Fuzzy Based Incremental Conductance Algorithm Stabilized By An Optimal Integrator For A Photovoltaic System Under Varying Operating Conditions

In renewable system control engineering, Maximum Power Point Tracking (MPPT) techniques are considered as one of the key steps in photovoltaic (PV) system development. Indeed, some MPPT techniques provide high performance under uniform irradiation and temperature conditions. However, their performance significantly degrades when the two preceding climatic conditions suddenly change. Therefore, this paper proposes a new voltage regulation based on Fuzzy Logic Control (FLC) strategy and small-signal model of DC-DC booster converter. The proposed control scheme is mainly based on the indirect incremental conductance (Inc) technique, equipped with an optimal integrator controller (OIC). It is implemented in a PV system, consisting of a DC-DC boost converter connected to a resistive load, with the main objective of ensuring a good MPP tracking behavior for variable operating conditions. To achieve this objective, the proposed MPPT strategy is designed around two stages. First, the smooth reference voltage is ensured by a Single-Input Single-Output (SISO) fuzzy logic controller using the Inc technique based on the MPPT approach. Then, the optimal integrator controller stabilizing the closed-loop system is integrated with optimization of its parameter according to Routh's criterion for resistive load variations. Simulation results confirm the effectiveness of the proposed MPPT technique compared to some commonly used MPPT approaches. The superiority of the proposal is proven by using efficiency ratio, which rises more than 98% in all case studies. These objectives are ensured for both uniform and critical sudden change in weather conditions, regardless of resistive load variations.