CHARACTERISTIC ANALYSIS AND THRESHOLD DETERMINATION OF POWER RAMP EVENTS IN A WIND FARM OF INNER MONGOLIA

Xu Li'na; Shen Yanbo; Wang Jieru

doi:10.19912/j.0254-0096.tynxb.2024-0846

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (9) : 133-142. DOI: 10.19912/j.0254-0096.tynxb.2024-0846

CHARACTERISTIC ANALYSIS AND THRESHOLD DETERMINATION OF POWER RAMP EVENTS IN A WIND FARM OF INNER MONGOLIA

Xu Li'na^1~3, Shen Yanbo^3,4, Wang Jieru^3,4

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Abstract

The fluctuation and intermittency of wind power influenced by meteorological environmental conditions are important reasons leading to wind power ramp. A wind farm in Inner Mongolia is taken as the study area. The data of wind speeds on the height of wind turbine hub and actual power data are used to identify the ramp events in the study area. The data time interval is 15 minutes and period is from 19:00 on September 11, 2019 to 23:45 on December 31, 2020. The characteristics of the ramp events are analyzed from the aspects of ramp heights, ramp speeds, times of duration, seasonal and daily variations, and so on. Further more, five risk levels of the ramp events including extremely low, low, medium, high and extremely high are classified, combining with the risk assessment of power system operation. The maximum ramp heights and wind speed changes at different risk levels are determined in order to provide effective technical support for predicting ramp events. The results show that： 1）The average ramp speed of the upward ramp events is significantly higher than that of the downward ramp events, the ramp speeds are inversely proportional to duration times; 2） the ramp heights and ramp speeds have significant seasonal variations, the average of those in spring and summer are higher than in autumn and winter; 3） the occurrence possibility of high risk upward ramp events is significantly higher than that of high risk downward ramp events, there is a possibility of extremely high risk downward ramp events, the maximum ramp height of upward ramp events is close to that of downward ramp events under different risk levelss, but the maximum wind speed variation of downward events is greater.

Key words

ramp event / wind power / wind speed / character analysis / threshold

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Xu Li'na, Shen Yanbo, Wang Jieru. CHARACTERISTIC ANALYSIS AND THRESHOLD DETERMINATION OF POWER RAMP EVENTS IN A WIND FARM OF INNER MONGOLIA[J]. Acta Energiae Solaris Sinica. 2025, 46(9): 133-142 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0846

