Grid-connected Control Based On The Brushless Double-Fed Machine Wind Power Generator

Brushless double-fed machine is a new type of induction machine that can operate in both asynchronous and the synchronous mode. It has the robust mechanical characteristics together with controllable speed and power factor, a relatively low rating power converter. These benefits attract more and more researcher's attention. A comprehensive research on the BDFM with cage rotor is developed,its structure characteristics and principals are discussed.The dissertation focus on the grid-connected system based on brushless doubly-fed machine wind power generator. The paper unifies the domestic and overseas related regulations and the literature to discuss. First, the different types of grid-connected generator is introduced,refer to the state of development,the source and the significance of the research. The principle , characteristic of structure and the lauch situatuion of BDFM is introduced next. Based on the tatic equivalent circuit model of the BDFM, the relations of power allocation in the stator winding and the power flow can be abtained ,when the machine is at events of operating state or generating state.A simulation model of BDFM is constructed,and use to simulate to the various operation.Neural networks and BP algorithm is introduced, by the way of suppling the introduction of theory to the grid-connected control.The emphasis is focused on grid-connected control based on the brushless doubly-fed machine.The strategy based on the brushless doubly-fed machine is discussed.In the generating state, the mathematical model of BDFM is stochastically changeable and a MIMO system. Compare to the other machine, the grid-connected process of the brushless doubly-fed machine is more complex. This novel dynamic decoupling control method for MIMO nonlinear system based on recurrent wavelet networks is presented in this paper.It adopts dispersive neural networks control structure and utilizes recurrent wavelet networks as decoupling identifier and PID neural network as controller respectively. The decoupling identifier identifies the MIMO nonlinear system and feedback the sensitivity information for PID controller through on-line learning. Simultaneously PID controller updates the weights and adjusts the system actively.Benefited from wavelet ability being non-linear mapping,it shows excellent temporal-frequency localization property,while it possesses such merits as powerful ability of mapping nonlinear systems,capturing the dynamic behavior of the system etc,thus this network converges quickly with high precision and robustness.The research work has been supported by the important research projects funded by national natural science foundation.The project name is The Research of Distributed Wind-Solar Hybrid Generating System.Its number is 60534040.