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基于模型预测控制的风电场有功功率波动抑制优化方法研究

秦晓栋 宋瑞军 吕杰 周文奇 姚鹏 魏赏赏

综合智慧能源2025,Vol.47Issue(7):23-31,9.
综合智慧能源2025,Vol.47Issue(7):23-31,9.DOI:10.3969/j.issn.2097-0706.2025.07.003

基于模型预测控制的风电场有功功率波动抑制优化方法研究

Research on an optimization method for suppressing active power fluctuations in wind farms based on model predictive control

秦晓栋 1宋瑞军 1吕杰 1周文奇 1姚鹏 2魏赏赏3

作者信息

  • 1. 内蒙古电力集团经济技术研究有限责任公司,呼和浩特 010010
  • 2. 超滑科技(佛山)有限责任公司,广东 佛山 528225
  • 3. 河海大学 新能源学院,江苏 常州 213200
  • 折叠

摘要

Abstract

Due to the spatial distribution characteristics of wind turbines and the randomness of wind speed,wind farm power output exhibits significant intermittency and fluctuation,which undermines the grid-friendly operation capability of wind farms.To address this issue,an optimization method for suppressing wind farm power fluctuations based on model predictive control(MPC)coupled with wake effect was proposed.A power output prediction model under varying wind speeds and directions was established using a coordinate transformation method,and wind speed forecasting was performed using a least squares support vector machine(LS-SVM).Within the MPC framework,a multi-dimensional coupled optimization objective was formulated by integrating the wake effect,wind direction deviation,and turbine constraints.An optimization problem considering the variance of active power output was then solved.The case study showed that compared with the proportional distribution method,the proposed approach reduced the average relative deviation and root mean square deviation of active power output by 93%and 97%,respectively,verifying the effectiveness of the multi-dimensional coupling model in fluctuation suppression.

关键词

风电场/尾流调控/波动抑制/模型预测/有功功率/机组约束/多维耦合

Key words

wind farm/wake control/fluctuation suppression/model prediction/active power/turbine constraints/multi-dimensional coupling

分类

能源科技

引用本文复制引用

秦晓栋,宋瑞军,吕杰,周文奇,姚鹏,魏赏赏..基于模型预测控制的风电场有功功率波动抑制优化方法研究[J].综合智慧能源,2025,47(7):23-31,9.

基金项目

国家自然科学基金项目(52406233,52106239) (52406233,52106239)

中国博士后基金项目(2024M750738) (2024M750738)

常州市科技应用基础研究项目(CJ20240095) (CJ20240095)

江苏省碳达峰碳中和科技创新专项(BT2024004)National Natural Science Foundation of China(52406233,52106239) (BT2024004)

China Postdoctoral Science Foundation(2024M750738) (2024M750738)

Changzhou Applied Basic Research Program(CJ20240095) (CJ20240095)

Jiangsu Carbon Neutrality Innovation Project(BT2024004) (BT2024004)

综合智慧能源

2097-0706

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