Experimental validation and intelligent control of a stand-alone solar energy conversion system using dSPACE platform - Yahiaoui, Fatah; Chabour, Ferhat; Guenounou, Ouahib; Zaouche, Faika; Belkhier, Youcef; Bajaj, Mohit; Shouran, Mokhtar; Elgamli, Elmazeg; Kamel, Salah (Frontiers in Energy Research, 2022)
Solar energy, as the leading renewable energy resource, is fully aware of the need to prevent the rise in global warming. The techno-economic feasibility of photovoltaic (PV) generation solar systems is greatly reliant on their operating conditions. However, the significant penetration of PV may cause lower system inertia, decreased system damping, higher frequency fluctuations when subjected to a fault or disturbance, and deteriorated small signal stability. In this paper, performances of an artificial intelligent fuzzy logic controller (FLC) based maximum power point tracking (MPPT) and a conventional perturb and observe (P&O) based MPPT controller is presented for a stand-alone PV system and tested in a real test bench experimentation using dSPACE DS1104 controller card. The studied system is composed of a DC power supply emulating the PV panel, a DC/DC boost converter, a variable resistive load and a real-time MPPT controller implemented in the dSPACE card. Under the above test conditions, a comparative analysis is performed for the proposed artificial intelligent FLC and the conventional P&O control algorithm. The proposed FLC shows the lowest transitional state response time, and the steady state variations are significantly minimized over the conventional P&O algorithm, which shows an overtaking. This makes the system more stable reducing power losses at a steady state. The demonstrated results verify the effectiveness of the proposed control scheme as compared to the conventional P&O algorithm.