考虑多风电场功率相关性的概率潮流联合分布计算

doi:10.11930/j.issn.1004-9649.201702093

中国电力 ›› 2017, Vol. 50 ›› Issue (10): 71-77.DOI: 10.11930/j.issn.1004-9649.201702093

考虑多风电场功率相关性的概率潮流联合分布计算

田蓓¹, 于珍², 李旭涛¹, 李宏强¹, 沈沉²

1. 国网宁夏电力公司电力科学研究院,宁夏银川 750001;
2. 清华大学电机工程与应用电子技术系电力系统国家重点实验室,北京 100084

收稿日期:2017-02-23 出版日期:2017-10-25 发布日期:2017-10-30
作者简介:田蓓（1977—）,女,宁夏银川人,高级工程师,从事电力系统自动化研究。E-mail: babyqi0203@163.com
基金资助:
国网宁夏电力公司电力科学研究院资助项目（5229DK14000Z）

Joint Distribution Calculation with Probabilistic Power Flow Considering Dependencies Among Multiple Wind Power Generations

TIAN Bei¹, YU Zhen², LI Xutao¹, LI Hongqiang¹, SHEN Chen²

1. Electric Power Research Institute of State Grid Ningxia Electric Power Company, Yinchuan 750001, China;
2. State Key Lab of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing100084, China

Received:2017-02-23 Online:2017-10-25 Published:2017-10-30
Supported by:
This work is supported by Electric Power Research Institute of State Grid Ningxia Electric Power Company (No. 5229DK14000Z).

摘要/Abstract

摘要： 随着大规模风电接入电网,风电的随机性为电网运行带来了更多的不确定因素,严重威胁系统的静态安全。提出一种考虑多风电场功率相关性的概率潮流联合分布计算方法,可用于评估多个风电场风电出力对系统静态安全的影响。首先采用高斯混合模型来准确描述多个风电场功率的联合概率分布,然后利用高斯混合模型的优良性质,依据系统状态量与风功率之间的近似线性关系,进而获得系统状态量的联合概率分布。将该方法应用于宁夏电网的静态安全概率评估,经过与蒙特卡罗仿真法比较,结果表明,该方法准确度更高,计算速度更快。

关键词: 电力系统, 风电, 概率潮流计算, 联合概率分布

Abstract: With large-scale wind power connected to power grid, wind generation fluctuation brings more uncertainties to power grid operation and seriously threatens power system static security. A joint distribution calculation method of probabilistic power flow considering dependencies among multiple wind power generations is proposed, which can be used to evaluate influence of wind generation on power system static security. Firstly, the Gaussian mixture model is used to characterize joint probability distribution of multiple wind power generations accurately. Then, based on excellent property of the Gaussian mixture model and approximate linear relationship between system state variables and wind power generations assumption, analytical expressions of joint probability distribution of system state variables are obtained. This method is applied to probability assessment of static security in Ningxia power grid. Compared with Monte Carlo simulation method, the proposed method has higher accuracy and faster computation speed.

中图分类号:

TM73

田蓓, 于珍, 李旭涛, 李宏强, 沈沉. 考虑多风电场功率相关性的概率潮流联合分布计算[J]. 中国电力, 2017, 50(10): 71-77.

TIAN Bei, YU Zhen, LI Xutao, LI Hongqiang, SHEN Chen. Joint Distribution Calculation with Probabilistic Power Flow Considering Dependencies Among Multiple Wind Power Generations[J]. Electric Power, 2017, 50(10): 71-77.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201702093

