共查询到19条相似文献,搜索用时 62 毫秒
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光伏阵列局部处于阴影时,其功率输出会呈现多峰值特征,将造成传统的MPPT算法跟踪失效。文章针对标准粒子群算法(PSO)在实现多峰值MPPT控制时,存在容易进入局部最优、收敛速度较慢和跟踪精度较低等问题,提出了一种基于改进PSO算法的多峰值MPPT控制算法。该方法把非线性变化的变异策略引入到PSO算法中,在显著提高跟踪速度的前提下,扩大了粒子的搜索范围,从而增强了全局寻优能力。仿真与实验结果表明,与传统的PSO方法相比,文章所提出的方法在均匀光照、静态阴影和动态阴影下,均能快速精准地实现对全局最大功率点的跟踪和控制,在一定程度上提高了光伏阵列的发电效率。 相似文献
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为优化光伏阵列在部分遮蔽情况下的多峰值MPPT控制,保证光伏发电系统实时功率的最大输出,提出了基于改进BA算法的最大功率追踪控制方法,即在基本BA算法的基础上,融入了小生境技术的共享机制与排挤策略,减少相似个体数量,从而增加了BA算法在迭代过程中的种群多样性,提高了BA算法在MPPT控制中的全局搜索能力,增强了最大功率追踪的稳定性,并将该算法与PSO、PO算法在不同光照及温度条件下的MPPT控制效果进行了仿真试验对比。结果表明,与传统算法相比,改进的BA算法具有更好的追踪效果,不仅避免了光伏系统在遮蔽情况下输出功率陷入局部最大值的问题,且提高了发电效率。 相似文献
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为减小光伏阵列在存在局部阴影时光伏系统输出功率的损失,提高最大功率点追踪(MPPT)的速度和准确性,提出基于布谷鸟(CS)算法和扰动观察法(P&O)相结合的MPPT控制方法(ICS-P&O)。对CS算法中的种群进行分组,在随机游走阶段为2个种群设置不同的更新策略,在偏好游走阶段加入信息共享策略来辅助更新,从而加快算法的收敛,提升收敛精度,而后利用小步长P&O算法进一步提高后期的收敛精度。仿真结果表明,所提算法在不同的外界环境下追踪速度和追踪精度均得到有效提升。 相似文献
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传统MPPT算法存在易陷入局部最优的问题,且目前采用的智能优化算法解决该类问题也有追踪精度不足、追踪速度慢等问题。为解决上述问题,该文提出一种基于金枪鱼算法(TSO)与改进黏菌觅食算法(MSMA)的混合优化算法。该方法通过早期金枪鱼算法的抛物线觅食策略来加快搜索速度,对黏菌觅食算法采用基于混沌映射的反向学习策略进行改进,达到扩大算法探索范围的目的,使之不易于陷入局部最优,并提高算法运算速度。将改进后的算法应用于光伏系统MPPT中,仿真实验结果表明:改进后算法相较于单独TSO与MSMA算法,在不同遮光条件下追踪速率有较大提升,精确度高于单独的TSO与MSMA算法,拥有更好的追踪速度与追踪精度。 相似文献
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针对在局部阴影情况下光伏阵列的功率-电压(P-U)特性曲线呈多峰特性,粒子群算法应用于局部阴影下的最大功率点跟踪(MPPT)跟踪,存在搜索速度慢、精度低的缺点。提出自适应惯性权重粒子群优化(PSO)算法的最大功率点跟踪算法,自动更新惯性权重w和学习因子C1、C2,通过仿真实验,优化前的全局最大功率点(GMPP)跟踪时间是0.045 s,输出功率为468 W。优化后的自适应粒子群算法GMPP跟踪时间为0.020 s,输出功率稳定在为480 W,光伏阵列的输出功率跟踪误差小于30%。在所搭建辐照度突变模型仿真中,在4.022 s突变到300 W/m2时经过0.05 s又重新跟踪到了新的最大功率点稳定在0.075 MW。最后通过实验平台验证,优化后的自适应粒子群优化算法与传统的粒子群优化算法相比,追踪时间减少了55.5%,误差小于5%,验证了该算法可行性和实用性。 相似文献
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《可再生能源》2016,(9)
针对光伏系统传统的最大功率点跟踪(MPPT)算法跟踪速度慢、易振荡、跟踪精度低等不足,提出一种改进的分数阶电导增量(IFOINC)算法,即将基于功率预测的变步长扰动观察(PO)算法和分数阶电导增量(FOINC)算法结合使用。IFOINC算法具体跟踪过程,先采用基于功率预测的变步长PO算法快速跟踪到MPP附近,再采用FOINC算法进一步搜索MPP从而完成整个跟踪过程。文章研究了光伏系统结构,光伏电池的等效模型,设计了IFOINC算法,建立了光伏系统MPPT仿真模型,在Matlab/Simulink下进行仿真。在光照均匀的条件下,改变其它环境条件,研究IFOINC算法的MPP跟踪效果与基于功率预测的变步长PO算法和FOINC算法之间的差异。研究结果表明,IFOINC算法的跟踪速度比FOINC算法提高了42.3%,IFOINC算法的跟踪精度比基于功率预测的变步长PO算法提高了3.9%,且消除了跟踪过程的振荡。 相似文献
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针对风光联合发电系统,文章提出了一种基于Cuk变换器电路的分时进行光伏电池和永磁风机最大输出功率跟踪的新控制方法。采用模糊控制算法对光伏电池和永磁风机最大输出功率跟踪进行了变步长确定。试验测试表明:对光伏电池和永磁风机的最大输出功率跟踪进行分时控制方案可行。采用模糊规则库确定步长效果良好,并且整体系统具有良好的经济实用性。 相似文献
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Artificial neural network (ANN) based maximum power point tracking (MPPT) algorithm makes use of the advantages of ANNs such as noise rejection capability and not requiring any prior knowledge of the physical parameters relating to PV system. This paper proposes a genetic algorithm (GA) optimized ANN-based MPPT algorithm implemented in a stand-alone PV system with direct-coupled induction motor drive. The major objective of this design is to eliminate dc–dc converter and its accompanying losses. Implementing off-line ANN in DSP needs optimization of ANN structure to obtain an ideal size. GA optimization was used in this study to determine neuron numbers in multi-layer perceptron neural network. Another objective of this work is to prevent the necessity of the trade-off between the tracking speed and the oscillations around the maximum power point. Hence, varying step size is used in MPPT algorithm and PI-controller is adopted for simple implementation. Simulation and experimental results have been used to demonstrate effectiveness of the proposed method. 相似文献
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《International Journal of Hydrogen Energy》2023,48(60):23230-23241
