Abstract
This paper presents a Modified Perturb & Observe (P&O) Maximum power point tracking (MPPT) algorithm using fuzzy logic-based variable step size to overcome some of the limitations associated with the conventional P&O MPPT tracking method to improve the transient response and reduce the steady-state terminal voltage oscillations. The proposed MPPT algorithm was implemented and tested on an indoor emulated PV source that is constructed from a conventional solar panel and a DC power supply, a boost DC-DC converter and a dSPACE-based MPPT controller. The advantage of implementing this testing platform for MPPT is easy implementation and indoor testing of MPPT algorithms and DC-DC power converters. Thus, dependency on atmospheric conditions such as irradiance level can be avoided. Details of the emulated PV source mathematical model and electrical characteristics, the proposed MPPT algorithm via dSPACE, simulation and test results were presented in the paper.
Highlights
Renewable energy is increasingly becoming popular due to environmental degradation caused by widespread use of fossil fuel
This paper proposed a modified perturb and observe (MP&O) Maximum power point tracking (MPPT) algorithm using fuzzy logic-based variable step size to overcome some of the limitations associated with the conventional
Perturb & Observe (P&O) based on fuzzy logic variable step size have a small deference of 0.38% efficiency in favor of the based on fuzzy logic variable step size have a small deference of 0.38% efficiency in favor of the Modified P&O based on fuzzy logic variable step size using Equation (2)
Summary
Renewable energy is increasingly becoming popular due to environmental degradation caused by widespread use of fossil fuel. The extensive use of fossil fuel results in potential economic upheaval, massive pollution issues as well as greenhouse gases which leads to climate change All these environmental degradations have increased the demand for green energy produced by renewable energy sources, such as solar energy, geothermal energy, tidal energy, biomass, biofuel and hydroelectric energy [1,2]. P&O MPPT tracking method discussed in [7,8] These limitations are slow convergence or rising time towards maximum power point (MPP), oscillation of PV power in steady state conditions around (MPP) resulting to power loss and abrupt change of MPP position under variable atmospheric conditions. Simulation and experimental results of the proposed MP&O MPPT algorithm show the method is efficient in tracking the maximum power point with changes in solar irradiance
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
