Research on Sub-state Quantization Method of Wind Convergence Trend Based on Improved Shapley Value

被引：0

作者：

Cui Y. ^{[1
]}

Qu Y. ^{[1
]}

Zhong W. ^{[2
]}

Lü C. ^{[2
]}

Sun B. ^{[2
]}

Wang Z. ^{[3
]}

Zhang P. ^{[3
]}

Zhao Y. ^{[1
]}

机构：

[1] School of Electrical Engineering, Northeast Electric Power University, Jilin, 132012, Jilin Province

[2] China Electric Power Research Institute, Haidian District, Beijing

[3] Dispatching and Control Center, State Grid Gansu Electric Power Company, Lanzhou, 730030, Gansu Province

来源：

Dianwang Jishu/Power System Technology | 2019年 / 43卷 / 06期

关键词：

Combined prediction; Convergence characteristics; Duration curve; Improved Shapley value method; Wind power output state;

D O I：

10.13335/j.1000-3673.pst.2018.1451

中图分类号：

学科分类号：

摘要：

Wind power output is fluctuant. Due to moderating effect of the output of each unit, the output fluctuation of wind power gradually slows down with wind power scale increase, and the wind power output shows a "convergence effect". It is of great guiding significance to grasp the trend of convergence effect for planning of outgoing transmission lines and capacity configuration. In this paper, the wind power output states are defined and the convergence trend of wind power in each output state is combined. The weight coefficients in the combination forecasting model are determined with the improved Shapley value method, avoiding the phenomenon that the traditional Shapley value method still participates in the combination when the deviation of a single model is too large. Based on quantitative calculation of continuous output curve of each state, a combined forecasting method of wind power continuous output curve is put forward based on analysis of convergence characteristics, and a prediction accuracy evaluation system is established. Validity of the method is verified with measured data. Case study shows that compared with the single prediction model, the combined forecasting method of wind power continuous output curve can accurately describe the trend of wind power convergence. © 2019, Power System Technology Press. All right reserved.

引用

页码：2094 / 2101

页数：7

共 13 条

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