Tracing optimization control method for wind turbine

A wind turbine, optimized control technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as dependence on model parameters, difficult control requirements of wind turbine model systems, poor robustness, etc.

Inactive Publication Date: 2015-03-11
BEIJING JIAOTONG UNIV
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Problems solved by technology

[0003] The traditional fan control method is PID control. This method is widely used in the industrial field. It has the characteristics of simple structure, good stability and high reliability. Under the simple wind condition of a single wind speed, PID control can obtain better control effect. , but this kind of controller depends too much on the model parameters of the control object, and has poor robustness. It is difficult to meet the control requirements of the fan model system with strong nonlinear characteristics affected by the wind speed.
In modern control strategies, robust adaptive control is the most widely used and highly practical control method, but it also has its own shortcomings, that is, in order to pursue high stability of the system, it will lose control accuracy and energy consumption. advantages, need to be used in combination with other control methods

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  • Tracing optimization control method for wind turbine
  • Tracing optimization control method for wind turbine
  • Tracing optimization control method for wind turbine

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[0029] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0030] The problem of optimal control of linear systems has been solved in the 1960s, and due to the complexity of nonlinear systems, most methods are to linearize the nonlinear system and then process it, which will lose a lot of system information. At the same time, the effect of optimization is relatively poor, and the most important problem is that there is no corresponding theoretical argument for the stability of the optimization algorithm. The invention provides a practical optimization control technology, avoids actual system processing, and only optimizes the linear part of the system controller, and realizes precise tracking control on this basis, and theoretically verifies the stability of the optimization algorithm.

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Abstract

The invention provides a tracing optimization control method for a wind turbine. According to the method, through calculating an estimated value of the air power torque of a wind wheel and a measuring value of the rotating speed of the wind wheel or a power generator, a non-linear self-adaptive control algorithm is designed; the controller linear part is subjected to optimization design; and the feasibility of the controller optimization is theoretically demonstrated.

Description

technical field [0001] The invention relates to the technical field of wind power generation operation control, in particular to a tracking optimization control method of a wind turbine. Background technique [0002] With its advantages of wide application range and high rate of return, wind power has been highly valued by various countries in recent years and has become a new energy technology with great potential. High rate of return wind energy utilization goals. In the past few years, China's wind power has developed at an annual growth rate of more than 100%. It has generally mastered the development technology of large-scale units and is promoting the construction of offshore wind farms. Therefore, in the face of a rapidly expanding development scale, how to ensure maximum wind power output on the basis of existing input costs is an important research topic to improve the utilization efficiency of existing wind turbines, reduce relative costs, and achieve sustainable ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
Inventor 刘峰李鹏宋永端李丹勇陈丽红
Owner BEIJING JIAOTONG UNIV
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