基于风速预测模型的风电一次调频仿真研究

doi:10.16182/j.issn1004731x.joss.21-1263

摘要/Abstract

摘要：

为进一步提高风速预测精度，考虑数据内部结构性与外部影响因素耦合性叠加特征，以及风电机组功率特性，构建逆向前馈神经网络自回归移动平均模型(back propagation-autoregressive integrated moving average model, BP-ARIMA)，并对风电场风速进行预测仿真，通过与实际数据对比分析，验证了所建模型具有较高预测精度。在所建预测模型基础上，基于风力发电机组典型功率特性曲线，统筹考虑储能装置容量优化配置与风电机组的致稳性问题，应用MATLAB-SIMULINK平台进行风电机组一次调频仿真。结果显示：一次调频控制策略的频率调节能力相较于常规超速减载调频控制可至少提高十个百分点。

关键词: 风速预测, 模型, 一次调频, 储能装置, 仿真分析

Abstract:

To furtherly improve the accuracy of wind speed prediction, considering the coupled comprehensive features of data internal structure external influencing factors, and the characteristics of wind turbines power, a BP-ARIMA combined prediction model is constructed and the wind speed of wind farms is simulated. Compared with the actual data, the high prediction accuracy of the model is verified. Bases on the curve of typical power characteristic of wind turbine, the optimal configuration of energy storage device capacity and the stability of wind turbine are considered, and the MATLAB-SIMULINK platform is applied to simulate the primary frequency regulation of wind turbine, and the results show that the frequency regulation capability of the primary frequency modulation control strategy, compared with the conventional over-speed and load-shedding frequency control strategy, can be improved by at least ten percentage.

Key words: wind speed prediction, model, primary frequency regulation, energy storage device, simulation analysis

中图分类号:

TP391

赵振宇,马旭,包格日乐图 . 基于风速预测模型的风电一次调频仿真研究[J]. 系统仿真学报, 2022, 34(10): 2233-2243.

Zhenyu Zhao,Xu Ma,Geriletu Bao . Wind Power Primary Frequency Regulation Simulation Based on Wind Speed Prediction Model[J]. Journal of System Simulation, 2022, 34(10): 2233-2243.

