Title: Fuzzy rule-based methodology for residential load behaviour forecasting during power systems restoration

Authors: Lia Toledo Moreira Mota, Alexandre Assis Mota, Andre Luiz Morelato Franca

Addresses: School of Electrical and Computer Engineering, State University of Campinas (UNICAMP), Av.: Albert Einstein, 400, Cidade Universitaria, CEP 13081-970, Campinas, Sao Paulo, Brazil. ' School of Electrical and Computer Engineering, State University of Campinas (UNICAMP), Av.: Albert Einstein, 400, Cidade Universitaria, CEP 13081-970, Campinas, Sao Paulo, Brazil. ' School of Electrical and Computer Engineering, State University of Campinas (UNICAMP), Av.: Albert Einstein, 400, Cidade Universitaria, CEP 13081-970, Campinas, Sao Paulo, Brazil

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.

Keywords: energy management systems; fuzzy logic; power system distribution; power system restoration; residential load forecasting; thermostatically controlled loads; load behaviour estimation; artificial intelligence.

DOI: 10.1504/IJCAT.2005.006938

International Journal of Computer Applications in Technology, 2005 Vol.22 No.2/3, pp.73 - 79

Published online: 26 Apr 2005 *

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