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- W3146059728 abstract "A novel chaotic small-world optimization algorithm based on real-coding was proposed by using the chaotic map to generate an initial node set and construct operators.The algorithm was tested with other 3 excellent algorithms to optimize several complex functions indicates that it could effectively avoid local minimum and quickly find out the optimum value.Applying the method to synchronous speed control when variable-pitch wind turbines startup to grid integration,a neural network model predictive control strategy was proposed,which the predictive model was built by neural network modeling based on field data.Simulation and actual test results show that the strategy can forecast the change of generator rotational speeds according to the wind speed disturbance,making the controller act ahead to eliminate the impact of system delay.Furthermore,the system output can track the reference trajectory well and ensure the stability for grid-connected wind power." @default.
- W3146059728 created "2021-04-13" @default.
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- W3146059728 date "2012-01-01" @default.
- W3146059728 modified "2023-09-25" @default.
- W3146059728 title "Neural Network Predictive Control of Variable-pitch Wind Turbines Based on Small-world Optimization Algorithm" @default.
- W3146059728 hasPublicationYear "2012" @default.
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