NDLI: Extreme wind power forecast error analysis considering its application in day-ahead reserve capacity planning

Content Provider	IET Digital Library
Author	Zhang, Fan Qiao, Ying Lu, Zongxiang
Abstract	Accurate wind power forecasting is crucial for setting reserve dimensions of a power system. From the perspective of power grid dispatcher, one of the most critical issues of dealing with the uncertainty brought by wind power forecast error (WPFE) is to analyse its extreme value to decide the new reserve requirements induced by variable wind power. This study targets at predicting the daily maximum of day-ahead WPFE via extreme value analysis approach considering its application of operating reserve planning. Non-stationary block maxima method (NS-BMM) is applied to model the probabilistic characteristic of daily maxima WPFE via fitting the non-linear relationship between distribution parameters and the covariates. To better shape the non-stationarity, a conditional NS-BMM (CNS-BMM) via partition according to wind conditions is proposed. Moreover, indicators to evaluate the quality of applying NS-BMMs in the day-ahead reserve plan are also discussed. Finally, a case study based on the operational data from a typical wind farm in northern China is carried out. Results show that CNS-BMM offers a better model of daily maximum WPFE compared to not only traditional quantile regression but also non-CNS-BMM, and applying the estimate of daily maximum WPFE on reserve plan demonstrates an advantage over conventional three-sigma method.
Starting Page	1923
Ending Page	1930
Page Count	8
ISSN	17521416
Volume Number	12
e-ISSN	17521424
Issue Number	Issue 16, Dec (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rpg/12/16
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2018.5023
Journal	IET Renewable Power Generation
Publisher Date	2018-09-25
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	CNS-BMM Conditional NS-BMM Day-ahead Reserve Capacity Planning Distribution Parameter Error Analysis Error Analysis in Numerical Method Extreme Value Analysis Extreme Wind Power Forecast Error Analysis Nonstationary Block Maxima Method Northern China Power Generation Dispatch Power Generation Economics Power Generation Planning Power Grid Dispatcher Power System Power System Economics Power System Managemen Power System Operation Power System Planning And Layout Probabilistic Daily Maxima WPFE Characteristic Probability Reserve Dimensions Reserve Requirements Statistics Variable Wind Power Wind Farm Wind Power Forecasting Wind Power Plant
Content Type	Text
Resource Type	Article
Subject	Renewable Energy, Sustainability and the Environment

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