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Simulation of Metaheuristic Intelligence MPPT Techniques for Solar PV Under Partial Shading Condition
S Odofin, Hussaian Basha C, , , Ch Hussaian Basha, , , Odofin S.
Published in Springer Singapore
Volume: 1048
Pages: 773 - 785
The nonlinear characteristics of solar PV consist of different MPPs under the partial shading condition. Hence, it is difficult to find out true MPP. The conventional MPPT methods are not giving an accurate position of MPP. In this work, two global metaheuristic optimization techniques are simulated and the comparative analysis is carried out in terms of tracking speed, steady-state oscillations, algorithm complexity, periodic tuning, and dynamic response. Those are the Cuckoo Search Optimization (CSO) and Particle Swarm Optimization (PSO) MPPT methods used to extract the maximum power of solar PV under partial shading condition. The Matlab/Simulink is used to evaluate performance results of CSA and PSO MPPT techniques. © 2020, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing Soft Computing for Problem Solving
PublisherData powered by TypesetSpringer Singapore
Open Access0
Authors (4)