Irradiance sensorless PSO-based Integral Backstepping and Immersion & invariance algorithm for robust MPPT control with real-climatic microcontroller-in-the-loop experimental validation

Abstract

This paper presents a novel irradiance sensorless Maximum Power Point Tracking (MPPT) controller for photovoltaic (PV) systems using a Particle Swarm Optimization (PSO)-based Integral Backstepping (IBSC) and Immersion & Invariance (I&I) algorithm. The proposed controller addresses the limitations of traditional and contemporary MPPT methods, such as the need for costly irradiance sensors and suboptimal performance under dynamic environmental conditions. The integration of a higher-order sliding mode differentiator (HOSMD) with the IBSC enhances transient response by completely eliminating overshoots, achieving a 0 % overshoot compared to 4.8 % with the conventional IBSC under standard test conditions. The system exhibits rapid tracking convergence with a significantly reduced tracking time of 0.4 ms, approximately seven times faster than the traditional Perturb and Observe (P&O) algorithm's 3 ms. Under real-world conditions, the proposed system's irradiance estimator maintains a mean absolute error below 15 W/m², with a maximum error of 69 W/m² at high irradiance levels. The system achieves an operating efficiency of 99.99 % with peak-to-peak power ripples of just 0.17 % under standard conditions, outperforming eight state-of-the-art MPPT techniques. This robust and efficient MPPT solution is validated through extensive simulations and real-climatic conditions. Additionally, real-climatic experimental implementations are carried out using Microcontroller-in-the-loop (MIL) integration. The acquired experimental results do not only corroborate the simulation outcomes but also endorses the reliability and practical robustness of the proposed MPPT controller