图/表 17

图1

表1

图2

图3

图4

图5

图6

图7

表2

图8

表3

图9

图10

图11

图12

图13

图14

参考文献 33

1	丁藤, 冯冬涵, 林晓凡, 等. 基于修正后ARIMA-GARCH模型的超短期风速预测[J]. 电网技术, 2017, 41(6): 1808-1814.
	Ding Teng, Feng Donghan, Lin Xiaofan, et al. Ultra-Short-Term Wind Speed Prediction Based on Modified ARIMA-GARCH Model[J]. Power Grid Technology, 2017, 41(6): 1808-1814.
2	孙冬梅, 陈玲, 朱靳. 基于ARIMA模型误差修正的小波神经网络风速短期预测[J]. 计算机与应用化学, 2013, 30(3): 322-326.
	Sun Dongmei, Chen Ling, Zhu Jin. Short-term Wind Speed Prediction by Wavelet Neural Network Based on ARIMA Model Error Correction[J]. Computers and Applied Chemistry, 2013, 30(3): 322-326.
3	田中大, 李树江, 王艳红, 等. 基于ARIMA与ESN的短期风速混合预测模型[J]. 太阳能学报, 2016, 37(6): 1603-1610.
	Tian Zhongda, Li Shujiang, Wang Yanhong, et al. Short-term Wind Speed Hybrid Prediction Model Based on ARIMA and ESN[J]. Journal of Solar Energy, 2016, 37(6): 1603-1610.
4	赵征, 汪向硕, 乔锦涛. 基于VMD和改进ARIMA模型的超短期风速预测[J]. 华北电力大学学报(自然科学版), 2019, 46(1): 54-59.
	Zhao Zheng, Wang Xiangshuo, Qiao Jintao. Ultra-Short-Term Wind Speed Prediction Based on VMD and Improved ARIMA Model[J]. Journal of North China Electric Power University (Natural Science Edition), 2019, 46(1): 54-59.
5	冉靖, 张智刚, 梁志峰, 等. 风电场风速和发电功率预测方法综述[J]. 数理统计与管理, 2020, 39(6): 1045-1059.
	Ran Jing, Zhang Zhigang, Liang Zhifeng, et al. A Review of Wind Speed and Power Generation Prediction Methods for Wind Farms[J]. Mathematical Statistics and Management, 2020, 39(6): 1045-1059.
6	Ortiz-Garcia E G, Salcedo-Sanz S, Perez-Bellido A M, et al. Short-Term Wind Speed Prediction in Wind Farms Based on Banks of Support Vector Machines[J]. Wind Energy(S1095-4244), 2011, 14(2): 193-207.
7	周松林, 茆美琴, 苏建徽. 基于预测误差校正的支持向量机短期风速预测[J]. 系统仿真学报, 2012, 24(4): 769-773.
	Zhou Songlin, Mao Meiqin, Su Jianhui. Short-term Wind Speed Prediction by Support Vector Machine Based on Prediction Error Correction[J]. Journal of System Simulation, 2012, 24(4): 769-773.
8	张友鹏, 叶爱贤, 高峰阳, 等. 风力机尾流效应影响下输出功率预测仿真研究[J]. 系统仿真学报, 2014, 26(7): 1467-1471.
	Zhang Youpeng, Ye Aixian, Gao Fengyang, et al. Simulation Study of Wind Turbine Output Power Prediction Under the Influence of Wake Effect[J]. Journal of System Simulation, 2014, 26(7): 1467-1471.
9	王子赟, 纪志成. 基于GM(2, 1)和辨识算法的风电功率短期预测研究[J]. 系统仿真学报, 2015, 27(11): 2762-2769, 2777.
	Wang Ziyun, Ji Zhicheng. Research on Short-term Prediction of Wind Power Based on GM (2,1) and Discriminative Algorithm[J]. Journal of System Simulation, 2015, 27(11): 2762-2769, 2777.
10	张妍, 王东风, 韩璞. 基于IDE-LSSVM的风电场短期风速预测[J]. 系统仿真学报, 2017, 29(7): 1561-1571.
	Zhang Yan, Wang Dongfeng, Han Pu. Short-term Wind Speed Prediction for Wind Farms Based on IDE-LSSVM[J]. Journal of System Simulation, 2017, 29(7): 1561-1571.
11	张如九, 严磊, 何旭辉, 等. 基于混合方法的风速预测模型研究[J]. 铁道科学与工程学报, 2020, 17(7): 1630-1636.
	Zhang Rujiu, Yan Lei, He Xuhui, et al. Research on Wind Speed Prediction Model Based on Hybrid Method[J]. Journal of Railway Science and Engineering, 2020, 17(7): 1630-1636.
