基于粒子群优化的光伏MPPT算法

针对光伏发电系统最大功率点跟踪恒定电压法跟踪精度较低的缺点,提出了基于温度系数在线修正的改进恒定电压法与粒子群优化结合的光伏MPPT算法,即在系统偏离最大功率点时,采用改进恒定电压法快速确定一个新的工作点,再采用粒子群优化进行最大功率控制,使得MPPT确保跟踪速度的同时又提高了跟踪精度。最后通过Matlab/Simulink对该算法进行了仿真,结果表明该控制系统可快速跟踪最大功率点。     

粒子群算法与电导增量法的双级最大功率点跟踪控制

通过对光伏发电最大功率点跟踪系统的研究,提出了PSO与电导增量法的双级最大功率跟踪(MPPT)控制算法。该算法能很好地解决传统电导增量法在采用较大跟踪步长时跟踪精度差,采用较小跟踪步长时跟踪速度慢,动态跟踪过程中功率震荡大的问题。所提出的算法包含最优占空比预测和最大功率点跟踪两个阶段。最优占空比预测阶段采用改进的PSO算法搜索最大功率点附近的工作电流和工作电压,然后根据搜索到的电压和电流计算最大功率点附近的最优占空比,该阶段能解决传统的电导增量法在采用较小步长时存在的跟踪速度慢、功率震荡大等问题;在最大功率点跟踪阶段接收上一阶段所搜索到的最优占空比,当电导增量法所产生的占空比接近最优占空比时,采用电导增量法进行控制,否则采用上一环节的最优占空比进行控制。仿真实验结果表明,PSO与电导增量法的双级MPPT控制算法跟踪速度快,跟踪精度高,功率震荡小,能很好地实现最大功率点跟踪。     

基于占空比的无电流传感器最大功率点跟踪系统

为了降低能量收集系统的功率损耗,提出了一种基于占空比的无电流传感器最大功率点跟踪（Maximum Power Point Tracking,MPPT）系统。传统的MPPT方法需要进行直流测量或开路电压测量,本文提出的算法利用滞后切换信息预估发电机的输出功率,可以实现保持最大功率提取,无需进行直流测量。采用MSP430微控制器进行了实现,并调整MPPT算法以适合热电发电机的特性。滞后电压调节器能够将热电发电机输出电压维持在参考电平上,因此可以根据给定的温度条件下提取最大功率。实验分析结果表明,提出的MPPT能量收集系统结构简单、成本较低、功率损耗低,且适用于各类小规模可持续发电。     

基于DSP的光伏电池最大功率点跟踪系统

太阳能光伏阵列的输出特性受外界环境的影响具有强烈的非线性,为了提高系统的整体效率,一个重要的途径就是实时调整光伏电池的工作点,进行最大功率点跟踪(MPPT),使之始终工作在最大功率点附近。本文通过对太阳能电池伏安特性的分析,采用自适应扰动观察算法,基于TMS320F2812设计了MPPT控制系统。实验结果表明,在此算法控制下,系统能够准确地跟踪最大功率点。     

基于周期扫描的太阳能控制器MPPT方法实现

经典的最大功率点跟踪（MPPT）算法会由于外部环境的变化或系统本身采样的误差而无法·陕速地达到最优点。本文提出了一种基于周期扫描的MPPT算法,当系统启动、检测到外部环境发生变化或间隔一定周期时,重新对特定的占空比进行扫描,以快速、准确的确定新的最大功率点。控制器采用同步降压斩波的拓扑结构．降低了系统的功耗。并采用软启...     

基于改进的黄金分割法的MPPT算法研究

为了提高光伏电池的利用效率,需要对光伏电池最大功率点进行快速精确地跟踪。文中提出了一种改进的黄金分割算法,通过在Matlab/Similink平台上进行系统的建模与仿真分析,将所得结果与传统的MPPT算法比较,结果表明,该方法能够显著提高MPPT跟踪的速度和精度。     

基于改进型单纯式加速法变步长MPPT控制算法

结合光伏并网系统控制特点,针对单纯式加速法的不足,提出一种新的基于改进型单纯式最大功率点跟踪(MPPT)优化算法,设计在线步长调节,改变电压收敛速度.利用PSIM仿真软件构建通用型光伏矩阵模型,模拟任意参数的光伏阵列,动态跟踪光照强度、环境温度的变化,应用于单相光伏并网系统.仿真结果表明,相对于常规MPPT控制算法,结合优化技术的变步长MPPT算法能快速准确地跟踪最大功率点,且系统波动小,稳定性高.     

