Energy harvesting enhancement: A roadmap for systematically tuning controllers applied on synchronous generators of wind turbines

This work presents a roadmap for tuning field oriented control (FOC) for permanent magnet synchronous generator (PMSG)-based wind turbines. A detailed discussion about how to design meta-heuristic optimizers for this task is presented, providing systematic rules to ensure that the tuning procedure returns a set of gains that result in feasible optimized controllers. Ten popular nature-inspired optimizers are implemented at the core of the controller tuning method. The 10 optimized controllers are applied in the system considering a highly stochastic wind speed profile, generated using the Shinozuka method and Kaimal spectrum under intense turbulence. Among them, the ant lion optimizer (ALO) provided the best set of gains for FOC. Compared to the tenth algorithm in the rank, the ALO-based controller ensured a reduction of 96.78% and 90.27% of mean absolute error and root mean squared error, respectively. The findings of this work contribute to the automation of the controller tuning of PMSG‐based wind turbines, enhancing its power generation with more precise current tracking using optimized FOC.