Hence,Load-current adaptive step-size and perturbation frequency (LCASF) based MPPT algorithm has been presented in [24] for enhancing speed, accuracy, and efficiency of the Solar-PV system. These attractive features have been addressed by designing the high-performance MPPT algorithm in [25] for efficient utilization of maximum power of Solar-PV under continuously changing environmental conditions. Likewise, modified firefly algorithm (MFA) has been proposed for minimizing the drawbacks of local peaks and oscillations of conventional MPPT algorithm under rapid-changing atmospheric conditions [26]. A modified flower pollination algorithm has been designed for enhancing the conversion efficiency of the Solar-PV system under nonuniform operating conditions [27]. Moreover, in [28], authors proposed a fuzzy logic controller (FLC) optimized by a combination of particle swarm optimization (PSO) and genetic algorithm (GA) for MPP tracking under above mentioned operating conditions. PSO and GA are two practical meta heuristic optimization approaches [29; 30] with approved efficiency, practical applications and extended variants like predictive data analysis [31], log-scaled variant [32], anaomaly detection [33], Mendelian extension[34], multi criteria decision making [35], etc. In this paper, PSO-GA is optimized by FLC and achieves remarkable output by considering various irradiation and temperature levels. A comparative study of this algorithm with the conventional and hybrid MPP algorithms is also presented. The output performance of this controller is 2-8% better than the other MPP algorithms [28]. In this work, the Incremental Conductance Particle Swarm Optimization (ICPSO) algorithm is designed and implemented for efficient tracking of the global MPP under NUOC. The significant contributions of research work included in this paper are highlighted below:  
* Design and application of ICPSO algorithm for extraction of efficient tracking the global maximum power point under NUOC. * Proposed algorithm is effective to reduce the steady-state oscillations by continuous tracking of weight component. * Proposed algorithm updates velocity and position of particles using the concept of I&C MPPT algorithm. * Proposed ICPSO is useful for fast-tracking of the speed with negligible oscillations at the global maximum point compared to other conventional and hybrid MPP algorithms. * Easy calculation for accurate tracking of global maximum during sudden fluctuations in temperature and irradiance level. * MATLAB code has been successfully executed for various temperatures and Irradiation condition of Solar-PV array in a practical scenario. Seven sections are used to arrange contents in the manuscript. Significant introduction to carry out research on the selected topic and main contributions are included in Section 1. Section 2 provides the concept behind the tracking of MPPT. Section 3 describes the system under consideration. Proposed Design and implementation of the proposed MPPT algorithm is presented in Section 4. Concept validation of proposed ICPSO algorithm is detailed in Section 5 using simulation results. Performance comparison of the proposed MPP algorithm with other existed MPP algorithms are described in Section 6, followed by conclusion in Section 7.