https://www.electricpower.com.cn/CN/Y2017/V50/I10/71

参考文献

[1] 薛禹胜,雷兴,薛峰,等. 关于风电不确定性对于电力系统影响的评述[J]. 中国电机工程学报,2014,34(29)：5029-5040.
XUE Yusheng, LEI Xing, XUE Feng, et al . A review on impacts of wind power uncertainties on power systems[J]. Proceedings of the CSEE, 2014, 34(29): 5029-5040.
[2] 张磊,罗毅,肖雅元,等. 大规模风电并网条件下AGC机组跨区分布式最优协调控制[J]. 电工技术学报,2016,31(9)：42-49.
ZHANG Lei, LUO Yi, XIAO Yayuan, et al . Trans-regional and distribution optimal coordination control of AGC units large-scale wind power grid[J]. Transactions of China Electrotechnical Society, 2016, 31(9): 42-49.
[3] 韩勇,郑翔宇,彭生江,等. 大规模风电集中接入的电力系统储能容量配置策略[J]. 中国电力,2015,48(6)：26-30.
HAN Yong, ZHENG Xiangyu, PENG Shengjiang, et al . Configuration of energy storage in power system with wind power integration [J]. Electric Power, 2015, 48(6): 26-30.
[4] BORKOWSKAB B. Probabilistic load flow[J]. IEEE Transactions on Power Apparatus and Systems, 1974, 93(3): 752-759.
[5] 邓威,李欣然,徐振华,等. 考虑风速相关性的概率潮流计算及影响分析[J]. 电网技术,2012,36(4)：45-50.
DENG Wei, LI Xinran, XU Zhenhua, et al . Calculation of probabilistic load flow considering wind speed correlation and analysis on influence of wind speed correlation[J]. Power System Technology, 2012, 36(4): 45-50.
[6] 张楷旋,陈建英,郭创新,等. 考虑天气因素的含风电场电力系统的概率潮流分析[J]. 电网技术,2014,38(12)：3418-3423.
ZHANG Kaixuan, CHEN Jianying, GUO Chuangxin, et al . Weather factor based analysis on probabilistic load flow of power grid containing wind farms[J]. Power System Technology, 2014, 38(12): 3418-3423.
[7] 艾小猛,文劲宇,吴桐,等. 基于点估计和Gram-Charlier展开的含风电电力系统概率潮流实用算法[J]. 中国电机工程学报, 2013,33(16)：16-22.
AI Xiaomeng, WEN Jinyu, WU Tong, et al . A pratical algorithm based on point estimate method and gram-charlier expansion for probabilistic load flow calculation of power systems incorporating wind power [J]. Proceeding of the CSEE, 2013, 33(16): 16-22.
[8] SILVA A M L D, ARIENTI V L, ALLAN R N. Probabilistic load flow considering sependence between input nodal powers[J]. IEEE Transactions on Power Apparatus & Systems, 1984, PAS-103(6): 1524-1530.
[9] 杨欢,邹斌. 含相关性随机变量的概率潮流三点估计法[J]. 电力系统自动化,2012,36(15)：51-56.
YANG Huan, ZOU Bin. A three-point estimate method for solving probabilistic power flow problems with correlated random varibles[J]. Automation of Electric Power Systems, 2012, 36(15): 51-56.
[10] ZHANG N, KANG C, XIA Q, et al . Modeling conditional forecast error for wind power in generation scheduling[J]. IEEE Transactions on Power Systems, 2014, 29(3): 1316-1324.
[11] PEI Z, LEE S T. Probabilistic load flow computation using the method of combined cumulants and gram-charlier expansion[J]. IEEE Transactions on Power Systems, 2004, 19(1): 676-682.
[12] ZHANG Z S, SUN Y Z, GAO D W, et al . A versatile probability distribution model for wind power forecast errors and its application in economic dispatch[J]. IEEE Transactions on Power Systems, 2013, 28(3): 3114-3125.
[13] 余鹏,封举富. 基于高斯混合模型的纹理图像分割[J]. 中国图像图形学报,2005,10(3)：281-285.
YU Peng, FENG Jufu. Texture image segmentation based on Gaussian mixture models [J]. Journal of Image and Graphics, 2005, 10(3): 281-285.
[14] 蒋伟. 基于高斯混合模型的说话人识别研究[D]. 成都: 电子科技大学,2008.
[15] SINGH R, PAL B C, JABR R A. Statistical representation of distribution system loads using Gaussian mixture model[J]. IEEE Transactions on Power Systems, 2010, 25(1): 29-37.
[16] WANG Z W, SHEN C, LIU F, et al . Analytical expressions for joint sistributions in probabilistic load flow [J]. IEEE Transactions on Power Systems, 2017, 32(3): 2473-2474.
[17] 张军,许晓艳,黄永宁,等. 基于时序生产模拟仿真的宁夏电网风光优化配比研究[J]. 电力系统保护与控制,2014,42(19)：81-86.
ZHANG Jun, XU Xiaoyan, HUANG Yongning, et al . Optimal proportion study of wind and PV capacity in Ningxia power grid based on time sequence simulation[J]. Power System Protection and Control, 2014, 42(19): 81-86.
[18] 2015年宁夏电网运行方式[M],银川：国网宁夏电力公司,2015.
[19] LI H S, LU Z Z, YUAN X K, et al . Nataf transformation based point estimate method [J]. Chinese Science Bulletin, 2008, 53(17): 2586-2592.

