Wind Energy Conversion System Oscillations Damping Using a Proposed Mutation Operator for LBBO-DE Algorithm

Damping the oscillations of the wind energy conversion system of a grid connected Doubly Fed Induction Generator (DFIG) is the main objective in this article. PID controller is commonly used in many industrial process, but its parameter tuning is a challenging task. The PID parameters values are not optimally adjusted by conventional methods being used such as frequency response. Such that, a new algorithm is used which is hybrid Differential Evolution with Linearized Biogeography-Based optimization (LBBO-DE). Linearized-Biogeography Based optimization (LBBO) is a new version of Biogeography-Based optimization (BBO). Cauchy and Gaussian mutation operators are proposed to modify the mutation equation. The algorithm LBBO-DE with the proposed mutation operators had been tested with 53 benchmarks and then compared with the 40 algorithms that have been accepted for 2005 and 2011 Congress on Evolutionary Computation (CEC). The proposed algorithm achieved advanced rank between them and gave better results and lower variance, which proved to have competitive performance with state-of-the-art evolutionary algorithms. A simulation model is used to show the oscillation damping in case of symmetrical and asymmetrical fault occurrence at the grid connected to WECS-DFIG. As a result, the LBBO-DE with Gaussian mutation equation is used to optimize the controller parameters for achieving oscillations damping. The simulation results of direct-drive PMSG model is also used for the oscillations damping purpose under the case of wind speed variation, which is done by the LBBO-DE.