A Multiple-Band Golden Section Search Strategy for Maximum Power Point Tracking in Solar Water Pumping Systems

This study proposes a novel multiple-band Golden Section Search (GSS) strategy for maximum power point tracking (MPPT) in photovoltaic (PV) systems, specifically designed to enhance the detection of the global maximum power point (GMPP) under dynamic operating conditions. The method is applied to control a brushless DC (BLDC) motor driving a single-stage solar water pumping system (SWPS). The power-voltage (P-V) curve of the PV array is optimally divided into sequential bands, within which the proposed GSS-MPPT algorithm identifies all local peaks and determines the global peak. The proposed design further increases search density compared to the conventional GSS-MPPT, ensuring GMPP capture within an acceptable time frame, reducing power oscillations, and eliminating the randomness and complexity of meta-heuristic MPPT methods. This enhanced strategy also improves reliability under shading conditions by enabling more efficient GMPP extraction. An indirect MPPT control structure, employing a proportional-integral-derivative (PID) controller, provides smooth motor speed regulation and precise PV voltage adjustment at each setpoint. MATLAB simulations under varying irradiance and temperature conditions demonstrate that the proposed system achieves stable motor operation with high dynamic responsiveness, tracking an MPPT efficiency exceeding 99%. These results confirm the method’s suitability for high-performance solar water pumping applications.