Typical Scene Acquisition Strategy for VPP Based on Multi-scale Spectral Clustering Algorithm

Yu Zhu; Zhongkai Yi; Qiuyu Lu; Sijie Liu; Yinliang Xu; Kang Wang

doi:10.1109/EI2.2018.8582357

Typical Scene Acquisition Strategy for VPP Based on Multi-scale Spectral Clustering Algorithm

Yu Zhu^*
, Zhongkai Yi
, Qiuyu Lu
, Sijie Liu
, Yinliang Xu
, Kang Wang

^*Corresponding author for this work

Power Grid Co. Ltd.
Tsinghua University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

The virtual power plant (VPP) technology can effectively realize the connection of distributed resources and power systems, and is benefit to the safety and economical operation of power systems. This paper considers the value of electric and heat load, fluctuation and changing trend of renewable energy sources such as wind power and photovoltaic. A multi-scale similarity metric method for multi kinds of flexible resources in VPP is proposed, which can be used to measure the similarity of different scenes in a VPP. Based on the proposed multi-scale similarity metric method, the multiscale spectral clustering algorithm is used to obtain typical scenes of VPP. Simulation results show that based on the proposed multi-scale spectral clustering algorithm, considering different kinds of flexible resources, typical scene of VPP can be obtained effectively. And the proposed strategy has satisfying performance and high stability. Also it offers a certain guiding significance for the analysis of VPP flexibility resources, rational allocation of resources and optimization planning.

Original language	English
Title of host publication	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538685495
DOIs	https://doi.org/10.1109/EI2.2018.8582357
State	Published - 19 Dec 2018
Externally published	Yes
Event	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Beijing, China Duration: 20 Oct 2018 → 22 Oct 2018

Publication series

Name	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings

Conference

Conference	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018
Country/Territory	China
City	Beijing
Period	20/10/18 → 22/10/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Multi-scale similarity metric
Spectral Clustering Algorithm
Typical Scene
Virtual power plants

Access to Document

10.1109/EI2.2018.8582357

Cite this

Zhu, Y., Yi, Z., Lu, Q., Liu, S., Xu, Y., & Wang, K. (2018). Typical Scene Acquisition Strategy for VPP Based on Multi-scale Spectral Clustering Algorithm. In 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings Article 8582357 (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EI2.2018.8582357

Zhu, Yu ; Yi, Zhongkai ; Lu, Qiuyu et al. / Typical Scene Acquisition Strategy for VPP Based on Multi-scale Spectral Clustering Algorithm. 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings).

@inproceedings{5292cc04f18c46b9a626603d804ba40a,

title = "Typical Scene Acquisition Strategy for VPP Based on Multi-scale Spectral Clustering Algorithm",

abstract = "The virtual power plant (VPP) technology can effectively realize the connection of distributed resources and power systems, and is benefit to the safety and economical operation of power systems. This paper considers the value of electric and heat load, fluctuation and changing trend of renewable energy sources such as wind power and photovoltaic. A multi-scale similarity metric method for multi kinds of flexible resources in VPP is proposed, which can be used to measure the similarity of different scenes in a VPP. Based on the proposed multi-scale similarity metric method, the multiscale spectral clustering algorithm is used to obtain typical scenes of VPP. Simulation results show that based on the proposed multi-scale spectral clustering algorithm, considering different kinds of flexible resources, typical scene of VPP can be obtained effectively. And the proposed strategy has satisfying performance and high stability. Also it offers a certain guiding significance for the analysis of VPP flexibility resources, rational allocation of resources and optimization planning.",

keywords = "Multi-scale similarity metric, Spectral Clustering Algorithm, Typical Scene, Virtual power plants",

author = "Yu Zhu and Zhongkai Yi and Qiuyu Lu and Sijie Liu and Yinliang Xu and Kang Wang",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 ; Conference date: 20-10-2018 Through 22-10-2018",

year = "2018",

month = dec,

day = "19",

doi = "10.1109/EI2.2018.8582357",

language = "英语",

series = "2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings",

address = "美国",

}

Zhu, Y, Yi, Z, Lu, Q, Liu, S, Xu, Y & Wang, K 2018, Typical Scene Acquisition Strategy for VPP Based on Multi-scale Spectral Clustering Algorithm. in 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings., 8582357, 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018, Beijing, China, 20/10/18. https://doi.org/10.1109/EI2.2018.8582357

Typical Scene Acquisition Strategy for VPP Based on Multi-scale Spectral Clustering Algorithm. / Zhu, Yu; Yi, Zhongkai; Lu, Qiuyu et al.
2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8582357 (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Typical Scene Acquisition Strategy for VPP Based on Multi-scale Spectral Clustering Algorithm

AU - Zhu, Yu

AU - Yi, Zhongkai

AU - Lu, Qiuyu

AU - Liu, Sijie

AU - Xu, Yinliang

AU - Wang, Kang

PY - 2018/12/19

Y1 - 2018/12/19

N2 - The virtual power plant (VPP) technology can effectively realize the connection of distributed resources and power systems, and is benefit to the safety and economical operation of power systems. This paper considers the value of electric and heat load, fluctuation and changing trend of renewable energy sources such as wind power and photovoltaic. A multi-scale similarity metric method for multi kinds of flexible resources in VPP is proposed, which can be used to measure the similarity of different scenes in a VPP. Based on the proposed multi-scale similarity metric method, the multiscale spectral clustering algorithm is used to obtain typical scenes of VPP. Simulation results show that based on the proposed multi-scale spectral clustering algorithm, considering different kinds of flexible resources, typical scene of VPP can be obtained effectively. And the proposed strategy has satisfying performance and high stability. Also it offers a certain guiding significance for the analysis of VPP flexibility resources, rational allocation of resources and optimization planning.

AB - The virtual power plant (VPP) technology can effectively realize the connection of distributed resources and power systems, and is benefit to the safety and economical operation of power systems. This paper considers the value of electric and heat load, fluctuation and changing trend of renewable energy sources such as wind power and photovoltaic. A multi-scale similarity metric method for multi kinds of flexible resources in VPP is proposed, which can be used to measure the similarity of different scenes in a VPP. Based on the proposed multi-scale similarity metric method, the multiscale spectral clustering algorithm is used to obtain typical scenes of VPP. Simulation results show that based on the proposed multi-scale spectral clustering algorithm, considering different kinds of flexible resources, typical scene of VPP can be obtained effectively. And the proposed strategy has satisfying performance and high stability. Also it offers a certain guiding significance for the analysis of VPP flexibility resources, rational allocation of resources and optimization planning.

KW - Multi-scale similarity metric

KW - Spectral Clustering Algorithm

KW - Typical Scene

KW - Virtual power plants

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U2 - 10.1109/EI2.2018.8582357

DO - 10.1109/EI2.2018.8582357

M3 - 会议稿件

AN - SCOPUS:85060889548

T3 - 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings

BT - 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018

Y2 - 20 October 2018 through 22 October 2018

ER -

Zhu Y, Yi Z, Lu Q, Liu S, Xu Y, Wang K. Typical Scene Acquisition Strategy for VPP Based on Multi-scale Spectral Clustering Algorithm. In 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. 8582357. (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings). doi: 10.1109/EI2.2018.8582357

Typical Scene Acquisition Strategy for VPP Based on Multi-scale Spectral Clustering Algorithm

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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