Title :
Formulation of loss minimization problem using genetic algorithm and line-flow-based equations
Author :
Jaganathan, Sharanya ; Sekar, Arun ; Gao, Wenzhong
Author_Institution :
Dept. of Electr. & Comput. Eng., Tennessee Tech Univ., Cookeville, TN, USA
Abstract :
Optimization problems in the steady state analysis of power systems aim at minimizing or maximizing some objective function. Traditional methods use mathematical programming techniques to obtain the optimum solution. Artificial intelligence (AI) methods have been shown to exhibit greater flexibility in solving the optimization problem. Genetic algorithm (GA) technique is used in the paper with a new formulation of system equations based on line flow variables. MATLAB GA toolbox is applied to solve the equations. An example system demonstrates the effectiveness of the formulation. Future extension are indicated.
Keywords :
genetic algorithms; load flow; losses; mathematical programming; mathematics computing; power system analysis computing; power system management; MATLAB GA toolbox; genetic algorithm; line flow equations; loss minimization problem; mathematical programming; optimization problem; power system steady state analysis; Artificial intelligence; Equations; Evolution (biology); Genetic algorithms; Minimization methods; Power system analysis computing; Power systems; Reactive power; Steady-state; Voltage; Bus incidence matrix; Genetic Algorithm (GA)Matlab GA toolbox; Line flow based equation; Loss minimization; Optimization; Power system;
Conference_Titel :
Power Symposium, 2008. NAPS '08. 40th North American
Conference_Location :
Calgary, AB
Print_ISBN :
978-1-4244-4283-6
DOI :
10.1109/NAPS.2008.5307358