Power Performance Analysis in Off-Grid Photovoltaic Battery System with ANFIS-FL Based MPPT Under Partial Shading Effects
DOI:
https://doi.org/10.63746/njtd.v22i5.3640Keywords:
ANFIS, Fuzzy Logic, MPPT, Partial shading, Photovoltaic, Power FlowAbstract
Photovoltaic (PV) systems combined with battery storage offer a reliable and autonomous energy solution for isolated regions. However, ensuring an optimal energy balance between production and consumption, while maintaining system stability under variable solar irradiation, remains a significant challenge. Therefore, the study proposes an all-encompassing control system for off-grid photovoltaic (PV) systems. The approach considers an MPPT algorithm with adaptive neuro-fuzzy inference system (ANFIS) and fuzzy logic (FL) as the controller, which would maximize energy extraction from photovoltaic panels subjected to partial shading conditions. The system also includes a DC-AC inverter with vector control to maintain the DC bus voltage at 800 V, together with a battery management algorithm to supervise battery charging and discharging. Energy dissipation is also incorporated to balance excess production. The system's performance was simulated and evaluated using two constant loads: 35 kW and 40 kW. Results highlight a critical operational distinction: while the 40 kW scenario was fully managed by the battery storage capabilities, the 35 kW scenario required the active intervention of the dissipation system to evacuate excess power and maintain DC bus stability. Simulation results demonstrate that the proposed ANFIS-FL controller achieves a rapid MPPT response time of 0.05 s, successfully tracking the Global Maximum Power Point (GMPP) under dynamic partial shading without steady-state oscillations. Regarding stability, the DC bus voltage was tightly regulated at 800 V, with transient overshoots limited to 6.25% and 9% under the 35 kW and 40 kW scenarios, respectively.
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