基于双并联Boost电路的光伏系统最大功率点跟踪控制方法

光伏电池的输出功率取决于外界环境（温度和光照条件）和负载状况,需采用最大功率点跟踪（MPPT）电路,才能使光伏电池始终输出最大功率,从而充分发挥光伏器件的光电转换效能.在比较了常用光伏发电系统控制的优缺点后,依据MPPT控制算法的基本工作原理,主电路采用双并联Boost电路,具有电压提升功能,并且能够提高DC-DC环节的额定功率和减小直流母线电压的纹波.针对传统扰动观察法存在的振荡和误判问题,提出了一种新型的基于双并联Boost电路的改进扰动观察法最大功率跟踪策略.在Matlab/Simulink下进行了建模与仿真,仿真结果表明,当外界环境发生变化时,系统能快速准确跟踪此变化,避免算法误判现象的发生,通过改变当前的负载阻抗,使之与光伏电池的输出阻抗等值相匹配采满足最大功率输出的要求,使系统始终工作在最大功率点处,并且在最大功率点处具有很好的稳态性能.最后通过实验验证了该算法的有效性.     

基于细菌觅食算法的光伏阵列MPPT控制方法

针对光照不均匀条件下光伏阵列P-V输出特征呈现多波峰,传统算法无法摆脱局部最优值的缺点,提出了一种基于细菌觅食的优化算法,并首次应用于光伏阵列的最大功率点跟踪(MPPT)。算法引入了趋向性操作,用以进行局部范围内的最优寻找。分析了光伏阵列在遮挡条件下输出功率的变化特性,然后使用细菌觅食算法进行了最大功率点跟踪控制方法实验。实验表明,该算法能够成功摆脱局部最优值的约束,快速寻找到全局最大功率点,控制精度高,为光伏阵列最大功率点跟踪提供了一种新的实现方法。     

提高能效的自主供电系统智能控制算法模型建立与仿真

为解决太阳能电池为机器人系统提供能量效率低下的问题,文中设计开发一种提高能效的自主供电系统。其采用基于模糊逻辑扰动观测算法的智能MPPT充电控制器,该算法通过使用足够精确的预测和自适应算法克服了在功率波动与最大功率点跟踪时间固定等方面的缺点,提高了太阳能电池的效率。为了研究模糊逻辑器件在MPPT算法中的实现,文中在Matlab/Simulink环境下开发了该系统的仿真模型,包括太阳能电池、MPPT控制器、蓄电池和负载。仿真结果表明,MPPT技术的应用使太阳能系统能量产生量提高了23%;将模糊逻辑算法引入MPPT控制器大幅提升了最大功率点跟踪的速度,且抵消了电压波动,从而使功率不足减少了2%。     

Improvement of maximum power point tracking in photovoltaic arrays in different environments using hybrid algorithms

When the photovoltaic(PV) system is generating PV power, the partial shading(PS) condition will cause multiple peaks in the power-voltage curve, and changes in light intensity and ambient temperature will cause the curve to shift. Traditional maximum power point tracking(MPPT) methods, such as the incremental conductance(INC) method, have the problem of being trapped in the local optimal solution. Biomimetic optimization algorithms, such as particle swarm optimization(PSO), have problems with os...     

A PSO‐based maximum power point tracking for photovoltaic systems under environmental and partially shaded conditions

To increase the efficiency of photovoltaic (PV) systems, maximum power point (MPP) tracking of the solar arrays is needed. Solar arrays output power depends on the solar irradiance and temperature. Also the mismatch phenomenon caused by partial shade will affect the output power of solar systems and lead to the incorrect operation of conventional MPP tracker. Under partially shaded conditions, the solar array power–current characteristic has multiple maximum. This paper presents a maximum power point tracking (MPPT) with particle swarm optimization method for PV systems under partially shaded condition. The performance of the proposed method is compared with perturb and observe (P&O), improved P&O, voltage‐based maximum power point tracking and current‐based maximum power point tracking algorithms, especially, under partially shaded condition. Simulation results confirm that proposed MPPT algorithm with high accuracy can track the peak power point under different insolation, temperature and partially shaded conditions, and it has the best performance in comparison with four mentioned MPPT algorithms. Also under rapidly changing atmospheric conditions, the P&O algorithm is diverged. Copyright © 2013 John Wiley & Sons, Ltd.     

A Fuzzy Logical MPPT Control Strategy for PMSG Wind Generation Systems

Making full use of wind power is one of the main purposes of the wind turbine generator control. Conventional hill climbing search (HCS) method can realize the maximum power point tracking (MPPT). However, the step size of HCS method is constant so that it cannot consider both steady-state response and dynamic response. A fuzzy logical control (FLC) algorithm is proposed to solve this problem in this paper, which can track the maximum power point (MPP) quickly and smoothly. To evaluate MPPT algorithms, four performance indices are also proposed in this paper. They are the energy captured by wind turbine, the maximum power-point tracking time when wind speed changes slowly, the fluctuation magnitude of real power during steady state, and the energy captured by wind turbine when wind speed changes fast. Three cases are designed and simulated in MATLAB/Simulink respectively. The comparison of the three MPPT strategies concludes that the proposed fuzzy logical control algorithm is more superior to the conventional HCS algorithms.     

