基于风电场输出功率波动特性分析的本征时间尺度的确定

时彤; 姜卓; 肖白; SHI Tong; JIANG Zhuo; XIAO Bai

doi:10.16513/j.cnki.10-1427/tk.2017.04.009

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分布式能源 ›› 2017, Vol. 2 ›› Issue (4) : 53-58. DOI: 10.16513/j.cnki.10-1427/tk.2017.04.009

应用技术

基于风电场输出功率波动特性分析的本征时间尺度的确定

时彤 ¹ ,
姜卓 ² ,
肖白 ³ ,
SHI Tong ¹ ,
JIANG Zhuo ² ,
XIAO Bai ³

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Intrinsic Time Scale Determination Based on Analyzing Wind Power Output Fluctuation Features

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摘要

Wind power is a kind of power with stochastic volatility output power. Different sampling time lengths may affect the preciseness of analysis results when analyzing the characteristic of wind power fluctuation. We expect to find one sampling time length which can make the analysis result closest to the fundamental volatile features and shorten the computation and analysis time in project, and named this sampling time length as the intrinsic time scale. Firstly, this paper establishes the index system that is able to depict the volatile features of wind power, and then analyzes the change rules and trends of all indexes under different time scales. Finally, this paper discusses the impact of sampling time on the wind power characteristics in detail and determines the intrinsic time scale.

关键词

风电功率 / 波动特性 / 采样时间间隔 / 本征时间尺度 / wind power / fluctuation characteristic / sampling time interval / intrinsic time scale

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时彤, 姜卓, 肖白, 等. Intrinsic Time Scale Determination Based on Analyzing Wind Power Output Fluctuation Features[J]. 分布式能源. 2017, 2(4): 53-58 https://doi.org/10.16513/j.cnki.10-1427/tk.2017.04.009

[J]. Distributed Energy Resources. 2017, 2(4): 53-58 https://doi.org/10.16513/j.cnki.10-1427/tk.2017.04.009

参考文献

列表( 原文顺序 | 文献年度倒序 | 文中引用次数倒序 ) 可视化分析

[1]	杨秀媛，肖洋，陈树勇. 风电场风速和发电功率预测研究[J]. 中国电机工程学报，2005, 25(11): 1-5. YANG Xiuyuan, XIAO Yang, CHEN Shuyong. Wind speed and generated power forecasting in wind farm[J]. Proceedings of the CSEE, 2005, 25(11): 1-5. 本文引用 [1]

[2]	范高锋，王伟胜，刘纯，等. 基于人工神经网络的风电功率短期预测系统[J]. 电网技术，2008, 32(22): 72-76. FAN Gaofeng, WANG Weisheng, LIU Chun, et al. Artificial neural network based wind power short term prediction system[J]. Power System Technology, 2008, 32(22): 72-76. 本文引用 [1]

[3]	杨琦，张建华，王向峰，等. 基于小波–神经网络的风速及风力发电量预测[J]. 电网技术，2009, 33(17): 44-48. YANG Qi, ZHANG Jianhua, WANG Xiangfeng, et al. Wind speed and generated wind power forecast based on wavelet-neural network[J]. Power System Technology, 2009, 33(17): 44-48. 本文引用 [1]

[4]	刘纯，范高锋，王伟胜，等. 风电场输出功率的组合预测模型[J]. 电网技术，2009, 33(13): 74-79. LIU Chun, FAN Gaofeng, WANG Weisheng, et al. A combination forecasting model for wind farm output power[J]. Power System Technology, 2009, 33(13): 74-79. 本文引用 [1]

[5]	VILLANUEVA D, PAZOS J L, FEIJÓo A. Probabilistic load flow including wind power generation[J]. IEEE Transactions on Power Systems, 2011, 26(3): 1659-1667. 本文引用 [1]

[6]	USAOLA J. Probabilistic load flow with correlated wind power injections[J]. Electric Power Systems Research, 2010, 80(5): 528-536. 本文引用 [1]

[7]	林卫星，文劲宇，艾小猛，等. 风电功率波动特性的概率分布研究[J]. 中国电机工程学报，2012, 32(1): 38-46. LIN Weixing, WEN Jinyu, AI Xiaomeng, et al. Probability density function of wind power variations[J]. Proceedings of the CSEE, 2012, 32(1): 38-46. 本文引用 [1]

