Optimization of MPPT-Based Solar Power System for Equatorial LEO Smallsat

Abstract

The rapid adoption of small satellites is primarily driven by shortened development cycles and cost efficiency. While photovoltaic (PV) systems with direct energy transfer (DET) architectures are widely used for their low complexity, DET fails to dynamically regulate the PV operating point, resulting in suboptimal power extraction during orbit. To address this limitation, this study evaluates and compares various maximum power point tracking (MPPT) techniques using the LAPAN-A2 satellite as a case study. A modified perturb and observe (P&O) algorithm is proposed and benchmarked against conventional P&O, incremental conductance (InC), fuzzy logic, and particle swarm optimization (PSO) methods in terms of tracking efficiency, tracking speed, convergence time, and power ripple under identical operational scenarios. Quantitative results show that the modified P&O achieves a higher average MPPT efficiency of 96.76% (a 0.61% improvement over conventional P&O and InC both at 96.15%) and significantly suppresses the average power ripple to 0.36% (versus 1.15% for P&O and 1.08% for InC). Although not the fastest in every transient interval, the proposed method demonstrates consistent convergence across all conditions, offering an optimal balance between energy extraction, ripple mitigation, dynamic stability, and hardware implementation simplicity.