Particle Swarm Optimization–Based Global MPPT for a Standalone PV Water Pumping System Under Partial Shading

Abstract

Partial shading conditions (PSCs) distort the photovoltaic (PV) power–voltage characteristic and generate multiple local maxima, potentially trapping conventional maximum power point tracking (MPPT) algorithms and reducing the energy available to motor–pump systems. This paper investigates a particle swarm optimization (PSO)–based global MPPT (GMPPT) strategy for a low-power standalone photovoltaic water pumping system (PVWPS) composed of a bypass-diode-protected PV module, a DC–DC boost converter, a permanent-magnet DC (PMDC) motor, and a centrifugal pump. The PSO algorithm directly searches for the optimal boost duty ratio that maximizes PV power under PSCs. To improve practical applicability, a holding-stage and averaged-fitness evaluation are introduced to reduce transient influence and limit steady-state oscillations. MATLAB/Simulink simulations are performed under uniform irradiance and a representative PSC pattern (1000–1000–200 W/m 2 In addition to electrical indicators, pumping-oriented metrics such as hydraulic power, motor speed, and flow rate are analyzed. Results show that PSO successfully converges to the global peak region under PSCs, improving hydraulic power by approximately 34% and increasing flow rate and motor speed by about 10% compared to the Incremental Conductance (INC) method, while maintaining a low ripple.