Whale optimization algorithm-based Sugeno fuzzy logic controller for fault ride-through improvement of grid-connected variable speed wind generators

Due to the extensive penetration of wind power plants (WPPs) into the grid, grid codes have been imposed such that the WPPs stay linked to the grid during faults for a period to maintain the grid stability. This paper designs optimal Sugeno fuzzy logic controllers (FLCs) to improve the fault ride-through (FRT) ability of grid-connected WPPs. The meta-heuristic algorithm, whale optimization algorithm (WOA), is utilized to design the control rules and the Gaussian memberships of eight Sugeno FLCs, simultaneously, by minimizing the high dimensional multi-objective fitness function. The WOA-FLCs and the grid-connected gearless permanent magnet synchronous generator driven by a variable-speed wind turbine (VSWT-PMSG) are modeled using PSCAD/EMTDC environment. The effectiveness of the FRT ability of grid-connected VSWTPMSG is investigated during balanced and unbalanced grid fault conditions. The simulation results of using WOA-FLCs revealed fast time response, less overshoot, and small steady-state error compared with those achieved by using a genetic algorithm (GA) and grey wolf optimizer (GWO).