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Improved Atom Search Optimizer of Offshore Wind Power for Fault Ride-through Capability Enhancement

This paper designs an improved atom search optimizer (IASO) to enhance the fault ride-through (FRT) ability of offshore wind power. Based on the proposed IASO, the Euclidian distance ratio of original atom search optimizer (ASO) is adopted to realize dynamical update with iterations. It can effectively and efficiently acquire a proper trade-off between global exploration and local exploitation based on the repulsion and attraction intensities variation among various atoms. Then, IASO is adopted for optimal tuning of PID control parameters of doubly-fed induction generator (DFIG) in offshore wind farm to enhance its FRT capability, which is of great importance to assure a stable and reliable operation under diverse faults scenarios. Case studies under Matlab/Simulink environment are carried out to validate its specific performance compared against that of the other well-known meta-heuristic methods, namely, particle swarm optimizer (PSO).