A new MBF-PSO for improving performance of DFIG connected to grid under disturbance

Renewable energy is one of the most important sources used for the production of electrical energy due to its natural availability and lack of harmful effects on the environment. From these sources, wind energy is often located in remote areas where exposure to disturbance sometimes affects its functioning. This paper consists of two parts. In the first, we propose a new Modified Bacterial Foraging-Particle Swarm Optimisation (MBF-PSO). This is improved by new inertia Weight (w_new), using mixed parameters of the PSO and BF to find a new formula for w_new. In the second part, we present the influence of different sorts of disturbance on the performance of a Doubly-Fed Induction Generator (DFIG) driven by the Wind Turbine (WT) with variable speeds and connected to the grid. Three optimisation strategies are investigated here for tuning the PID controller of DFIG. Finally, the results of the proposed strategies show that the MBF-PSO strategy is most effective in the stabilisation and improves the quality of the power.