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MPPT-Based Particle Swarm and Cuckoo Search Algorithms for PV Systems‏

Research Authors
Farag K. Abo-Elyousr, Alaaeldin M. Abdelshafy, Almoataz Y. Abdelaziz
Research Department
Research Year
2019
Research Journal
Part of the Green Energy and Technology book series (GREEN)
Research Publisher
Springer, Cham
Research Vol
NULL
Research Rank
1
Research_Pages
pp 379-400
Research Website
https://link.springer.com/chapter/10.1007/978-3-030-05578-3_14
Research Abstract

The increased penetration of photovoltaics (PVs) within power system on both islanded and grid-tied inverters encourages researchers to develop several maximum power point tracking (MPPT) algorithms. The main target of this chapter is to enable PV systems to participate effectively in power systems by harvesting the possible PV maximum power from a solar panel. Two evolutionary algorithms for MPPT were developed and compared, namely particle swarm optimization (PSO) algorithm and the recent cuckoo search (CS). The proposed controllers employ DC/DC boost converter to harvest the maximum power available from the PV resource. System programming and modeling is done using MATLAB/SIMULINK software. The obtained results are compared with the mature perturb and observe (P&O) algorithm under several operating conditions such as irradiance, temperature, and partial shading. The developed controllers require only the PV voltage and current, which makes them economically cost and attractive in the PV transient and steady-state operating conditions.