TY - GEN
T1 - Feature selection for intelligent stability assessment of power systems
AU - Zhang, Rui
AU - Xu, Yan
AU - Dong, Zhao Yang
AU - Hill, David J.
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2012
Y1 - 2012
N2 - Intelligent System (IS) strategy have been widely adopted in facilitating real-time stability assessment of modern power systems. Typically, the development of such an IS comprises four steps: database generation, input/output specification, knowledge extraction, and validation. While current research efforts are mainly focusing on the third step, much less attention is paid to the second step, which actually is very important to the performance of the IS. It is also noted that only a limited number of feature selection methods were used in the literature. In this paper, systematical study, review and comparisons of feature selection technique are conducted, through which better understanding and decision-support for incorporating a feature selection technique in an IS can be obtained. Additionally, this paper also introduces two alternative feature selection methods, which can be applied in this area. Numerical simulations are also conducted to verify the studied approaches. The immediate value of this paper is that it provides straightforward guideline and reference to researchers who intend to integrate effective feature selection in developing an IS-based stability assessment model. © 2012 IEEE.
AB - Intelligent System (IS) strategy have been widely adopted in facilitating real-time stability assessment of modern power systems. Typically, the development of such an IS comprises four steps: database generation, input/output specification, knowledge extraction, and validation. While current research efforts are mainly focusing on the third step, much less attention is paid to the second step, which actually is very important to the performance of the IS. It is also noted that only a limited number of feature selection methods were used in the literature. In this paper, systematical study, review and comparisons of feature selection technique are conducted, through which better understanding and decision-support for incorporating a feature selection technique in an IS can be obtained. Additionally, this paper also introduces two alternative feature selection methods, which can be applied in this area. Numerical simulations are also conducted to verify the studied approaches. The immediate value of this paper is that it provides straightforward guideline and reference to researchers who intend to integrate effective feature selection in developing an IS-based stability assessment model. © 2012 IEEE.
KW - feature selection
KW - intelligent system (IS)
KW - real-time stability assessment
UR - https://www.scopus.com/pages/publications/84870603890
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84870603890&origin=recordpage
U2 - 10.1109/PESGM.2012.6344780
DO - 10.1109/PESGM.2012.6344780
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781467327275
T3 - IEEE Power and Energy Society General Meeting
BT - 2012 IEEE Power and Energy Society General Meeting, PES 2012
T2 - 2012 IEEE Power and Energy Society General Meeting, PES 2012
Y2 - 22 July 2012 through 26 July 2012
ER -