Real-time bald eagle search approach for tracking the maximum generated power of wind energy conversion system

Abstract

The operation of the wind energy conversion (WEC) system is affected by the weather conditions as its generated power is dependent on the wind speed. It is essential to monitor the maximum generated power from the WEC system, this requires installing a maximum power point tracker (MPPT). This paper proposes a recent metaheuristic optimization approach named bald eagle search (BES) optimizer to design MPPT for WEC system operated at variable wind speed for tracking its global maximum power. The BES is selected as it can explore new search spaces, this helps in enhancing its divergence to avoid stuck in local optima and guarantee global solution. The proposed BES controls the DC-DC boost converter MOSFET at the terminals of a permanent magnet synchronous generator (PMSG) driven by wind turbine (WT). The BES adapts the MOSFET duty cycle such that the generated output power is enhanced. The proposed tracker is investigated on WEC operated at constant wind speed, variable wind speed, and real measured wind speed collected via Al-Jouf stations affiliated to the Saudi Arabia meteorological authority. Comparison to other approaches of particle swarm optimizer (PSO), aquila optimizer (AO), dingo optimization algorithm (DOA), sparrow search algorithm (SSA), and sooty tern optimization algorithm (STOA) is presented. Moreover, set of nonparametric tests such as Wilcoxon sign-rank test, Friedman test, ANOVA table, and Multiple comparison test are performed for statistical justification. According to the results, the BES has Friedman average rank of 1.1; meanwhile, the followed technique (DOA) has an average rank of 2.0250 that proves the superiority of the optimizer. Furthermore, the attained p-value of 1.6419e-54 based on the ANOVA table affirms the existence of significant differences among the algorithms. Therefore, the obtained results confirmed the competence and superiority of the proposed BES-MPPT in extracting the best global maximum power in all studied cases.