12	张祥宇, 付媛, 王毅, 等. 含虚拟惯性与阻尼控制的变速风电机组综合PSS控制器[J]. 电工技术学报, 2015, 30(1): 159-169.
	Zhang Xiangyu, Fu Yuan, Wang Yi, et al. Integrated PSS Controller for Variable-speed Wind Turbines with Virtual Inertia and Damping Control[J]. Journal of Electrical Engineering Technology, 2015, 30(1): 159-169.
13	Knudsen H, Nielsen J N. Introduction to the Modelling of Wind Turbines[M]. John Wiley & Sons, Ltd, 2012.
14	牛玉广, 杨巍, 李晓明, 等. 双馈风机神经电力系统稳定器设计与仿真研究[J]. 系统仿真学报, 2017, 29(1): 162-169, 180.
	Niu Yuguang, Yang Wei, Li Xiaoming, et al. Design and Simulation Study of Neural Power System Stabilizer for Doubly-fed Wind Turbine[J]. Journal of System Simulation, 2017, 29(1): 162-169, 180.
15	李和明, 张祥宇, 王毅, 等. 基于功率跟踪优化的双馈风力发电机组虚拟惯性控制技术[J]. 中国电机工程学报, 2012, 32(7): 32-39, 188.
	Li Heming, Zhang Xiangyu, Wang Yi, et al. Virtual Inertia Control Technology for Doubly-fed Wind Turbines Based on Power Tracking Optimization[J]. Chinese Journal of Electrical Engineering, 2012, 32(7): 32-39, 188.
16	赵晶晶, 吕雪, 符杨, 等. 基于可变系数的双馈风机虚拟惯量与超速控制协调的风光柴微电网频率调节技术[J]. 电工技术学报, 2015, 30(5): 59-68.
	Zhao Jingjing, Xue Lü, Fu Yang, et al. Frequency Regulation Technology of Scenic Diesel Microgrid Based on Virtual Inertia and Overspeed Control Coordination of Doubly-fed Wind Turbine with Variable Coefficients[J]. Journal of Electrotechnology, 2015, 30(5): 59-68.
17	胥国毅, 胡家欣, 郭树锋, 等. 超速风电机组的改进频率控制方法[J]. 电力系统自动化, 2018, 42(8): 39-44.
	Xu Guoyi, Hu Jiaxin, Guo Shufeng, et al. An Improved Frequency Control Method for Overspeed Wind Turbines[J]. Power System Automation, 2018, 42(8): 39-44.
18	Vidyanandan K V, Senroy N. Primary Frequency Regulation by Deloaded Wind Turbines Using Variable Droop[J]. IEEE Transactions on Power Systems(S0885-8950), 2013, 28(2): 837-846.
19	付媛, 王毅, 张祥宇, 等. 变速风电机组的惯性与一次调频特性分析及综合控制[J]. 中国电机工程学报, 2014, 34(27): 4706-4716.
	Fu Yuan, Wang Yi, Zhang Xiangyu, et al. Inertia and Primary Frequency Regulation Characteristics Analysis and Integrated Control of Variable Speed Wind Turbine[J]. Chinese Journal of Electrical Engineering, 2014, 34(27): 4706-4716.
20	赵晶晶, 吕雪, 符杨, 等. 基于双馈感应风力发电机虚拟惯量和桨距角联合控制的风光柴微电网动态频率控制[J]. 中国电机工程学报, 2015, 35(15): 3815-3822.
	Zhao Jingjing, Xue Lü, Fu Yang, et al. Dynamic Frequency Control of Scenic Diesel Microgrid Based on Virtual Inertia and Pitch Angle Joint Control of Doubly-fed Induction Wind Turbine[J]. Chinese Journal of Electrical Engineering, 2015, 35(15): 3815-3822.
21	张昭遂, 孙元章, 李国杰, 等. 超速与变桨协调的双馈风电机组频率控制[J]. 电力系统自动化, 2011, 35(17): 20-25, 43.
	Zhang Zhaosui, Sun Yuanzhang, Li Guojie, et al. Frequency Control of Doubly-fed Wind Turbines with Overspeed and Pitch Coordination[J]. Power System Automation, 2011, 35(17): 20-25, 43.
22	刘巨, 姚伟, 文劲宇, 等. 大规模风电参与系统频率调整的技术展望[J]. 电网技术, 2014, 38(3): 638-646.
	Liu Ju, Yao Wei, Wen Jinyu, et al. Technical Prospect of Large-scale Wind Power Participation in System Frequency Adjustment[J]. Power Grid Technology, 2014, 38(3): 638-646.