[8]	高凯，朱加明，葛延峰，等. 联网风电场集群运行特性分析[J]. 东北电力大学学报，2014, 34(4): 11-16. GAO Kai, ZHU Jiaming, GE Yanfeng, et al. Analysis on operating characteristics of clustered wind farms[J]. Journal of Northeast Dianli University, 2014, 34(4): 11-16. 本文引用 [1]

[9]	张义斌，王伟胜. 风电场输出功率的概率分布及其应用[J]. 电力设备，2004, 5(8): 38-40. ZHANG Yibin, WANG Weisheng. Probability distribution of power output for wind power field and its application[J]. Electrical Equipment, 2004, 5(8): 38-40. 本文引用 [1]

[10]	POUL S, NICOLAOS A C. Power fluctuations from large wind farms[J]. IEEE Trans. on Power Systems, 2007, 22(3): 958-965. 本文引用 [1]

[11]	崔杨，穆钢，刘玉，等. 风电功率波动的时空分布特性[J]. 电网技术，2011, 35(2): 110-114. CUI Yang, MU Gang, LIU Yu, et al. Spatiotemporal distribution characteristic of wind power fluctuation[J]. Power System Technology, 2011, 35(2): 110-114. 本文引用 [1]

[12]	谷兴凯，范高锋，王晓蓉. 风电功率预测技术综述[J]. 电网技术，2007, 31(): 335-338. 摘要 S2 GU Xingkai, FAN Gaofeng, WANG Xiaorong. Summarization of wind power prediction technology[J]. Power System Technology, 2007, 31(): 335-338. 本文引用 [1] 摘要 S2

[13]	GO T, NORIHIDE K, MASATOSHI M, et al. Study on power fluctuation characteristics of wind energy converters with fluctuating turbine torque[J]. Electrical Engineering in Japan, 2005, 153(4): 1-11. 本文引用 [1]

[14]	丁明，吴伟，吴红斌. 风速概率分布参数预测及应用[J]. 电网技术，2008, 32(32): 10-14. DING Ming, WU Wei, WU Hongbin. Research on forecasting of probabilistic distribution parameters of wind speed and its application[J]. Power System Technology, 2008, 32(32): 10-14. 本文引用 [1]

[15]	杨振斌，朱瑞兆，薛桁. 风电场风能资源评价两个新参数：相当风速、有功风功率密度[J]. 太阳能学报，2007, 28(3): 248-251. YANG Zhenbin, ZHU Ruizhao, XUE Heng. Two new concepts on wind energy assessment in wind farm: equivalent wind speed, available wind power density[J]. Acta Energiae Solaris Sinica, 2007, 28(3): 248-251. 本文引用 [1]

[16]	曹娜，赵海翔，任普春，等. 风电场动态分析中风速模型的建立及应用[J]. 中国电机工程学报，2007, 27(36): 68-72. CAO Na, ZHAO Haixiang, REN Puchun, et al. Establish and application of wind speed model in wind farm dynamic analysis[J]. Proceedings of the CSEE, 2007, 27(36): 68-72. 本文引用 [1]

[17]	靳雯皓，刘继春. 平滑风电功率波动的混合储能系统容量优化配置[J]. 分布式能源，2017, 2(2): 32-38. JIN Wenhao, LIU Jichun. Capacity optimization configuration of hybrid energy storage system for smoothing wind power fluctuation[J]. Distributed Energy, 2017, 2(2): 32-38. 本文引用 [1]

[18]	MARY B, GORAN S. Value of bulk energy storage for managing wind power fluctuations[J]. IEEE Trans on Energy Conversion, 2007, 22(1): 197-205. 本文引用 [1]

[19]	LI Wei, GÉZA J, CHAD A. Attenuation of wind power fluctuations in wind turbine generators using a DC bus capacitor based filtering control scheme[C]//IEEE 4th World Conference on Photovoltaic Energy Conversion. Waikoloa, Hawaii, USA: IEEE, 2006, 1(1): 216-221. 本文引用 [1]