A Direct Search Nelder Mead MPPT based Induction Motor Drive for Solar PV Water Pumping Systems

K. Swetha, Barry Venugopal Reddy, R. Jain
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Abstract

This paper presents a Nelder Mead (NM) approach for solar photovoltaic (SPV) array-based water pumping systems (WPS) to achieve maximum power point tracking (MPPT). The conventional MPPT algorithms fail to track global MPPT under partial shading conditions. The NM algorithm mainly consists of four operations (reflection, expansion, contraction, and shrinkage) which aid in the rapid convergence of all the particles to a global optimum. This results in a negligible steady-state error. The two-stage PV system is modeled and simulated in MATLAB/Simulink. To verify the effectiveness of the proposed system, it is compared with the perturb and observe and particle swarm optimization method. The NM algorithm converges in an average time duration of 0.25 s with an efficiency of 99.85%. The proposed two-stage system performance has been improved with the reduction in steady-state oscillation when compared with the conventional method.
基于直接搜索Nelder Mead MPPT的太阳能光伏水泵系统感应电机驱动
针对太阳能光伏(SPV)阵列抽水系统(WPS)的最大功率点跟踪(MPPT),提出了一种Nelder Mead (NM)方法。在部分遮阳条件下,传统的MPPT算法无法跟踪全局MPPT。NM算法主要包括四个操作(反射、扩张、收缩和收缩),有助于所有粒子快速收敛到全局最优。这导致一个可以忽略不计的稳态误差。在MATLAB/Simulink中对两级光伏系统进行了建模和仿真。为了验证所提系统的有效性,将其与扰动观测和粒子群优化方法进行了比较。该算法的平均收敛时间为0.25 s,效率为99.85%。与传统方法相比,所提出的两级系统性能得到改善,稳态振荡减小。
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