Title :
Finding Improved Local Minima of Power System Optimization Problems by Interior-Point Methods
Author :
Santos, J. R. ; Martinez, Ramos, J. L. ; Lora, A. T. ; Gomez-Exposito, Antonio
Author_Institution :
University of Sevilla
Abstract :
This paper presents a simple heuristic technique to deal with multiple local minima in nonconvex, nonlinear, power system optimization problems by solving a sequence of interior point subproblems. Both the real-valued and the mixed-integer cases are discussed separately. The method is then applied to the unit commitment problem, and its performance on realistic cases is compared with that of a genetic algorithm.
Keywords :
Bayesian methods; Circuits; Genetic algorithms; Lagrangian functions; Load flow; Neural networks; Optimization methods; Power markets; Power systems; Uncertainty; Nonconvex mixed-integer optimization; genetic algorithms; global optimization; interior point algorithms;
Journal_Title :
Power Engineering Review, IEEE
DOI :
10.1109/MPER.2002.4311905
