In this study, a precise global maximum power point tracking (MPPT) technique based on invasive weed optimization (IWO) algorithm for PV array under partial shading conditions (PSCs) is proposed. There are several maximum power points (MPPs) in the power-voltage curve of the PV array. These points; have a unique global point and the others are local. Hence, optimal MPPT will be troublesome operation. Classical MPPT techniques, such as Perturb & Observe (P&O) and Incremental Conductance (IC) cannot recognize between local MPP and global MPP, so it is incurable to track global MPP using these techniques under partial shading conditions. Furthermore, some researches in the area to overcome this problem, global MPPT techniques based on Meta-Heuristic optimization algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Harmony Search Algorithm (HSA), Bat Algorithm (BA), Sine Cosine Algorithm (SCA), Cuckoo Search (CS), and Genetic Algorithm (GA) are presented in literature. The main contribution of this study is to inform a new optimization technique based on IWO which is not used before with this problem. An overall statistical appraisal of IWO, with different meta-heuristic techniques mentioned before is executed under different scenarios of shading conditions. Six statistical metrics including geometric mean error, the root mean square error, mean absolute error, standard deviation, significance using t-test, and efficiency are used to estimate the superiority of the proposed technique over all other techniques. Hence, the proposed MPPT based on IWO algorithm is considered to be the most efficient and outstanding optimization technique compared to corresponding ones.