Renewable energy sources have provided a great contribution to global energy demand; However, their intermittent characteristics can cause sustainability and efficiency problems. To handle these, alternative systems are utilized. Among these, proton exchange membrane fuel cells (PEMFCs) stand out with their longer lifecycle, efficient, and cost-effective features. However, their performance depends on operating conditions such as temperature, gas pressure, and membrane water content. These nonlinear features require instant and proper control for maximizing efficiency and longer working life. In this study, a whale optimization algorithm (WOA) based maximum power point tracking (MPPT) controller is utilized for a PEMFC system. To validate the proposed controller, the PEMFC system has been analyzed under changing conditions in the MATLAB/Simulink environment. The proposed method has been compared with the other MPPT methods. The results indicate that the proposed controller can provide accurate and fast MPPT performance, less power fluctuations, and higher production efficiency. 相似文献
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S.A.KH. Mozaffari Niapour S. Danyali M.B.B. Sharifian M.R. Feyzi 《Energy Conversion and Management》2011,52(8-9):3043-3059
This paper discusses operation performance of a water pumping system consist of a brushless dc (BLDC) motor coupled a centrifugal pump and accompanying a Z-source inverter (ZSI) fed by a photovoltaic (PV) array, to be improved. Despite conventional double-stage power converters, this paper proposes utilizing a single-stage ZSI to extract the maximum power of the PV array and supply the BLDC motor simultaneously. Utilizing the ZSI provides some inherent advantages such as high efficiency and low cost, which is very promising for PV systems due to its novel voltage buck/boost capability. In addition, in order to precisely perform the maximum power point tracking (MPPT) of the PV array the fuzzy logic-incremental conductance (FL-IC) MPPT scheme is proposed. The proposed FL-IC MPPT scheme provides enough modification to the conventional IC method to enjoy an appropriate variable step size MPPT control signal for the ZSI. Moreover, direct torque control (DTC) is found more effective in comparison with hysteresis current control with current shaping to drive the BLDC motor, because it benefits from faster torque response, reduced torque ripple, less sensitivity to parameters variations, and simple implementation. In the mean time, due to the frequently variations of the PV power generation; delivered mechanical power to the centrifugal pump is variable. Thus, the BLDC motor should be driven with variable reference speed. In order to improve the speed transient response of the BLDC motor and enhance the energy saving aspect of the system, it should enjoy a high quality dynamic response characteristic. Therefore, to realize these purposes, particle swarm optimization (PSO) has been proposed to regulate the proportional-integral-derivative (PID) parameters of the BLDC motor speed controller. The system configuration, operation principle and control methods are presented in detail. Finally, the proposed system was simulated in different operation conditions of the PV array by computer simulations and the effectiveness of the proposed control strategies has been validated by comparative studies and simulation results. 相似文献
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在利用Matlab-Simulink软件结合组件工程模型建立的系统仿真模型基础上,首先仿真分析了各种因素对系统输出特性的影响,为了克服传统算法定步长跟踪带来的不利影响,提出了一种变步长跟踪算法,并对其进行了仿真验证. 相似文献
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《可再生能源》2017,(1)
基于光伏并网发电系统直流母线电压恒定的特点,定义了一个由光伏电池输出电流和Boost变换器占空比表示的等效功率,根据该等效功率与Boost变换器占空比的关系深入分析了一种无电压传感器最大功率点跟踪(MPPT)算法。为了实现变步长跟踪以保证MPPT算法的快速性,将模糊控制与无电压传感器MPPT算法相结合,改善了系统的动态特性。基于Matlab/Simulink平台搭建了光伏并网发电系统模型,将该算法与传统的扰动观测法进行比较,结果表明,在保证稳态精度的基础上,基于模糊控制的无电压传感器MPPT算法具有更快的跟踪速度,并在光照强度和温度变化的条件下证明了该算法具有更好的鲁棒性。 相似文献