光伏系统
最大功率点跟踪
最大功率原理
控制理论(社会学)
计算机科学
MATLAB语言
控制器(灌溉)
逆变器
功率(物理)
抽水
瞬态(计算机编程)
点(几何)
电压
控制工程
工程类
数学
控制(管理)
电气工程
入口
操作系统
人工智能
物理
几何学
生物
机械工程
量子力学
农学
作者
Ramakrishna Raghutu,Vasupalli Manoj,Narendra Kumar Yegireddy
标识
DOI:10.1051/e3sconf/202454005006
摘要
The water pumping system (WPS) utilized in this research is powered by a photovoltaic (PV) system and is regulated by an inverter that is equipped with a TS-Fuzzy controller. To enhance the power extraction from the PV system when faced with partial shading conditions (PSCs), a Modified Invasive Weed Optimization (MIWO) technique is incorporated into the Perturb and Observes (P&O) algorithm. The conventional P&O algorithm faces difficulties in harnessing the full potential of the PV system when confronted with partial shading scenarios, primarily because of the presence of numerous maximum points. In such instances, optimization methods can be employed to locate the global maximum point. The MIWObased P&O algorithm proposed will modify the reference voltage according to the prevailing weather conditions in order to guarantee optimal operation of the PV system at the Maximum Power Point (MPP). The PV-based WPS is designed to cater to both irrigation and domestic water supply needs. In this study, a sensorless vector controlbased induction motor is utilized to drive the pump. The primary goal of this study is to showcase the efficiency of a PV-based WPS without the necessity of battery storage. The TS-Fuzzy controller guarantees smooth motor operation during transient periods. The efficacy of the proposed approach is confirmed through MATLAB/Simulink simulations as well as Hardware – in the – Loop and real-time data is also used, taking into account various water pumping scenarios and the fluctuating solar irradiance levels during rapid climate changes.
科研通智能强力驱动
Strongly Powered by AbleSci AI