最大功率点跟踪
光伏系统
占空比
控制理论(社会学)
最大功率原理
太阳能微型逆变器
太阳辐照度
功率(物理)
MATLAB语言
计算机科学
电子工程
电压
工程类
电气工程
逆变器
物理
人工智能
操作系统
大气科学
控制(管理)
量子力学
作者
M. Premkumar,Umashankar Subramaniam,Thanikanti Sudhakar Babu,Sanjeevikumar Padmanaban,Jens Bo Holm‐Nielsen,Massimo Mitolo,R. Sowmya
出处
期刊:IEEE Systems Journal
[Institute of Electrical and Electronics Engineers]
日期:2021-06-01
卷期号:15 (2): 3024-3035
被引量:67
标识
DOI:10.1109/jsyst.2020.3003255
摘要
The primary concerns in the practical photovoltaic (PV) system are the power reduction due to the change in operating conditions, such as the temperature or irradiance, the high computation burden due to the modern maximum power point tracking (MPPT) mechanisms, and to maximize the PV array output during the rapid change in weather conditions. The conventional perturb and observation (P&O) technique is preferred in most of the PV systems. Nevertheless, it undergoes false tracking of maximum power point (MPP) during the rapid change in solar insolation due to the wrong decision in the duty cycle. To avoid the computational burden and drift effect, this article presents a simple and enhanced P&O MPPT technique. The proposed technique is enhanced by including the change in current (dI), in addition to the changes in output voltage and output power of the PV module. The effect of including the dI profile with the traditional method is explained with the fixed and variable step-size methods. The mathematical expression for the drift-free condition is derived. The traditional boost converter is considered for validating the effectiveness of the proposed methods by employing the direct duty cycle technique. The proposed algorithm is simulated using MATLAB/Simulink and validated under various scenarios with the developed laboratory prototype in terms of drift-free characteristics and tracking efficiency. The result proves that the proposed technique can track the MPP accurately under various operating conditions.
科研通智能强力驱动
Strongly Powered by AbleSci AI