Design and implementation of FPGA-based Taguchi-chaos-PSO sun tracking systems

The field-programmable gate array (FPGA) based intelligent sun tracking system proposed in this paper uses an NI 9642 controller to integrate the dual-axis sun tracking system with a Maximum Power Point Tracker (MPPT), so as to effectively increase the output power of solar panels. Furthermore, it is provided with multiple intelligent functions, so that the system can start up the sun tracking function automatically in the daytime, and automatically return to its initial position at night. It has a delay function to reduce the electric power consumed by the motor in rotation. Moreover, it can be switched to dual-axis or one-axis sun tracking freely as required by the user, and the solar panel inclination can be operated directly. The dual-axis sun tracking system uses the Particle Swarm Optimization (PSO) method to look for the parameters of the PI controller. The Taguchi Method and Logistic Map are proposed to enhance the steady state convergence of PSO in seeking the optimal solution. The MPPT uses Fuzzy Logic to adjust the step length of the incremental conductance method, so as to remedy the defects in the traditional fixed step method, and to make the solar panel output reach the maximum power point position rapidly and stably.     

Efficient Maximum Power Tracking of Energy Harvesting Using a μController for Power Savings

This letter describes an efficient technique for maximum power point tracking (MPPT) of an energy harvesting device. It is based on controlling the device voltage at the point of maximum power. Using a microcontroller with a power saving technique, the MPPT algorithm maintains the maximum power with low power consumption. An experiment shows that the algorithm maximizes the energy transfer power using an energy management IC fabricated in a 0.18‐μm process. Compared to direct energy transfer to a battery, the proposed technique is more efficient for low‐energy harvesting under variable conditions.     

Maximum Power Point Tracking in Variable Speed Wind Turbine Based on Permanent Magnet Synchronous Generator Using Maximum Torque Sliding Mode Control Strategy

The present study was carried out in order to track the maximum power point in a variable speed turbine by minimizing electromechanical torque changes using a sliding mode control strategy. In this strategy, first, the rotor speed is set at an optimal point for different wind speeds. As a result of which, the tip speed ratio reaches an optimal point, mechanical power coefficient is maximized, and wind turbine produces its maximum power and mechanical torque. Then, the maximum mechanical torque is tracked using electromechanical torque. In this technique, tracking error integral of maximum mechanical torque, the error, and the derivative of error are used as state variables. During changes in wind speed, sliding mode control is designed to absorb the maximum energy from the wind and minimize the response time of maximum power point tracking (MPPT). In this method, the actual control input signal is formed from a second order integral operation of the original sliding mode control input signal. The result of the second order integral in this model includes control signal integrity, full chattering attenuation, and prevention from large fluctuations in the power generator output. The simulation results, calculated by using MATLAB/m-file software, have shown the effectiveness of the proposed control strategy for wind energy systems based on the permanent magnet synchronous generator (PMSG).     

基于复合式PSO的光伏最大功率点跟踪控制

针对不均匀光照条件下光伏阵列的MPPT跟踪控制问题,提出了基于粒子群的复合式MPPT控制算法。复合式PSO-MPPT控制算法包括离线寻优和在线寻优两个部分。离线寻优环节采用相邻粒子信息交换机制加强了在寻优过程中的收敛性以及对关键区域的搜索力度;在线寻优环节采用适应度模糊判断的方法解决了粒子群算法在线工作时扰动大、耗时长的问题。复合式PSO-MPPT控制算法将离线和在线的优化方法结合到一起,弥补了各自方法的不足。与传统的方法相比,所提出的方法具有更快的响应速度和更高寻优精度。最后通过Matlab仿真证明了所提出的算法可以实现在不均匀光照条件下的最大功率点跟踪。     

基于MPPT的变速恒频双馈风力发电系统控制策略

充分利用风能是风力发电控制的主要目的之一,为达此目的,本文基于风力机特性和双馈风力发电机的数学模型,提出了一种不依赖于风速测量来实现双馈风力发电系统最大功率点追踪(MPPT)控制的策略。该策略应用定子磁链定向矢量控制技术,对双馈发电机进行有功功率和无功功率的解耦控制,然后通过对发电机输出有功功率进行控制来间接得到与风速相对应的最佳叶尖速比和最优转速,从而实现最大功率点追踪(MPPT)控制。仿真结果证实了基于该方法,双馈风力发电系统在风速变化过程中能自动寻找并追随最大功率点,且控制相对简单,运行可靠,有较高的实用价值。