Title :
Reactive power optimization and voltage control using an improved genetic algorithm
Author :
Liu, S.C. ; Zhang, J.H. ; Liu, Z.Q. ; Wang, H.Q.
Author_Institution :
Coll. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
This paper presents an improved dynamic genetic algorithm (IDGA) for reactive power optimization and voltage control. The problem is formulated as a mixed integer, nonlinear optimization problems considering both continuous and discrete control variables. The objective of optimization is minimizing active power losses while maintaining the quality of voltages. During evolution process, the crucial parameters, including mutation and crossover rate, are adjusted dynamically in order to get the optimal global solution. The IEEE standards 14 and 30 bus systems were used as test systems to demonstrate the applicability and efficiency of the proposed method. The results, compared with classical genetic algorithm and previous approaches reported in the literature, show that IDGA could find high-quality solutions with more reliability and efficiency.
Keywords :
genetic algorithms; optimal control; reactive power control; voltage control; IEEE standard 14 bus systems; IEEE standard 30 bus systems; active power losses; continuous control variables; crossover rate; discrete control variables; improved dynamic genetic algorithm; nonlinear optimization problems; reactive power optimization; voltage control; Biological information theory; Capacitors; Gallium; Nickel; Robustness; Genetic Algorithms; IEEE Standards; Losses; Optimal Control; Optimization Methods; Power Quality; Power Systems; Reactive Power Control; VAR; Voltage Control;
Conference_Titel :
Power System Technology (POWERCON), 2010 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4244-5938-4
DOI :
10.1109/POWERCON.2010.5666654