Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Fan active power tracking method based on dynamic multi-model prediction controller

A predictive controller and model prediction technology, which is applied in the control of wind turbines, motors, wind turbines, etc., can solve the problems of difficult and accurate model establishment, large accuracy relationship, and large influence of input wind speed.

Active Publication Date: 2021-04-20
BEIJING HUANENG XINRUI CONTROL TECH
View PDF15 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The PI control strategy is mainly to adjust the pitch angle through the PI controller to keep the generator speed at the rated speed when the wind speed is above the rated wind speed, and the electromagnetic torque controller cooperates with the generator speed to realize the power tracking of the rated power; the gain scheduling PI control strategy is to solve Under different wind speeds, the output power of the generator has different sensitivity to the pitch angle, so the gain compensation and scheduling of the PI controller are performed based on the sensitivity; the traditional model predictive control strategy can be based on the fan model for real-time optimal control to meet the power requirements. Output requirements, but the accuracy and precision of the control are closely related to the accuracy of the model. At the same time, because the states of the fans are coupled with each other and are greatly affected by the input wind speed, the model is difficult to establish accurately. If the model is more realistic If the model gap is large, the power of the fan will not meet the control requirements

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Fan active power tracking method based on dynamic multi-model prediction controller
  • Fan active power tracking method based on dynamic multi-model prediction controller
  • Fan active power tracking method based on dynamic multi-model prediction controller

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0084] In order to enable those skilled in the art to better understand the technical solution of the present disclosure, the present disclosure will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0085] Such as figure 1 As shown, a dynamic multi-model predictive controller-based fan active power tracking method S100, the method includes:

[0086] S110. Establish each nonlinear model of the fan, and respectively linearize and discretize each of the nonlinear models at each operating point to obtain a linear multi-condition multi-model of the fan;

[0087] S120. Build a model predictive controller according to the linear multi-working-condition multi-model of the fan;

[0088] S130. Update and correct the parameters of the model in the model predictive controller according to the actual operating state of the wind turbine, and build a dynamic multi-model predictive controller;

[0089] S140. Based on an actual ex...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a fan active power tracking method based on a dynamic multi-model prediction controller. The method comprises the steps that nonlinear models of a fan are built and subjected to linearization and discretization at working condition points, and a linear multi-working-condition multi-model of the fan is obtained; a model prediction controller is built according to the linear multi-working-condition multi-model of the fan; parameters of models in the model prediction controller are updated and corrected according to the actual running state of the fan, and a dynamic multi-model prediction controller is built; and the effectiveness of the dynamic multi-model prediction controller in the aspect of fan active power tracking is verified based on an actual experiment platform or high-fidelity simulation software. The defects of a traditional fan active power tracking strategy are overcome, fluctuation during fan output power tracking is restrained on the basis of the dynamic multi-model prediction controller, and the economic performance of the fan is improved.

Description

technical field [0001] The disclosure belongs to the technical field of wind turbine active power tracking control, and in particular relates to a wind turbine active power tracking method based on a dynamic multi-model predictive controller. Background technique [0002] Since the energy output by the wind turbine comes from the wind in the environment, and the wind in the environment is difficult to be accurately predicted, and there will be turbulence and rapid changes, the output power of the wind turbine is prone to fluctuations, and it is difficult to accurately control the power of the wind turbine , not only affects the economic operation of the wind turbine, but also affects the frequency of the power grid, posing a huge challenge to the operation of the wind turbine and the power grid. [0003] Therefore, it is necessary to find effective means to improve the power tracking ability of wind turbines, reduce power fluctuations, and improve the quality of wind energy ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): F03D7/00
CPCY02E10/72
Inventor 曾凡春江灿安赵霞高越杨继明
Owner BEIJING HUANENG XINRUI CONTROL TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products