考虑多风电场功率相关性的概率潮流联合分布计算

Joint Distribution Calculation with Probabilistic Power Flow Considering Dependencies Among Multiple Wind Power Generations

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	李健, 张钧, 韩新阳, 靳晓凌. 新型电力系统形态量化推演方法的总体框架与功能设计[J]. 中国电力, 2025, 58(3): 1-7, 97.
[2]	张磊, 马晓伟, 王满亮, 陈力, 高丙团. 互联新能源电力系统区内AGC机组分布式协同控制策略[J]. 中国电力, 2025, 58(3): 8-19.
[3]	张沛, 杨马婧, 张放, 谢桦, 刘广一, 李文云, 路学刚, 王珍意, 翟苏巍. 图数据库与图计算在电力系统调度运行应用综述[J]. 中国电力, 2025, 58(3): 119-131.
[4]	高志远, 庄卫金, 李峰, 于芳, 张鸿, 王艳, 夏旻. 调控领域人工智能应用的高复用性验证平台[J]. 中国电力, 2025, 58(3): 142-150.
[5]	宋许鹏, 杨小洋, 樊征臻. 基于电流合成矢量轨迹特性的双馈风电场主变压器差动保护[J]. 中国电力, 2025, 58(2): 9-21.
[6]	汤明润, 李若旸, 刘慕然, 程晓钰, 刘铫, 杨淑霞. 电力系统稳态下可再生能源大规模接入量预测[J]. 中国电力, 2025, 58(2): 126-132.
[7]	赵晨浩, 焦在滨, 李程昊, 张迪, 张鹏辉. 基于主动迁移学习的电力系统暂态稳定自适应评估[J]. 中国电力, 2025, 58(1): 70-77.
[8]	董武, 张健, 周勤勇, 张立波, 龚浩岳. 中国电力系统安全稳定性演化综述[J]. 中国电力, 2025, 58(1): 115-127.
[9]	丰力, 张莲梅, 韦家佳, 邓长虹, 李果, 尹家悦. 基于全生命周期经济评估的海上风电发展与思考[J]. 中国电力, 2024, 57(9): 80-93.
[10]	刘钟淇, 刘耀, 侯金鸣. 以深远海风电为核心的能源岛能源外送经济性分析[J]. 中国电力, 2024, 57(9): 94-102.
[11]	姜文瑾, 刘巧妹, 杨晓东, 阙定飞, 沈豫, 黄夏楠, 赖振华. 计及气固两相储氢特性的海上风电-多元储能系统优化配置[J]. 中国电力, 2024, 57(9): 103-112.
[12]	黄宁泊, 高建伟, 许传博, 徐选华, 赵舒通, 缑迅杰, 姜晓静. 基于经验挖掘与混合语言的海上风电制氢加氢港口选址研究[J]. 中国电力, 2024, 57(9): 113-123.
[13]	朱瑞, 娄奇鹤, 靳晓凌, 刘畅. 适应新型电力系统的电网基建功能化投资结构演化研究[J]. 中国电力, 2024, 57(9): 194-204.
[14]	周专, 苗帅, 袁铁江. 提升风电消纳的绿氢钢铁冶炼系统动力学建模[J]. 中国电力, 2024, 57(8): 36-45.
[15]	王泽嘉, 韩民晓, 范溢文. 基于SVG附加电流反馈阻抗重塑的双馈风电场次/超同步振荡抑制策略[J]. 中国电力, 2024, 57(8): 55-66.

模态框（Modal）标题

考虑多风电场功率相关性的概率潮流联合分布计算

Joint Distribution Calculation with Probabilistic Power Flow Considering Dependencies Among Multiple Wind Power Generations

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics