Title :
An application of mean field theory to optimal power flow
Author :
Chen, Luonan ; Aihara, Kazuyuki
Author_Institution :
KCC Ltd., Tokyo, Japan
Abstract :
This paper aims at proposing a new method based on mean field theory to cope with the mixed nonlinear integer programming, especially with optimal power flow problems. That is, the first step is to establish the energy function as well as the related partition function, and then to take advantage of the characteristics of the original problem to integrate out the discrete variables. The second step is to derive mean field equations by carrying out saddle approximation. Numerical simulations have verified effectiveness of this approach for a small power system
Keywords :
integer programming; load flow; nonlinear programming; power systems; energy function; mean field theory; mixed nonlinear integer programming; optimal power flow; partition function; saddle approximation; Chaos; Equations; Linear programming; Load flow; Neural networks; Newton method; Phase shifters; Phase transformers; Power generation; Simulated annealing;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.487536