|
|
基于箱形图数据清洗的水电站特性曲线修正方法
|
Abstract:
水电站和机组长期运行后，下泄流量~尾水位、水头~耗水率等特性曲线相较于设计参数存在偏差，影响水电计划编制的准确性，该问题在西南地区巨型梯级水电站群普遍存在，需要研究行之有效的解决方法。基于南方电网水电调度生产实践，提出基于箱形图数据清洗的水电站特性曲线修正方法。利用水电站海量历史运行数据构造大数据样本，通过箱型图模型去除异常数据，采用多项式拟合技术对设计曲线进行修正，能够更好地反映发电特性曲线真实关系。实际应用算例证明了方法的有效性。
The characteristic curves, such as tailwater level and net head curve, deviate from the design parameters during the long-term operation of hydropower units, which is difficult to make an accurate hydropower scheduling plan. It is necessary to find an effective solution to address the problem, especially for the giant cascade hydropower stations in Southwest China. A correction method of characteristic curve of hydropower unit based on the box-plot data cleaning is proposed and applied in the hydropower dispatching in China Southern Power Grid. We utilized the massive historical operation data of hydropower station to construct large data samples, used the box-plot model to remove the abnormal data, and adopted the polynomial fitting technology to modify the characteristic curve. The results show that this method can better describe the power generation characteristic curve, and its effectiveness is proved by practical application examples.
| [1] | 陈尧, 马光文, 杨道辉, 等. 水电站综合耗水率参数在水库优化调度中的应用[J]. 水力发电, 2009, 35(4): 22-28.
CHEN Yao, MA Guangwen, YANG Daohui, et al. Application of comprehensive water consumption rate to reservoir operation optimization of hydropower station. Water Power, 2009, 35(4): 22-28. (in Chinese). |
| [2] | 张东霞, 苗新, 刘丽平, 等. 智能电网大数据技术发展研究[J]. 中国电机工程学报, 2015, 35(1): 2-12.
ZHANG Dongxia, MIAO Xin, LIU Liping, et al. Research on development strategy for smart grid big data. Proceedings of the CSEE, 2015, 35(1): 2-12. (in Chinese) |
| [3] | 薛禹胜, 赖业宁. 大能源思维与大数据思维的融合(一): 大数据与电力大数据[J]. 电力系统自动化, 2016, 40(1): 1-8.
XUE Yusheng, LAI Yening. Integration of macro energy thinking and big data thinking: part one big data and power big data. Automation of Electric Power Systems, 2016, 40(1): 1-8. (in Chinese) |
| [4] | 李国杰. 大数据研究的科学价值[J]. 中国计算机学会通讯, 2012, 8(9): 8-15.
LI Guojie. The scientific value of big data. Research Communications of the CCF, 2012, 8(9): 8-15. (in Chinese) |
| [5] | 肖先勇, 王希宝, 季广辉. 基于箱形图和矩估计的敏感元件电压凹陷敏感度评估[J]. 电网技术, 2008, 32(17): 64-68.
XIAO Xianyong, WANG Xibao, and JI Guanghui. Sensitivity assessment of voltage sag for sensitive equipment based on boxplot and moment estimation. Power System Technology, 2008, 32(17): 64-68. (in Chinese) |
| [6] | STREIT, M., GEHLENBORG, N. Bar charts and box plots. Nature Methods, 2014, 11(2): 117.
https://doi.org/10.1038/nmeth.2807 |
| [7] | SCHWERTMAN, N. C., OWENS, M., and ADNAN, R. A simple more general boxplot method for identifying outliers. Computational Statistics & Data Analysis, 2004, 47(1): 165-174. https://doi.org/10.1016/j.csda.2003.10.012 |
| [8] | 罗琴琴, 苏建徽, 林志光, 等. 基于递推最小二乘法的虚拟同步发电机参数辨识方法[J]. 电力系统自动化, 2019, 43(1): 215-221.
LUO Qinqin, SU Jianhui, LIN Zhiguang, et al. Parameter identification methods for virtual synchronous generators based on recursive least squares algorithm. Automation of Electric Power Systems, 2019, 43(1): 215-221. (in Chinese) |
| [9] | 贾秀芳, 华回春, 曹东升, 等. 基于复线性最小二乘法的谐波责任定量划分[J]. 中国电机工程学报, 2013, 33(4): 149-155.
JIA Xiufang, HUA Huichun, CAO Dongsheng, et al. Determining harmonic contributions based on complex least squares method. Proceedings of the CSEE, 2013, 33(4): 149-155. (in Chinese) |
| [10] | 付忠广, 靳涛, 周丽君, 等. 复杂系统反向建模方法及偏最小二乘法建模应用研究[J]. 中国电机工程学报, 2009, 29(2): 25-29.
FU Zhonguang, JIN Tao, ZHOU Lijun, et al. Research and application of the reversed modelling method and partial least-square regression modelling for the complex thermal system. Proceedings of the CSEE, 2009, 29(2): 25-29. (in Chi-nese) |
| [11] | 黎小林, 曹侃, 谢开贵, 等. 基于最小二乘法的高压直流输电系统可靠性灵敏度分析[J]. 电力系统自动化, 2009, 33(18): 12-15.
LI Xiaolin, CAO Kan, XIE Kaigui, et al. Sensitivity analysis of HVDC transmission system reliability using the least square methods. Automation of Electric Power Systems, 2009, 33(18): 12-15. (in Chinese) |
| [12] | 程启明, 王勇浩. 基于最小二乘算的模糊支持向量机控制器及其应用[J]. 中国电机工程学报, 2007, 27(8): 76-80.
CHENG Qiming, WANG Yonghao. The fuzzy support vector network controller based on least square algorithms and its application. Proceedings of the CSEE, 2007, 27(8): 76-80. (in Chinese) |
| [13] | LIU, Z., ZHOU, Y., LIN, L. et al. Some remarks on Jacobi and Gauss-Seidel-type iteration methods for the matrix equation AXB = C. Applied Mathematics and Computation, 2019, 354(C): 305-307. https://doi.org/10.1016/j.amc.2019.02.014 |
| [14] | HADJIDIMOS, A. Successive overrelaxation (SOR) and related methods. Journal of Computational and Applied Mathematics, 2000, 123(1-2): 177-199. https://doi.org/10.1016/S0377-0427(00)00403-9 |
