| Full text | |
| Author(s): |
Moreira Mota, Lia Toledo
;
Mota, Alexandre Assis
;
Morelato Franca, Andre Luiz
Total Authors: 3
|
| Document type: | Journal article |
| Source: | International Journal of Computer Applications in Technology; v. 22, n. 2-3, p. 7-pg., 2005-01-01. |
| Abstract | |
Inadequate load pickup during power system restoration can lead to overload and underfrequency conditions, and even restart the blackout process, due to thermal energy losses. Thus, load behaviour estimation during restoration is desirable to avoid inadequate pickups. This work describes an artificial intelligence method to aid the operator in taking decisions during system restoration by estimating residential load behaviour parameters such as overload in buses and the necessary time to recover steady-state power consumption. This method uses a fuzzy rule-based system to forecast the residential load, obtaining correct estimates with low computational cost. Test results using actual substation data are presented. (AU) | |