Comparison of Maximum Power Point Tracking (MPPT) Algorithms to Control DC-DC Converters in Photovoltaic Systems

Author(s): Milad Samady Shadlu*

Journal Name: Recent Advances in Electrical & Electronic Engineering
Formerly Recent Patents on Electrical & Electronic Engineering

Volume 12 , Issue 4 , 2019

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Graphical Abstract:


Background: Using the solar energy by photovoltaic arrays is constantly increasing and has been considered as one of the cleanest sources of energy in recent years. One of the ways to reduce the cost of photovoltaic systems is to maximize the power delivered to the load. On the other hand, changing the load leads to change the operating point of the solar conversion system and causes deviation from the maximum power point (MPP).

Methods: For this reason, in various research studies, attention has been paid to MPPT methods applicable in photovoltaic systems. In this paper, a comparison is performed between conventional MPPT methods including Perturb and Observe (P&O), Incremental Conductance (INC), Fractional Open Circuit Voltage (FOCV), Ripple Correlation Control (RCC) and Extremum Seeking Control (ESC). Only current and voltage parameters of the PV panel are measured instantly and used to generate control signals. However, the output voltage of the PV cells is relatively low without using the DC-DC converters.

Results: Therefore, high-performance DC-DC converters need to convert the low voltage PV arrays into high DC voltages to handle the 220 VAC systems.

Conclusion: Accordingly, in this study, conventional DC-DC converters including Boost, Buck and Buck-Boost converters are investigated, and each of them is simulated using different MPPT controllers and the results are compared together. It is worth noting that all of the simulations are carried out using MATLAB/Simulink.

Keywords: Photovoltaic system, Maximum power point tracking (MPPT), DC-DC converters, MATLAB simulation, FSCC, PV cell.

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Article Details

Year: 2019
Published on: 22 August, 2019
Page: [355 - 367]
Pages: 13
DOI: 10.2174/2352096511666180530075244
Price: $25

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