The increase of renewable energy usage in the last two decades, in particular photovoltaic (PV) systems, has opened up different solar plant configurations that need to operate and properly perform in terms of efficient power transfer with respect to all of the involved components, such as inverters, grid interface, storage, and other electrical loads. In such applications, the power characteristics of the plant modules all together represent the main components that are responsible for power extraction, depending on both external and internal factors. Conventionalmaximumpower point tracking techniques may not have a proper conversion efficiency under particular external dynamic conditions. This paper proposes an evolutionary-based maximum power point tracking algorithm suitable to operate under dynamic partial shading conditions and compares its performance with classical maximum power point trackingmethods in order to evaluate their conversion efficiency in partial shading scenarioswith relevant and dynamic changes in the environmental conditions. Simulations taking into account the different dynamic shading conditions were carried out to prove the effectiveness and limitations of the proposed approach with respect to classical algorithms.

An evolutionary-based MPPT algorithm for photovoltaic systems under dynamic partial shading

Dolara, Alberto;Grimaccia, Francesco;Mussetta, Marco;Ogliari, Emanuele;Leva, Sonia
2018-01-01

Abstract

The increase of renewable energy usage in the last two decades, in particular photovoltaic (PV) systems, has opened up different solar plant configurations that need to operate and properly perform in terms of efficient power transfer with respect to all of the involved components, such as inverters, grid interface, storage, and other electrical loads. In such applications, the power characteristics of the plant modules all together represent the main components that are responsible for power extraction, depending on both external and internal factors. Conventionalmaximumpower point tracking techniques may not have a proper conversion efficiency under particular external dynamic conditions. This paper proposes an evolutionary-based maximum power point tracking algorithm suitable to operate under dynamic partial shading conditions and compares its performance with classical maximum power point trackingmethods in order to evaluate their conversion efficiency in partial shading scenarioswith relevant and dynamic changes in the environmental conditions. Simulations taking into account the different dynamic shading conditions were carried out to prove the effectiveness and limitations of the proposed approach with respect to classical algorithms.
2018
Evolutionary algorithms; MPPT algorithm; Particle swarm optimization; Photovoltaics; Materials Science (all); Instrumentation; Engineering (all); Process Chemistry and Technology; Computer Science Applications1707 Computer Vision and Pattern Recognition; Fluid Flow and Transfer Processes
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1085431
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