动态触发模型预测控制在含风电电力系统自动发电控制中的应用

赵熙临; 李金星

doi:10.19725/j.cnki.1007-2322.2023.0092

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动态触发模型预测控制在含风电电力系统自动发电控制中的应用

新能源电力系统 | 更新时间：2025-10-13

- 动态触发模型预测控制在含风电电力系统自动发电控制中的应用
- Application of Dynamic Trigger MPC in AGC Containing Wind Power
- 现代电力 2025年42卷第2期页码：220-229
- 作者机构：
  
  湖北工业大学电气与电子工程学院, 湖北省武汉市430068
- 作者简介：
  
  [ "赵熙临(1969)，男，博士，教授，通信作者，研究方向为电力系统优化与控制，E-mail：zhaoxl@mail.hbut.edu.cn" ]
  [ "李金星(1998)，男，硕士研究生，研究方向为电力系统优化与控制、新能源发电，E-mail：2910895913@qq.com" ]
- 基金信息：
  
  湖北省重点研发计划项目(2021BAA193)。
- DOI：10.19725/j.cnki.1007-2322.2023.0092
  中图分类号： TM73
- 收稿：2023-03-10，
  
  录用：2023-09-28，
  
  纸质出版：2025-04-10
- 稿件说明：
移动端阅览
赵熙临, 李金星. 动态触发模型预测控制在含风电电力系统自动发电控制中的应用[J]. 现代电力, 2025,42(2):220-229.

Xilin ZHAO, Jinxing LI. Application of Dynamic Trigger MPC in AGC Containing Wind Power[J]. Modern electric power, 2025, 42(2): 220-229.
赵熙临, 李金星. 动态触发模型预测控制在含风电电力系统自动发电控制中的应用[J]. 现代电力, 2025,42(2):220-229. DOI： 10.19725/j.cnki.1007-2322.2023.0092.

Xilin ZHAO, Jinxing LI. Application of Dynamic Trigger MPC in AGC Containing Wind Power[J]. Modern electric power, 2025, 42(2): 220-229. DOI： 10.19725/j.cnki.1007-2322.2023.0092.

摘要

高比例可再生能源并网增大了电力系统的供需不确定性，需要自动发电控制（automatic generation control

AGC）方法在应对不同的调频需求时更具针对性。文中以含风电电力系统为研究对象，首先，通过构建互联电网AGC模型，分析了基于模型预测控制（model predictive control

MPC）的系统控制流程；其次，针对传统MPC在线计算复杂度过高的问题，引入条件触发策略以降低MPC执行优化计算的频次；并考虑到系统不同状态下调频需求存在的差异，设计了能跟随系统状态进行动态调整的触发规则，以获得更好调频控制效果；最后，仿真验证了所提方法在保证控制性能的基础上能有效降低系统在线计算复杂度，并在面对不同的调频需求时具有更好的系统稳定性。

Abstract

The integration of a high proportion of renewable energy into the grid amplifies the uncertainty in supply and demand of the power system

which requires an more targeted automatic generation control (AGC) methods to meet different FM needs. In this paper

the wind power system is taken as the research object. The system control process based on model predictive control (MPC) is first analyzed by constructing the AGC model of interconnected power grid. Then

to address the issue of high computational complexity of traditional online MPCS

a conditional trigger strategy is introduced to reduce the frequency of optimal computation. Trigger rules and thresholds are designed to dynamically adjust the different frequency modulation requirements of various states within the system

so as to achieve optimal trigger and control effects. Finally

the simulation results demonstrate that the proposed method can effectively reduce the online computing complexity of the system while ensuring the control performance at the same time

and it exhibits better system stability in respond to various frequency modulation requirements.

关键词

Keywords

references

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