23	刘辉, 葛俊, 巩宇, 等. 风电场参与电网一次调频最优方案选择与风储协调控制策略研究[J]. 全球能源互联网, 2019, 2(1): 44-52.
	Liu Hui, Ge Jun, Gong Yu, et al. Research on Optimal Scheme Selection and Wind-storage Coordination Control Strategy for Wind Farm Participation in Grid Primary Frequency Regulation[J]. Global Energy Internet, 2019, 2(1): 44-52.
24	刘巨, 姚伟, 文劲宇, 等.一种基于储能技术的风电场虚拟惯量补偿策略[J]. 中国电机工程学报, 2015, 35(7): 1596-1605.
	Liu Ju, Yao Wei, Wen Jinyu, et al. A Virtual Inertia Compensation Strategy for Wind Farms Based on Energy Storage Technology[J]. Chinese Journal of Electrical Engineering, 2015, 35(7): 1596-1605.
25	孙鹏, 蔡勇, 万黎, 等. 基于混合储能的风电场一次调频控制[J]. 电网与清洁能源, 2016, 32(2): 133-139.
	Sun Peng, Cai Yong, Wan Li, et al. Hybrid Energy Storage Based Primary Frequency Regulation Control for Wind Farms[J]. Power Grid and Clean Energy, 2016, 32(2): 133-139.
26	颜湘武, 崔森, 宋子君, 等. 基于超级电容储能控制的双馈风电机组惯量与一次调频策略[J]. 电力系统自动化, 2020, 44(14): 111-120.
	Yan Xiangwu, Cui Sen, Song Zijun, et al. Double-fed Wind Turbine Inertia and Primary Frequency Regulation Strategy Based on Supercapacitor Energy Storage Control[J]. Power System Automation, 2020, 44(14): 111-120.
27	颜湘武, 宋子君, 崔森, 等. 基于变功率点跟踪和超级电容器储能协调控制的双馈风电机组一次调频策略[J]. 电工技术学报, 2020, 35(3): 530-541.
	Yan Xiangwu, Song Zijun, Cui Sen, et al. Primary Frequency Regulation Strategy for Doubly-fed Wind Turbines Based on Coordinated Control of Variable Power Point Tracking and Supercapacitor Energy Storage[J]. Journal of Electrical Engineering Technology, 2020, 35(3): 530-541.
28	林海涛. 考虑气象因素的风电场风速及风电功率短期预测研究[D]. 上海: 上海交通大学, 2010.
	Lin Haitao. Short-term Wind Speed and Wind Power Prediction for Wind Farms Considering Meteorological Factors[D]. Shanghai: Shanghai Jiao Tong University, 2010.
29	史宇伟, 潘学萍. 计及历史气象数据的短期风速预测[J]. 电力自动化设备, 2014, 34(10): 75-80.
	Shi Yuwei, Pan Xueping. Short-term Wind Speed Prediction by Counting and Historical Meteorological Data[J]. Power Automation Equipment, 2014, 34(10): 75-80.
30	田中大, 李树江, 王艳红, 等.短期风速时间序列混沌特性分析及预测[J]. 物理学报, 2015, 64(3): 246-257.
	Tian Zhongda, Li Shujiang, Wang Yanhong, et al. Analysis and Prediction of Chaotic Characteristics of Short-term Wind Speed Time Series[J]. Journal of Physics, 2015, 64(3): 246-257.
31	宣传忠, 陈智, 武佩, 等. 草原风电场气象与时间纵横组合的风速预测[J]. 太阳能学报, 2016, 37(1): 230-235.
	Xuan Chuanzhong, Chen Zhi, Wu Pei, et al. Wind Speed Prediction for Grassland Wind Farms with Meteorological and Temporal Longitudinal Combinations[J]. Journal of Solar Energy, 2016, 37(1): 230-235.
32	袁翀. 基于历史气象数据的风电场风速和风功率预测研究[D]. 吉林: 东北电力大学, 2017.
	Yuan Chong. Research on Wind Speed and Wind Power Prediction of Wind Farms Based on Historical Meteorological Data [D]. Jilin: Northeast Electric Power University, 2017.
33	冬雷, 廖晓钟, 王丽婕. 大型风电场发电功率建模与预测[M]. 北京: 科学出版社, 2014.
	Dong Lei, Liao Xiaozhong, Wang Lijie. Modeling and Prediction of Power Generation from Large Wind Farms [M]. Beijing: Science Press, 2014.

