A parallel Archimedes optimization algorithm based on Taguchi method for application in the control of variable pitch wind turbine

Archimedes optimization algorithm (AOA) is a recent metaheuristic algorithm that offers several advantages, including a few parameters, an easy-to-understand interface, and easy implementation. Still, some drawbacks exist, e.g., lack of diversity for search-exploring capacity, drop-trap local optimum. This study suggests a new variant of AOA based on the parallel and Taguchi method (TPAOA) for the global optimization problems and the wind turbine parameter adjust-tuning variable pitch controller problem. The parallel mechanism with communication strategy and the Taguchi orthogonal combination deal with the AOA’s drawbacks. The experimental results show that the proposed algorithm is more competitive than the other algorithms under the CEC2017 test suite. The wind turbine problem of parameter tuning difficulty of variable pitch controller is solved by applying the TPAOA. Compared solution results show that the TPAOA proves the feasibility smooth the output power of wind turbines and reducing the impact of wind speed fluctuations on the power grid, which has high feasibility.