Forecasting of Wind Capacity Ramp Events Using Typical Event Clustering Identification

With the large-scale integration of wind generation into the power grid, violent wind speed fluctuation will cause wind power ramp events that can affect the safe and stable operation of power systems. In this article, a forecasting method for day-ahead ramp events is proposed based on wind speed ev...

Full description

Bibliographic Details
Main Authors:	Jiang Li, Tianyu Song, Bo Liu, Haotian Ma, Jikai Chen, Yujian Cheng
Format:	Article
Language:	English
Published:	IEEE 2020-01-01
Series:	IEEE Access
Subjects:	Ramp events event clustering identification wind power uncertainty event forecasting
Online Access:	https://ieeexplore.ieee.org/document/9205917/

id	doaj-80f213a9ce734522ab1d31e6b3480301
record_format	Article
spelling	doaj-80f213a9ce734522ab1d31e6b34803012021-03-30T03:48:40ZengIEEEIEEE Access2169-35362020-01-01817653017653910.1109/ACCESS.2020.30268649205917Forecasting of Wind Capacity Ramp Events Using Typical Event Clustering IdentificationJiang Li0https://orcid.org/0000-0002-8208-912XTianyu Song1https://orcid.org/0000-0002-5286-2089Bo Liu2https://orcid.org/0000-0002-8804-1741Haotian Ma3https://orcid.org/0000-0003-2114-5586Jikai Chen4https://orcid.org/0000-0002-2029-1103Yujian Cheng5https://orcid.org/0000-0002-8942-5536School of Electrical Engineering, Northeast Electric Power University, Jilin City, ChinaSchool of Electrical Engineering, Northeast Electric Power University, Jilin City, ChinaSchool of Electrical Engineering, Northeast Electric Power University, Jilin City, ChinaSchool of Electrical Engineering, Northeast Electric Power University, Jilin City, ChinaSchool of Electrical Engineering, Northeast Electric Power University, Jilin City, ChinaNanjing Nanrui Jibao Electric Company, Ltd., Nanjing, ChinaWith the large-scale integration of wind generation into the power grid, violent wind speed fluctuation will cause wind power ramp events that can affect the safe and stable operation of power systems. In this article, a forecasting method for day-ahead ramp events is proposed based on wind speed event definition and profile analysis. Firstly, event-based K-means (EB-K) clustering is used to preprocess historical wind speed. Typical event indexes, such as change rate, amplitude, and time intervals are then extensively used to describe ramp event characteristics and decrease the computational burden for the following event identification within given intervals. Then, the similarity of wind power event set is obtained through empirical probability estimation of successive history ramp events. Typical event clustering identification (TECI) algorithm based on EB-K clustering, wind capacity events, and event cluster profiles is proposed to search the maximum occurrence probability for historical data with the similarity indicator. Finally, a case study on a practical farm in Hebei, China is used to verify the effectiveness and accuracy of wind capacity ramp event forecasting by using TECI.https://ieeexplore.ieee.org/document/9205917/Ramp eventsevent clustering identificationwind power uncertaintyevent forecasting
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Jiang Li Tianyu Song Bo Liu Haotian Ma Jikai Chen Yujian Cheng
spellingShingle	Jiang Li Tianyu Song Bo Liu Haotian Ma Jikai Chen Yujian Cheng Forecasting of Wind Capacity Ramp Events Using Typical Event Clustering Identification IEEE Access Ramp events event clustering identification wind power uncertainty event forecasting
author_facet	Jiang Li Tianyu Song Bo Liu Haotian Ma Jikai Chen Yujian Cheng
author_sort	Jiang Li
title	Forecasting of Wind Capacity Ramp Events Using Typical Event Clustering Identification
title_short	Forecasting of Wind Capacity Ramp Events Using Typical Event Clustering Identification
title_full	Forecasting of Wind Capacity Ramp Events Using Typical Event Clustering Identification
title_fullStr	Forecasting of Wind Capacity Ramp Events Using Typical Event Clustering Identification
title_full_unstemmed	Forecasting of Wind Capacity Ramp Events Using Typical Event Clustering Identification
title_sort	forecasting of wind capacity ramp events using typical event clustering identification
publisher	IEEE
series	IEEE Access
issn	2169-3536
publishDate	2020-01-01
description	With the large-scale integration of wind generation into the power grid, violent wind speed fluctuation will cause wind power ramp events that can affect the safe and stable operation of power systems. In this article, a forecasting method for day-ahead ramp events is proposed based on wind speed event definition and profile analysis. Firstly, event-based K-means (EB-K) clustering is used to preprocess historical wind speed. Typical event indexes, such as change rate, amplitude, and time intervals are then extensively used to describe ramp event characteristics and decrease the computational burden for the following event identification within given intervals. Then, the similarity of wind power event set is obtained through empirical probability estimation of successive history ramp events. Typical event clustering identification (TECI) algorithm based on EB-K clustering, wind capacity events, and event cluster profiles is proposed to search the maximum occurrence probability for historical data with the similarity indicator. Finally, a case study on a practical farm in Hebei, China is used to verify the effectiveness and accuracy of wind capacity ramp event forecasting by using TECI.
topic	Ramp events event clustering identification wind power uncertainty event forecasting
url	https://ieeexplore.ieee.org/document/9205917/
work_keys_str_mv	AT jiangli forecastingofwindcapacityrampeventsusingtypicaleventclusteringidentification AT tianyusong forecastingofwindcapacityrampeventsusingtypicaleventclusteringidentification AT boliu forecastingofwindcapacityrampeventsusingtypicaleventclusteringidentification AT haotianma forecastingofwindcapacityrampeventsusingtypicaleventclusteringidentification AT jikaichen forecastingofwindcapacityrampeventsusingtypicaleventclusteringidentification AT yujiancheng forecastingofwindcapacityrampeventsusingtypicaleventclusteringidentification
_version_	1724182853598576640

Forecasting of Wind Capacity Ramp Events Using Typical Event Clustering Identification

Similar Items