FSQV and artificial neural networks to voltage stability assessment

• Type: Article in International Conference Proceedings Book
• Date: 2006

Authors

Andrade, AC (Author) Other; Fernando Maciel Barbosa (Author) FEUP; Khodr, HM (Author) Other

Conference proceedings International

Title: 2006 IEEE/PES TRANSMISSION & DISTRIBUTION CONFERENCE & EXPOSITION: LATIN AMERICA, VOLS 1-3

Pages: 532-537

IEEE/PES Transmission and Distribution Conference and Exposition Latin America

Caracas, VENEZUELA, AUG 15-18, 2006

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-004-RCA

DOI: 10.1109/tdcla.2006.311640

Abstract (EN): This paper presents a study of the application of artificial neural network (ANN) to the evaluation of the distance to the voltage collapse point. Voltage stability has been of the major concern in power system operation. To prevent these problems, technical staff evaluates frequently the distance of the operation state to the voltage collapse point. This distance normally is calculated with power flow equations. This classic technique is very slow for electric power systems with large dimension. In abnormal exploration situations it may introduce serious limitation in the voltage stability analysis process. So, the application of a fast and reliable evaluation technique is very important to diminish the evaluation time. This paper also presents the method FSQV (Full sum dQ/dV) for the detection of the collapse point.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6