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Research Article

A novel two-stage MPPT method based on inflection voltages

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Pages 591-612 | Received 01 Jun 2021, Accepted 27 Feb 2022, Published online: 10 Mar 2022
 

ABSTRACT

The electrical characteristic of a photovoltaic system is directly dependent on atmospheric conditions such as temperature, solar insolation, and even shading conditions. Hence, utilizing a maximum power point tracking hardware with a fast and accurate algorithm is crucial to obtaining the highest possible photovoltaic power. Several algorithms have been proposed in the literature to obtain maximum photovoltaic power, such as particle swarm optimization and perturb & observe variants. However, these algorithms provide less performance than optimal under partial shading. This study proposes a novel two-stage maximum power point tracking algorithm that equipped inflection voltages method and conventional perturb & observe algorithms. The proposed algorithm displays superior properties of both the inflection voltages method and the perturb & observe algorithms, such as predicting the location of maximum power points and high-speed climbing to these power points. A set of computer simulations are conducted in the PSIM environment to compare the performance of the proposed algorithm with particle swarm optimization, perturb & observe, and inflection voltages algorithms. Furthermore, a DC/DC converter-based experimental setup was produced and connected to a BK precision solar array simulator for experimental verification. The analysis results have shown that the proposed algorithm outperforms perturb & observe, inflection voltages, and particle swarm optimization methods in convergence speed and rate. Experimental and simulation results also show that the proposed algorithm successfully tracks the maximum peak in uniform and non-uniform irradiance conditions when others fail occasionally. On top of that, over 99% tracking efficiency is achieved, and the convergence time is also under 1 second.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was funded by the Scientific and Technological Research Council of Turkey (TÜBİTAK) ARDEB 1002 Grant No 120E521.

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