradiance and temperature. The proposed MPPT overcomes the limitations such as slow convergence speed, steady-state oscillations, lower tracking efficiency as encountered in conventional methods viz. perturb & observed (P&O) and FLC techniques. The feasibility of the proposed MPPT is validated through experimentation. The effectiveness of the proposed scheme is compared with P&O and also with FLC MPPT.     

光伏并网发电系统的MPPT改进算法及其在光照突变时的仿真

利用MATLAB软件中的S函数编写了光照突变时光伏组件的模型,并依此建立了一个三相光伏并网发电系统的仿真模型。对传统的最大功率点跟踪（MPPT）算法进行了分析,提出了扰动观测法和电导增量法的改进算法,给出了基于光照突变时传统的恒定电压法和所提改进算法的跟踪仿真曲线,通过根据跟踪曲线的局部和总体的相对误差以及方差比较了这些算法的效果,指出改进的扰动观测法是一种特性较好并具有实用性的MPPT算法。由于仿真分析采用了三相并网运行光伏发电系统的仿真模型,得到的结论更适合作为实际应用参考。     

A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems

Maximum power point tracking (MPPT) techniques are considered a crucial part in photovoltaic system design to maximise the output power of a photovoltaic array. Whilst several techniques have been designed, Perturb and Observe (P&O) is widely used for MPPT due to its low cost and simple implementation. Fuzzy logic (FL) is another common technique that achieves vastly improved performance for MPPT technique in terms of response speed and low fluctuation about the maximum power point. However, major issues of the conventional FL-MPPT are a drift problem associated with changing irradiance and complex implementation when compared with the P&O-MPPT. In this paper, a novel MPPT technique based on FL control and P&O algorithm is presented. The proposed method incorporates the advantages of the P&O-MPPT to account for slow and fast changes in solar irradiance and the reduced processing time for the FL-MPPT to address complex engineering problems when the membership functions are few. To evaluate the performance, the P&O-MPPT, FL-MPPT and the proposed method are simulated by a MATLAB-SIMULINK model for a grid-connected PV system. The EN 50530 standard test is used to calculate the efficiency of the proposed method under varying weather conditions. The simulation results demonstrate that the proposed technique accurately tracks the maximum power point and avoids the drift problem, whilst achieving efficiencies of greater than 99.6%.     

Modeling and control of photovoltaic and fuel cell based alternative power systems

Photovoltaic (PV) systems and fuel cells (FCs) represent interesting solutions as being alternative power sources with high performance and low emission. This work presents a modeling and control study of two power generators; photovoltaic array and fuel cell based systems. An MPPT approach to optimize the PV system performances is proposed. The PV system consists of a PV array connected to a DC-DC buck converter and a resistive load. A maximum power point tracker controller is required to extract the maximum generated power. Based on Incremental Conductance (INC) principle, the idea of the proposed control is to use a Fuzzy Logic Controller (FLC) that allows the choice of the duty cycle step size which is used to be fixed in conventional MPPT algorithms. The variable step is computed according to the value of the PV power-voltage characteristic slope. The second working system comprises a controlled DC-DC converter fed by a proton exchange membrane fuel cell (PEMFC) and supplies a DC bus. The mathematical model of the PEMFC system is given. The converter duty cycle is adjusted in order to regulate the DC bus voltage. Obtained simulation results validate the control algorithms for both of studied power systems.     

Adaptive neuro-fuzzy inference system-based maximum power point tracking of solar PV modules for fast varying solar radiations

This paper analyses the operation of an adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) for solar photovoltaic (SPV) energy generation system. The MPPT works on the principle of adjusting the voltage of the SPV modules by changing the duty ratio of the boost converter. The duty ratio of the boost converter is calculated for a given solar irradiance and temperature condition by a closed-loop control scheme. The ANFIS is trained to generate maximum power corresponding to the given solar irradiance level and temperature. The response of the ANFIS-based control system is highly precise and offers an extremely fast response. The response time is seen as nearly 1 ms for fast varying cell temperature and 6 ms for fast varying solar irradiance. The simulation is done for fast-changing solar irradiance and temperature conditions. The response of the proposed controller is also presented.     

A review of maximum power point tracking algorithms for wind energy systems

This paper reviews state of the art maximum power point tracking (MPPT) algorithms for wind energy systems. Due to the instantaneous changing nature of the wind, it is desirable to determine the one optimal generator speed that ensures maximum energy yield. Therefore, it is essential to include a controller that can track the maximum peak regardless of wind speed. The available MPPT algorithms can be classified as either with or without sensors, as well as according to the techniques used to locate the maximum peak. A comparison has been made between the performance of different MPPT algorithms on the basis of various speed responses and ability to achieve the maximum energy yield. Based on simulation results available in the literature, the optimal torque control (OTC) has been found to be the best MPPT method for wind energy systems due to its simplicity. On the other hand, the perturbation and observation (P&O) method is flexible and simple in implementation, but is less efficient and has difficulties determining the optimum step-size.     

An on-line MPPT algorithm for rapidly changing illuminations of solar arrays

Maximum power point tracking (MPPT) is usually used for a solar power system. Many maximum power tracking techniques have been considered in the past. The microprocessors with appropriate MPPT algorithms are favored because of their flexibility and compatibility with different solar arrays. Although the efficiency of MPPT algorithms is usually high, it drops noticeably in case of rapidly changing illumination conditions. The authors have proposed an improved MPPT algorithm based on the fact that the maximum power point (MPP) of solar arrays can be tracked accurately. The principle of energy conservation is used to develop the large- and small-signal model and transfer function for the solar power system. The work was carried out by both simulation and experiment on a current converter, by the digital signal processor (DSP) control, in MPPT mode under different illuminations. The results show that the proposed MPPT algorithm has successfully tracked the MPP in rapidly changing illumination conditions.