Intelligent techniques applied to power plant

Author

Lee, Kwang Y.

Author_Institution

Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA

fYear

0

fDate

0-0 0

Abstract

Developments in power plant control are increasing steadily in recent years by seeking new techniques other than conventional PID controls. This panel introduces intelligent techniques to power plant control, which deal with complex dynamic systems having significant uncertainties. As for intelligent techniques, neural network (NN), fuzzy logic (FL), evolutionary programming (EP), genetic algorithm (GA), particle swarm optimization (PSO) and multi-agent system (MAS) are presented for the power plant control. Intelligent techniques provide control methodologies that improve the performance of the plant in a wide-range of operation. Moreover, intelligent techniques are shown to overcome the unpredictable dynamics, computational complexity and problems associated with large-scale distributed complex power plants

Keywords

control engineering computing; fuzzy logic; genetic algorithms; intelligent control; multi-agent systems; neurocontrollers; particle swarm optimisation; power engineering computing; power station control; three-term control; PID controls; complex dynamic systems; computational complexity; evolutionary programming; fuzzy logic; genetic algorithm; intelligent techniques; large-scale distributed complex power plants; multiagent system; neural network; particle swarm optimization; power plant control; Computational intelligence; Control systems; Fuzzy logic; Genetic programming; Intelligent networks; Logic programming; Neural networks; Power generation; Three-term control; Uncertainty; Intelligent techniques; evolutionary programming; fuzzy logic; genetic algorithm; multi-agent system; neural network; particle swarm optimization; power plant control;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Society General Meeting, 2006. IEEE

Conference_Location

Montreal, Que.

Print_ISBN

1-4244-0493-2

Type

conf

DOI

10.1109/PES.2006.1709609

Filename

1709609