摘要： Maximum power point tracking (MPPT) is an algorithm to extract maximum available power from a solar photovoltaic system associated with DC-DC power converters. Conventional MPPT methods like Perturb and Observe (P&O) algorithm and Incremental Conductance algorithm are inefficient, as they cannot differentiate between local and global MPP. In addition, they oscillate on reaching MPP due to their fixed step size. Advanced methods using Artificial Neural Networks and Artificial Intelligence based methods were proposed to overcome these problems. These advanced methods have high tracking efficiency and they are fast. Particle Swarm Optimization algorithm based MPPT method a simple and basic method of Artificial Intelligence based MPPT methods. This paper presents a brief review of advanced artificial intelligence based MPPT methods alongside the generic SPV model utilized for simulation.