小时序号	风速/(m/s)	气压/kPa	温度/℃	相对湿度/%
1	6.55	89.08	-10.3	45
2	6.5	89.07	-8.4	40
3	6.6	89.04	-6.4	34
4	5.55	89.00	-5.2	33
5	5.6	88.92	-4.3	30
6	5.2	88.84	-4	30
7	5.7	88.82	-2.8	28
8	5.4	88.81	-6.1	40
9	5.4	88.88	-7.8	45
10	5	88.82	-9.1	56
…
285	5.29	89.92	-10	70
286	5.51	89.93	-11	71
287	6.1	89.86	-11	76
288	5.9	89.81	-12	78

预测精度指标	MAPE/%	MAE/(m/s)	RMSE/(m/s)
ARIMA	11.78	0.62	0.94
BP-ARIMA	6.22	0.32	0.42

[1]	李鹏飞, 徐伟, 朴永杰, 方应红, 石敦攀. 天基空间小目标复杂场景数字成像仿真[J]. 系统仿真学报, 2025, 37(9): 2315-2334.
[2]	范增, 何明君, 邢翔宇. 面向飞行员认知负荷评估的数字化仿真方法研究[J]. 系统仿真学报, 2025, 37(8): 1921-1932.
[3]	谢学远, 林晨, 吴晗, 赵庆岚, 高俊飞, 郝强国, 郑新前. 基于虚拟行驶场景的特种车辆发动机运行特性联合仿真研究[J]. 系统仿真学报, 2025, 37(8): 2163-2175.
[4]	董志明, 胡忠奇, 刘赵阳, 周贺阳. 作战仿真想定智能化生成研究综述[J]. 系统仿真学报, 2025, 37(7): 1665-1683.
[5]	朴景华, 高宸, 张芳, 苏竣, 李勇. 大型社会模拟器：前沿与展望[J]. 系统仿真学报, 2025, 37(7): 1770-1790.
[6]	刘涛, 李瀚熙, 尹勇, 刘佳仑. 航海智能仿真技术及应用研究综述[J]. 系统仿真学报, 2025, 37(7): 1684-1709.
[7]	韩冰, 林昀和, 陈宇航, 彭周华. 双吊舱船舶运动建模与仿真[J]. 系统仿真学报, 2025, 37(6): 1352-1365.
[8]	杜康萍, 隋璘, 熊伟丽. 基于自适应稀疏宽度学习系统的软测量建模[J]. 系统仿真学报, 2025, 37(6): 1449-1461.
[9]	赵雪梦, 任天助, 方哲梅. 基于多模型的体系架构迭代设计方法[J]. 系统仿真学报, 2025, 37(6): 1512-1521.
[10]	赵曙光, 陈策, 谢孝昌, 栗付平, 韩劲. 基于直线模型提升同轴磁齿轮设计效率的研究[J]. 系统仿真学报, 2025, 37(6): 1574-1581.
[11]	马苗苗, 龙紫娟, 任智伟, 成永强. 基于EMPC的含电动汽车综合能源系统分层优化调度[J]. 系统仿真学报, 2025, 37(5): 1116-1128.
[12]	谷学强, 罗俊仁, 周棪忠, 张万鹏. 智能博弈决策大模型智能体技术综述[J]. 系统仿真学报, 2025, 37(5): 1142-1157.
[13]	王祥, 谭国真. 基于知识与大语言模型的高速环境自动驾驶决策研究[J]. 系统仿真学报, 2025, 37(5): 1246-1255.
[14]	窦小强, 刘艳, 赵志龙, 付超, 张馥琳, 邹珊珊. 基于DoDAF框架的工业核心能力架构建模方法研究[J]. 系统仿真学报, 2025, 37(5): 1290-1304.
[15]	刘志鹏, 顾艳阳, 胡宝洁, 贺方君, 范志鹏. 一种关于新型分布式对抗的仿真框架构建方法研究[J]. 系统仿真学报, 2025, 37(5): 1305-1313.