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

doi:10.3969/j.issn.2097-0706.2025.07.003

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

• 博弈论与电力市场决策 • 上一篇下一篇

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¹(), 宋瑞军¹(), 吕杰¹, 周文奇¹, 姚鹏²(), 魏赏赏³^,^*()

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

收稿日期:2025-02-12 修回日期:2025-03-10 出版日期:2025-07-25
通讯作者: ^*魏赏赏（1990），男，副教授，博士，从事风光新能源、储能以及多能互补系统等方面的研究，weishsh@hhu.edu.cn。
作者简介:秦晓栋（1975），男，高级工程师，硕士，从事电网、新能源、储能等项目的设计评审、专题研究、科技创新等方面的研究，qxdnj@foxmail.com；
宋瑞军（1990），男，工程师，硕士，从事电网、新能源、储能等项目的设计评审、专题研究、科技创新等方面的研究，398449801@qq.com；
姚鹏（1989），男，工程师，硕士，从事风电机组传动链在线修复、监测及润滑系统优化等方面的研究，115953864@qq.com。
基金资助:
国家自然科学基金项目(52406233);国家自然科学基金项目(52106239);中国博士后基金项目(2024M750738);常州市科技应用基础研究项目(CJ20240095);江苏省碳达峰碳中和科技创新专项(BT2024004)

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

QIN Xiaodong¹(), SONG Ruijun¹(), LYU Jie¹, ZHOU Wenqi¹, YAO Peng²(), WEI Shangshang³^,^*()

1. Inner Mongolia Electric Power Group Economic and Technological Research Company Limited，Hohhot 010010，China
2. Chaohua Technology （Foshan） Company Limited，Foshan 528225， China
3. School of Energy and Electrical Engineering， Hohai University，Changzhou 213200， China

Received:2025-02-12 Revised:2025-03-10 Published:2025-07-25
Supported by:
National Natural Science Foundation of China(52406233);National Natural Science Foundation of China(52106239);China Postdoctoral Science Foundation(2024M750738);Changzhou Applied Basic Research Program(CJ20240095);Jiangsu Carbon Neutrality Innovation Project(BT2024004)

摘要/Abstract

摘要：

风电机组的空间分布特性以及风速的随机性，导致风电场出力具有显著的间歇性和波动性，削弱了风电场的电网友好型运行能力。为此，提出一种基于模型预测控制与尾流效应耦合的风电场波动抑制优化方法。采用坐标变换法构建了不同风速大小与方向下风电场有功功率出力预测模型，结合最小二乘支持向量机进行风速预测。在模型预测控制框架中集成尾流效应、风向偏差及机组约束的多维耦合优化目标，求解考虑风电场有功功率出力方差的优化问题。案例仿真表明，所提方法较比例分配法有功功率平均相对偏差与均方根偏差分别降低了94%和97%，验证了多维耦合模型对波动抑制的有效性。

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

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.

Key words: wind farm, wake control, fluctuation suppression, model prediction, active power, turbine constraints, multi-dimensional coupling

中图分类号:

TK08：TM614

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.

QIN Xiaodong, SONG Ruijun, LYU Jie, ZHOU Wenqi, YAO Peng, WEI Shangshang. Research on an optimization method for suppressing active power fluctuations in wind farms based on model predictive control[J]. Integrated Intelligent Energy, 2025, 47(7): 23-31.

图/表 12

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表1

不同优化方法下风电场波动指标比较

优化方法	$ε M R E$	$ε M S E$ /MW
1	16.90	6.55
2	262.00	240.05

表1

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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

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

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