Performance Optimization of Photovoltaic Systems Using MPPT Under Dynamic Irradiance Conditions

Rapid irradiance transients and temperature swings shift the maximum power point (MPP) of photovoltaic (PV) arrays, degrading harvested energy when conventional Maximum Power Point Tracking (MPPT) is used. This paper investigates performance optimization under dynamic conditions by benchmarking three controllers in MATLAB/Simulink: (i) classical Perturb and Observe (P&O), (ii) Incremental Conductance (INC), and (iii) an Adaptive P&O (A-P&O) that varies the duty-cycle step using a power-slope detector and a dead-band to suppress steady-state oscillations. The PV plant comprises a string of modules feeding a DC–DC boost converter; scenarios include step changes in irradiance (1000→700→900 W/m²), fast ramps (±400 W/m²/s), and partial shading with mismatched parallel strings. Evaluation metrics are tracking efficiency, settling time, energy captured, and duty-cycle ripple. Results show that A-P&O achieves the best compromise: average tracking efficiency >99.3% with 35–50% faster settling versus fixed-step P&O, and ~2.6–3.4% more energy harvested over 60–120 s test windows. INC matches A-P&O in slow ramps but lags during abrupt transitions due to derivative noise sensitivity. The proposed configuration is simple, low-cost, and readily portable to embedded controllers for both standalone and grid-tied PV systems.