Title :
Evolutionary programming based optimal power flow algorithm
Author :
Yuryevich, Jason ; Wong, Kit Po
Author_Institution :
Dept. of Electr. & Electron. Eng., Western Australia Univ., Nedlands, WA, Australia
fDate :
11/1/1999 12:00:00 AM
Abstract :
This paper develops an efficient and reliable evolutionary programming algorithm for solving the optimal power flow (OPF) problem. The class of curves used to describe generator performance does not limit the algorithm and the algorithm is also less sensitive to starting points. To improve the speed of convergence of the algorithm as well as its ability to handle larger systems, the algorithm is enhanced with gradient information. In the paper, the main elements of the evolutionary programming based OPF algorithm are presented. The algorithm is then demonstrated on the IEEE 30 bus test system
Keywords :
control system analysis computing; control system synthesis; evolutionary computation; load flow control; optimal control; power system analysis computing; power system control; IEEE 30 bus test system; computer simulation; control design; control simulation; convergence speed; evolutionary programming; generator performance; gradient information; optimal power flow algorithm; starting points; Acceleration; Constraint optimization; Costs; Genetic programming; Load flow; Power system analysis computing; Power system economics; Power system reliability; Power systems; System testing;
Journal_Title :
Power Systems, IEEE Transactions on
