This paper presents modeling and evaluation of more widely used Maximum power Point tracking (MPPT) algorithms. These algorithms are simulated in Matlab/Simulink environment in order to provide a comparison in terms of sensors required, ease of implementation, efficiency, and the dynamic response of the Photovoltaics (PV) systems to variations in temperature and irradiance. This simulation based evaluation can be useful in specifying the appropriateness of the MPPT algorithms for the different PV system applications. It can be used as a reference modeling for future research related to the PV power generation. Furthermore, a novel artificial intelligence technique based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is presented in this work. The solar irradiance and cell temperature are used as input to predict the duty cycle of the electronic switch of the DC-DC converter adopted in the system. The proposed technique provides high accuracy, stability, very fast tracking algorithm.
- Maximum power Point tracking algorithms
- Photovoltaics systems
- Adaptive Neuro-Fuzzy Inference System
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment