Whale optimization algorithm-based Sugeno fuzzy logic controller for fault ride-through improvement of grid-connected variable speed wind generators. (January 2020) - Qais, Mohammed H.; Hasanien, Hany M.; Alghuwainem, Saad
Abstract: 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 VSWT-PMSG 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). Highlights: This paper designs optimal Sugeno FLCs using whale optimization algorithm (WOA). WOA-FLC is used to improve the fault ride-through (FRT) ability of wind power plants. The FRT of grid-tied PMSG is investigated during balanced and unbalanced faults. The results of WOA-FLC are compared with the results of GA-FLC and GWO-FLC.