Effective wind speed obtaining method of wind generating set based on High-Gain observer

Abstract

The invention discloses an effective wind speed obtaining method of a wind generating set based on a High-Gain observer. The effective wind speed obtaining method includes the following steps that firstly, a sensor is used for collecting a rotor speed omega r of a wind wheel of the wind generating set and data are filter, sorted and preprocessed, high-frequency disturbance from a wind power plant circumstance and a wind generating set tower body is eliminated, mechanical and electrical features of the wind generating set are combined to set up the High-Gain observer and finally, an effective wind speed estimation value is obtained through a Cp secondary surface fitting polynomial function. The effective wind speed estimation value serves as the important reference input of a wind generating set controlling system, is applied to torque control, pitch angle control and yaw control of the wind generating set and also can be applied to analysis of reliability and economic benefits of a wind power station and estimation and analysis on influences on a power system by the wind power station which accesses to the power grid. The effective wind speed obtaining method of the wind generating set based on the High-Gain observer has great scientific significance and application value in planning and design of grid connection of the wind power station, analysis and calculation on safety and stability of the power grid including wind power and configuration and setting of a protection and safety automatic device.

Description

technical field [0001] The invention belongs to the technical field of wind power generating set control, and in particular relates to an effective wind speed acquisition method. Background technique [0002] Wind energy is a green energy, and wind power generation is of great significance to protecting the ecological environment and improving the energy structure. The wind turbine is a continuous stochastic nonlinear multivariable system, and the timely, accurate and effective control technology scheme is the key to the safe and efficient operation of large-scale grid-connected wind turbines. In actual operation, different wind farms are very different in terms of topography, model, scale, unit layout, and wind speed distribution, and wind speed and wind speed distribution are important factors that determine the operating characteristics of wind turbines in wind farms. Since the wind turbine is in a three-dimensional time-varying wind field environment, the wind speed and...

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Problems solved by technology

However, because the SVM algorithm is difficult to implement on large-scale training samples, the parameters are not easy to adjust, and the amount of calculation increases sharply as the number of related parameters increases.

Another example is to use the neural network to model the non-linear data of wind turbines, and adjust its own network structure and connection weights through repeated learning. However, the structure of the neural network is complex, and it is easy to fall into local minima, and over-learning problems are more likely to occur. It leads to a decrease in the generalization ability and is not suitable for the control system design of large wind turbines

If the Kalman filter is used for wind speed estimation and applied to the speed and pitch angle control of variable-speed wind turbines, since the Kalman filter is based on the linearized model of the nonlinear system at the operating point for state estimation, the linearized model At each sampling moment, the parameters must be recalculated and updated. When the wind speed changes in a large range, it is difficult for the Kalman filter to work in real time, resulting in a large amount of calculation in the actual work of the control system and reducing the operation of the entire wind turbine control system. speed, the control is not timely, resulting in a large perturbation of the output power of the generator, which affects the stability of the power grid

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