References

[1] 陶玉波, 陈昊, 秦晓辉, 等. 短期风电功率预测概念和模型与方法[J]. 电力工程技术, 2018, 37(5): 7-13.
TAO Y B, CHEN H, QIN X H, et al.A review of the short-term wind power forecasting theory, model and approach[J]. Electric power engineering technology, 2018, 37(5): 7-13.
[2] 张东英, 代悦, 张旭, 等. 风电爬坡事件研究综述及展望[J]. 电网技术, 2018, 42(6): 1783-1792.
ZHANG D Y, DAI Y, ZHANG X, et al.Review and prospect of research on wind power ramp events[J]. Power system technology, 2018, 42(6): 1783-1792.
[3] ELA E, KIRBY B.ERCOT event on February 26,2008:lessons learned[R].USA:National Renewable Energy Laboratory, 2008.
[4] 熊一, 査晓明, 秦亮, 等. 基于强对流天气判别的风功率爬坡预报方法研究[J]. 中国电机工程学报, 2016, 36(10): 2690-2698.
XIONG Y, ZHA X M, QIN L, et al.Research on wind power ramping prediction based on the strong convective weather discriminant method[J]. Proceedings of the CSEE, 2016, 36(10): 2690-2698.
[5] KUSIAK A, ZHENG H Y, SONG Z.Wind farm power prediction: a data-mining approach[J]. Wind energy, 2009, 12(3): 275-293.
[6] 李芬, 李春阳, 闫全全, 等. 多时间尺度下光伏出力爬坡事件概率建模与评估研究[J]. 太阳能学报, 2019, 40(11): 3289-3298.
LI F, LI C Y, YAN Q Q, et al.PV power ramp events probability modeling and assessment in multiple time scales[J]. Acta energiae solaris sinica, 2019, 40(11): 3289-3298.
[7] 朱文立, 张利, 杨明, 等. 考虑日周期性影响的光伏功率爬坡事件非精确概率预测[J]. 电力系统自动化, 2019, 43(20): 31-38.
ZHU W L, ZHANG L, YANG M, et al.Imprecise probabilistic prediction of photovoltaic power ramp event considering daily periodic effect[J]. Automation of electric power systems, 2019, 43(20): 31-38.
[8] 匡洪海, 王建辉, 张瀚超, 等. 一种新型的风电功率爬坡段识别方法[J]. 电网技术, 2019, 43(5): 1752-1759.
KUANG H H, WANG J H, ZHANG H C, et al.A novel wind power climbing section identification method[J]. Power system technology, 2019, 43(5): 1752-1759.
[9] KHODAYAR M E, SHAHIDEHPOUR M.Stochastic price-based coordination of intrahour wind energy and storage in a generation company[J]. IEEE transactions on sustainable energy, 2013, 4(3): 554-562.
[10] 刘申. 基于气象测量场的风电爬坡事件与功率预测[D]. 济南: 山东大学, 2015.
LIU S.Wind ramp events and wind power forecasting using meteorological measurement field[D]. Ji'nan: Shandong University, 2015.
[11] FERREIRA C, GAMA J, MATIAS L, et al.A survey on wind power ramp forecasting[R].USA:Argonne National Laboratory (ANL),2011.
[12] 郭燕玲, 赵晶, 周林, 等. 山东半岛风电爬坡事件的识别与天气分析研究[J]. 气候与环境研究, 2017, 22(1): 97-107.
GUO Y L, ZHAO J, ZHOU L, et al.A study on the identification and synoptic analysis of wind ramp events in Shandong Peninsula[J]. Climatic and environmental research, 2017, 22(1): 97-107.
[13] OHBA M, KADOKURA S, NOHARA D.Impacts of synoptic circulation patterns on wind power ramp events in East Japan[J]. Renewable energy, 2016, 96: 591-602.
[14] 余洋, 陈东阳, 王卜潇, 等. 基于IBSO-SDT的风电爬坡事件检测方法[J]. 太阳能学报, 2023, 44(9): 348-355.
YU Y, CHEN D Y, WANG B X, et al.Wind power ramp event detection method based on IBSO-SDT[J]. Acta energiae solaris sinica, 2023, 44(9): 348-355.
[15] 杨茂, 刘红柳. 超短期风电功率爬坡事件对风电功率实时预测误差的影响研究[J]. 太阳能学报, 2017, 38(3): 571-577.
YANG M, LIU H L.Ultra-short-term wind power climbing event research on the effect of wind power real-time prediction error[J]. Acta energiae solaris sinica, 2017, 38(3): 571-577.
[16] 黄棋悦, 严楠, 钟旭佳. 基于生成对抗网络的风电爬坡功率预测[J]. 太阳能学报, 2023, 44(1): 226-231.
HUANG Q Y, YAN N, ZHONG X J.Wind power ramping events prediction based on generative adversarial network[J]. Acta energiae solaris sinica, 2023, 44(1): 226-231.
[17] 任双雪, 王毅钊, 张寓涵, 等. 风电功率爬坡事件的滑动窗检测与实例分析[J]. 电网与清洁能源, 2018, 34(1): 109-114.
REN S X, WANG Y Z, ZHANG Y H, et al.Detection method and case analysis of wind power ramping events with sliding window[J]. Power system and clean energy, 2018, 34(1): 109-114.
[18] 崔明建. 风电功率爬坡事件问题研究[D]. 武汉: 武汉大学, 2015.
CUI M J.Study of wind power ramping events[D]. Wuhan: Wuhan University, 2015.
[19] 沈小军, 付雪姣, 周冲成, 等. 风电机组风速-功率异常运行数据特征及清洗方法[J]. 电工技术学报, 2018, 33(14): 3353-3361.
SHEN X J, FU X J, ZHOU C C, et al.Characteristics of outliers in wind speed-power operation data of wind turbines and its cleaning method[J]. Transactions of China Electrotechnical Society, 2018, 33(14): 3353-3361.
[20] 宗阳. 风电功率爬坡事件检测及预测方法研究[D]. 南京: 南京信息工程大学, 2020.
ZONG Y.Research on detection and prediction method of wind power ramping events[D]. Nanjing: Nanjing University of Information Science & Technology, 2020.
[21] 张颖超, 宗阳, 邓华, 等. 基于趋势特征的风电功率爬坡事件检测方法[J]. 电测与仪表, 2020, 57(18): 122-127, 132.
ZHANG Y C, ZONG Y, DENG H, et al.Wind power ramp event detection method based on trend feature[J]. Electrical measurement & instrumentation, 2020, 57(18): 122-127, 132.
[22] 涂娇娇. 风电功率波动特性分析及其在电力系统中的应用[D]. 吉林: 东北电力大学, 2015.
TU J J.The analysis of wind power fluctuation characteristics and the application in the power system[D]. Jilin: Northeast Dianli University, 2015.
[23] 邢丽珠, 张方敏, 黄进, 等. 1961—2018年内蒙古6级及以上大风日数时空变化特征[J]. 干旱区地理, 2021, 44(5): 1290-1298.
XING L Z, ZHANG F M, HUANG J, et al.Spatial and temporal changes of high wind days over category 6 and above in Inner Mongolia from 1961 to 2018[J]. Arid land geography, 2021, 44(5): 1290-1298.
[24] 佟新元. 考虑风电高风险爬坡事件的电力系统运行风险评估与备用决策[D]. 济南: 山东大学, 2016.
TONG X Y.Operation risk assessment and reserve strategy of power system considering wind power ramp events[D]. Ji'nan: Shandong University, 2016.