Wind Power Interval Forecasting Based on Confidence Interval Optimization

Xiaodong Yu, Wen Zhang, Hongzhi Zang and Hao Yang
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Xiaodong Yu: School of Electrical Engineering, Shandong University, Jinan 250061, China
Wen Zhang: School of Electrical Engineering, Shandong University, Jinan 250061, China
Hongzhi Zang: Economic & Technology Research Institute, State Grid Shandong Electric Power Company, Jinan 250001, China
Hao Yang: School of Electrical Engineering, Shandong University, Jinan 250061, China

Energies, 2018, vol. 11, issue 12, 1-15

Abstract: Most of the current wind power interval forecast methods are based on the assumption the point forecast error is subject to a known distribution (such as a normal distribution, beta distribution, etc.). The interval forecast of wind power is obtained after solving the confidence interval of the known distribution. However, this assumption does not reflect the truth because the distribution of error is random and does not necessary obey any known distribution. Moreover, the current method for calculating the confidence interval is only good for a known distribution. Therefore, those interval forecast methods cannot be applied generally, and the forecast quality is not good. In this paper, a general method is proposed to determine the optimal interval forecast of wind power. Firstly, the distribution of the point forecast error is found by using the non-parametric Parzen window estimation method which is suitable for the distribution of an arbitrary shape. Secondly, an optimal method is used to find the minimum confidence interval of arbitrary distribution. Finally the optimal forecast interval is obtained. Simulation results indicate that this method is not only generally applicable, but also has a better comprehensive evaluation index.

Keywords: wind power; interval forecast; non-parameter Parzen window estimation; confidence interval optimization; F value (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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