A new control strategy for harmonic reduction in photovoltaic inverters inspired by the autonomous nervous system

Walid Rahmouni – Ghalem Bachir – Michel Aillerie

   This paper proposes a new inverter control strategy whose main purpose is to reduce the current harmonic distortion resulting from unnecessary control actions without sacrificing the system's dynamic response. The brain's capabilities to learn and react to stress are mimicked to generate control actions based on emotional cues. The model is based on the brain emotional learning based intelligent controller, to which an autonomous nervous system was added. The modified controller aims at separating the strategy during transient states from the one during steady states. The proposed method was compared to the PI controller, the PR controller, and a neural network-based controller on Matlab Simulink. It shows major improvements in terms of harmonic distortion and a complete removal of the inter-harmonics. It provides a good dynamic response in transient states and an immunity to irrelevant signal variations during the steady state, which results in an improvement in the harmonic production.

Keywords: photovoltaic system control, harmonic spectrum, THD, BELBIC, grid integration, transient state detection

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