Research On Intelligent Sliding Mode Control Of Large-scale Wind Turbines

Energy and environment are pressing problems that must be settled by human beings for future survival and development. Wind power has preferable economic and social benefits because of its cleanliness and free pollution, short construction period, flexible investment and few occupation of land. At present, research of wind turbine in china is very weak and many advanced wind turbine technologies are not solved such as high power capacity, pitch control and variable speed constant frequency etc. Thus, almost all advanced large-scale wind turbines are imported from overseas. In all, indepth research of wind turbine technology has very important meaning for persistent wind turbine development and home production.The research difficulties and hot pots of wind power are focused on high power capacity, advanced control and optimization etc. Becaust the wind energy has lower density, instability and randomicity, wind turbines have strong nonlinear multivariable with many uncertain factors and disturbances, control is crucial to the efficiency and reliability of wind turbines.This thesis first makes a deep research to wind-power system's mathematical model and its control theory.Then by using Sliding Mode Control theory, this article proposes a series of control principles to overcome the system parameter variation and the outside perturbation adverse effects. In order to solve the SMC theory's problems,such as buffeting,static error and the require of system parameter range,this article takes the SMC theory,the fuzzy theory and the neural network theory together ,and combine them to form some new control theory.With using these theories in the wind power generation control and simulating,some wonderful result is obtained.All this may provide the reference for practical application.The below is the main contents:(1)Nonlinear mathematical model of large-scale wind turbines is established by analysis modeling to describe the dynamic behavior of complete wind turbines.Wind wheel is analysis modeled and simulated according to the theory of the blade's chip and the the theory of vortex for amendment.The lift force rate and resisitance rate are selective analysised.In the introduction of transmission system, transmission system's rigid axis model and the flexible shaft model have been studied.(2)Integral fuzzy sliding mode controller is proposed to conquer the traditional SMC method's nature defect.System's output function is replaced by a assistant output function,which has none zero-point and match up to the hope system output.A integral item is added to the sliding mode surface to force the static error into zero.In the uncertain parameter's upper boundary unknown situation, according to the sliding mode reach condition,switch gain is estimated by using fuzzy rule,and the switch function is replaced by saturation function in order to ease the high frequency concussion.This control principle is applied to the wind power system's speed trace control and is proved to well deal with the strong uncertainty.(3)A adaptive variable structure neural network controller is proposed for the pitch control problem,using Feedback linear method and based on the adaptive neural network theory,which can perfect control the system with no mathematic model.And NN's fast learning algorithm is studied mainly.The controler's stability and Convergence are well studied too.A new design method of self-learning SMC based on NN has been developed ,followed by a detailed algorithm analysis for three-tier structure of adaline NN.Finally,an application example in the pitch control is given.(4)In the last chapter, the basic principles for DFIG is analysized first, then a mathematical model based on two-phase syncharonous rotation coordinates is deduced,which has been transformed from three-phase static coordinate.To achieve the DFIG's stator voltage constant control objective,a sliding mode controller has been designed finally for the machine side converter, using Lyapunov stable theorem to guarantee its accessibility of sliding mode surface in finite time.