University of Sistan and Baluchestan International Journal of Industrial Electronics Control and Optimization 2645-3517 3 4 2020 09 01 Application of Improved Salp Swarm Algorithm Based on MPPT for PV Systems under Partial Shading Conditions 407 414 5540 10.22111/ieco.2020.31320.1200 EN Javad Farzaneh Electrical and Computer Engineering Faculty, Semnan University, Semnan, Iran Ali Karsaz Khorasan Istitute of Higher Education Journal Article 2019 08 16 Maximum Power Point Tracking (MPPT) is an important concept for both uniform solar irradiance and Partial Shading Conditions (PSCs). The paper presents an Improved Salp Swarm Algorithm (ISSA) for MPPT under PSCs. The proposed method benefits a fast convergence speed in tracking the Maximum Power Point (MPP), in addition to overcoming the problems of conventional MPPT methods, such as failure to detect the Global MPP (GMPP) under PSCs, getting trapped in the local optima, and oscillations around the MPP. The proposed method is compared with original algorithms such as Perturbation and Observation (P&O) method (which is widely employed in MPPT applications), Differential Evolutionary (DE) algorithm, Particle Swarm Optimization (PSO), and Firefly Algorithm (FA). The obtained results show that the proposed method can detect and track the MPP in a very short time, and its accuracy outperforms the other methods in terms of detecting the GMPP. The proposed ISSA algorithm has a higher speed and the convergence rate than the other traditional algorithms. https://ieco.usb.ac.ir/article_5540_805069a7d5fdbece74c82733242cca46.pdf