Identification and justification of abnormal electric load data based on density evaluation

Shulin Tong; Fushuan Wen; Liang Chen; Jiansheng Huang

doi:10.1109/DRPT.2011.5993997

Identification and justification of abnormal electric load data based on density evaluation

Shulin Tong, Fushuan Wen, Liang Chen, Jiansheng Huang

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

5 Citations (Scopus)

Abstract

![CDATA[There are usually a number of abnormal data in the electric load database derived from the SCADA system, thus it is necessary to identify and justify them before the load data are used for electric load forecasting or power system analysis. Considering both horizontal and vertical continuity of the electric load, a density evaluation based method is proposed to identify and justify abnormal data in two dimensions as a whole. The feasibility and efficiency of the developed method has been demonstrated by simulation results.]]

Original language	English
Title of host publication	Proceedings of the 2011 4th IEEE International Conference on Electric Utility Deregulation, Restructuring, and Power Technologies (DRPT2011), 6-9 July, 2011, Weihai, China
Publisher	IEEE
Pages	776-780
Number of pages	5
ISBN (Print)	9781457703645
DOIs	https://doi.org/10.1109/DRPT.2011.5993997
Publication status	Published - 2011
Event	IEEE International Conference on Electric Utility Deregulation_Restructuring_and Power Technologies - Duration: 6 Jul 2011 → …

Conference

Conference	IEEE International Conference on Electric Utility Deregulation_Restructuring_and Power Technologies
Period	6/07/11 → …

Access to Document

10.1109/DRPT.2011.5993997

Cite this

Tong, S., Wen, F., Chen, L., & Huang, J. (2011). Identification and justification of abnormal electric load data based on density evaluation. In Proceedings of the 2011 4th IEEE International Conference on Electric Utility Deregulation, Restructuring, and Power Technologies (DRPT2011), 6-9 July, 2011, Weihai, China (pp. 776-780). IEEE. https://doi.org/10.1109/DRPT.2011.5993997

@inproceedings{ec62ca7575b14ab583ce20766cd62142,

title = "Identification and justification of abnormal electric load data based on density evaluation",

abstract = "![CDATA[There are usually a number of abnormal data in the electric load database derived from the SCADA system, thus it is necessary to identify and justify them before the load data are used for electric load forecasting or power system analysis. Considering both horizontal and vertical continuity of the electric load, a density evaluation based method is proposed to identify and justify abnormal data in two dimensions as a whole. The feasibility and efficiency of the developed method has been demonstrated by simulation results.]]",

author = "Shulin Tong and Fushuan Wen and Liang Chen and Jiansheng Huang",

year = "2011",

doi = "10.1109/DRPT.2011.5993997",

language = "English",

isbn = "9781457703645",

pages = "776--780",

booktitle = "Proceedings of the 2011 4th IEEE International Conference on Electric Utility Deregulation, Restructuring, and Power Technologies (DRPT2011), 6-9 July, 2011, Weihai, China",

publisher = "IEEE",

note = "IEEE International Conference on Electric Utility Deregulation_Restructuring_and Power Technologies ; Conference date: 06-07-2011",

}

Tong, S, Wen, F, Chen, L & Huang, J 2011, Identification and justification of abnormal electric load data based on density evaluation. in Proceedings of the 2011 4th IEEE International Conference on Electric Utility Deregulation, Restructuring, and Power Technologies (DRPT2011), 6-9 July, 2011, Weihai, China. IEEE, pp. 776-780, IEEE International Conference on Electric Utility Deregulation_Restructuring_and Power Technologies, 6/07/11. https://doi.org/10.1109/DRPT.2011.5993997

Identification and justification of abnormal electric load data based on density evaluation. / Tong, Shulin; Wen, Fushuan; Chen, Liang et al.
Proceedings of the 2011 4th IEEE International Conference on Electric Utility Deregulation, Restructuring, and Power Technologies (DRPT2011), 6-9 July, 2011, Weihai, China. IEEE, 2011. p. 776-780.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

TY - GEN

T1 - Identification and justification of abnormal electric load data based on density evaluation

AU - Tong, Shulin

AU - Wen, Fushuan

AU - Chen, Liang

AU - Huang, Jiansheng

PY - 2011

Y1 - 2011

N2 - ![CDATA[There are usually a number of abnormal data in the electric load database derived from the SCADA system, thus it is necessary to identify and justify them before the load data are used for electric load forecasting or power system analysis. Considering both horizontal and vertical continuity of the electric load, a density evaluation based method is proposed to identify and justify abnormal data in two dimensions as a whole. The feasibility and efficiency of the developed method has been demonstrated by simulation results.]]

AB - ![CDATA[There are usually a number of abnormal data in the electric load database derived from the SCADA system, thus it is necessary to identify and justify them before the load data are used for electric load forecasting or power system analysis. Considering both horizontal and vertical continuity of the electric load, a density evaluation based method is proposed to identify and justify abnormal data in two dimensions as a whole. The feasibility and efficiency of the developed method has been demonstrated by simulation results.]]

UR - http://handle.uws.edu.au:8081/1959.7/543344

UR - http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=18607

U2 - 10.1109/DRPT.2011.5993997

DO - 10.1109/DRPT.2011.5993997

M3 - Conference Paper

SN - 9781457703645

SP - 776

EP - 780

BT - Proceedings of the 2011 4th IEEE International Conference on Electric Utility Deregulation, Restructuring, and Power Technologies (DRPT2011), 6-9 July, 2011, Weihai, China

PB - IEEE

T2 - IEEE International Conference on Electric Utility Deregulation_Restructuring_and Power Technologies

Y2 - 6 July 2011

ER -

Identification and justification of abnormal electric load data based on density evaluation

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this