Title :
System identification for the prediction of the electric energy consumption of a dairy firm
Author :
Frosini, Lucia ; Petrecca, Giovanni
Author_Institution :
Dept. of Electr. Eng., Pavia Univ., Italy
Abstract :
A system identification method based on black-box techniques for the prediction of the electric energy consumption in a dairy firm is presented. This prediction is required by the Italian free energy market where the energy sellers aim at selling energy according to a load flow scheduled some days in advance. The black-box identification is employed as an alternative to an energy investigation of the firm. The inputs of the system are the work shifts of each process unit and the output is the electric energy consumption. Two black-box parametric models have been evaluated-linear and neural-and the principal component analysis method has been employed to preprocess the data
Keywords :
dairying; load flow; neural nets; power consumption; power engineering computing; power system identification; principal component analysis; Italian free energy market; dairy firm; electric energy consumption prediction; energy sellers; linear black-box parametric model; neural black-box parametric model; principal component analysis; process unit; scheduled load flow; system identification method; work shifts; Electric variables control; Energy consumption; Energy management; Job shop scheduling; Load flow; Load forecasting; Parametric statistics; Principal component analysis; System identification; Thermal management;
Conference_Titel :
Soft Computing in Industrial Applications, 2001. SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on
Conference_Location :
Blacksburg, VA
Print_ISBN :
0-7803-7154-2
DOI :
10.1109/SMCIA.2001.936726