Archimedes optimization algorithm based maximum power point tracker for wind energy generation system

Abstract

Improving the operation of wind energy generation system is a big challenge especially when it operates under unstable weather conditions. Therefore, installing a tracker for monitoring the maximum power expected to be generated from the wind energy system is essential, this controller is known as maximum power point tracker (MPPT). Hill climbing based approaches were applied for simulating the tracker, however they have limitations in tracking speed and efficiency. This paper proposes a recent efficient approach of Archimedes optimization algorithm (AOA) for simulating MPPT installed with the wind energy generation system. The constructed system composes wind turbine (WT) connected to a permanent magnet synchronous generator (PMSG), the AC output power from the generator is converted to DC via 3-phase rectifier, the DC voltage is the input of boost converter which is controlled via its MOSFET duty cycle. The designing process is presented as an optimization problem considering the electrical output power from the system as the target. The proposed AOA tunes the converter duty cycle to maximize the output power. Three scenarios are followed in this work which are fixed wind speed, variable wind speed, and real wind speed recorded at four sites in Saudi Arabia (Sakaka, Riyadh, Jeddah, and Jizan). The obtained results via the proposed approach are compared with the results obtained via cuckoo search (CS), grasshopper optimization algorithm (GOA), and electric charged particle optimization (ECPO). The results confirmed the robustness of the proposed AOA-MPPT in achieving the best performance of wind energy generation system.