Algorithm for identifying wind power ramp events via novel improved dynamic swinging door

With the rapid increase in the penetration of wind power in recent years, wind power ramp events (WPREs) have become the main factors affecting the safety and stability of electric power systems. Accurate detection of ramp events could help power systems better manage the extreme events and reduce e...

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Published inRenewable energy Vol. 171; pp. 542 - 556
Main Authors Cui, Yang, He, Yingjie, Xiong, Xiong, Chen, Zhenghong, Li, Fen, Xu, Taotao, Zhang, Fanghong
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.06.2021
Subjects
Online AccessGet full text
ISSN0960-1481
1879-0682
DOI10.1016/j.renene.2021.02.123

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Abstract With the rapid increase in the penetration of wind power in recent years, wind power ramp events (WPREs) have become the main factors affecting the safety and stability of electric power systems. Accurate detection of ramp events could help power systems better manage the extreme events and reduce economic losses. The previous ramp detection methods are either too complex to implement that influence the computing efficiency, or based on the value of points which cannot completely reflect the trend of data segments and lead to a decrease of accuracy. Based on the above problems and the on-site requirements, this paper proposes a novel improved dynamic swinging door algorithm (ImDSDA) to optimise the state-of-the-art in WPREs detection. Firstly, the swinging door algorithm (SDA) is used to extract ramp segments. Secondly, the dynamic programming method is used for ramp trend identification and segment combination. Finally, raw data obtained from three real-world wind farms in Hubei, China were applied to validate the performance of the proposed ImDSDA. The detection results show that the ImDSDA is more accurate and efficient than the traditional detection methods and could be a feasible option for WPRE detection in power systems. •A novel wind power ramp event detection algorithm is presented.•The algorithm is based on swing door algorithm(SDA) and sliding window(SW).•The optimal ‘door width’ of SDA is obtained.•The algorithm shows good performance both in accuracy and efficiency.•Enable auxiliary decision-making for power systems.
AbstractList With the rapid increase in the penetration of wind power in recent years, wind power ramp events (WPREs) have become the main factors affecting the safety and stability of electric power systems. Accurate detection of ramp events could help power systems better manage the extreme events and reduce economic losses. The previous ramp detection methods are either too complex to implement that influence the computing efficiency, or based on the value of points which cannot completely reflect the trend of data segments and lead to a decrease of accuracy. Based on the above problems and the on-site requirements, this paper proposes a novel improved dynamic swinging door algorithm (ImDSDA) to optimise the state-of-the-art in WPREs detection. Firstly, the swinging door algorithm (SDA) is used to extract ramp segments. Secondly, the dynamic programming method is used for ramp trend identification and segment combination. Finally, raw data obtained from three real-world wind farms in Hubei, China were applied to validate the performance of the proposed ImDSDA. The detection results show that the ImDSDA is more accurate and efficient than the traditional detection methods and could be a feasible option for WPRE detection in power systems.
With the rapid increase in the penetration of wind power in recent years, wind power ramp events (WPREs) have become the main factors affecting the safety and stability of electric power systems. Accurate detection of ramp events could help power systems better manage the extreme events and reduce economic losses. The previous ramp detection methods are either too complex to implement that influence the computing efficiency, or based on the value of points which cannot completely reflect the trend of data segments and lead to a decrease of accuracy. Based on the above problems and the on-site requirements, this paper proposes a novel improved dynamic swinging door algorithm (ImDSDA) to optimise the state-of-the-art in WPREs detection. Firstly, the swinging door algorithm (SDA) is used to extract ramp segments. Secondly, the dynamic programming method is used for ramp trend identification and segment combination. Finally, raw data obtained from three real-world wind farms in Hubei, China were applied to validate the performance of the proposed ImDSDA. The detection results show that the ImDSDA is more accurate and efficient than the traditional detection methods and could be a feasible option for WPRE detection in power systems. •A novel wind power ramp event detection algorithm is presented.•The algorithm is based on swing door algorithm(SDA) and sliding window(SW).•The optimal ‘door width’ of SDA is obtained.•The algorithm shows good performance both in accuracy and efficiency.•Enable auxiliary decision-making for power systems.
Author Xiong, Xiong
Xu, Taotao
Chen, Zhenghong
He, Yingjie
Li, Fen
Zhang, Fanghong
Cui, Yang
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  organization: Chongqing Hai Zhuang Wind Power Equipment Co., Ltd., Chongqing, 401122, China
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Keywords Power system
Dynamic programming
Swinging door algorithm (SDA)
Wind power
Sliding window (SW)
Wind power ramp events (WPREs)
Language English
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Snippet With the rapid increase in the penetration of wind power in recent years, wind power ramp events (WPREs) have become the main factors affecting the safety and...
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StartPage 542
SubjectTerms algorithms
China
Dynamic programming
electric power
Power system
Sliding window (SW)
Swinging door algorithm (SDA)
wind
Wind power
Wind power ramp events (WPREs)
Title Algorithm for identifying wind power ramp events via novel improved dynamic swinging door
URI https://dx.doi.org/10.1016/j.renene.2021.02.123
https://www.proquest.com/docview/2636452605
Volume 171
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