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
Abstract :
Summary form only given. This paper develops an evolutionary programming (EP) based optimal power flow (OPF) solution algorithm which makes use of an EP load flow. Solution acceleration concepts are implemented which improve the basic EP algorithm. This acceleration is implemented using the gradient information obtained using the steepest descent method to perform a local search. The method is capable of determining the global optimum solution to the OPF for a range of constraints and objective functions. The algorithm is not sensitive to starting points and is capable of handling nonconvex generator cost curves. The performances of the algorithm when applied to the IEEE 30-bus test system under different generator input-output curves are presented
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; constraints; control design; control simulation; evolutionary programming; generator input-output curves; gradient information; local search; objective functions; optimal power flow algorithm; power systems; solution acceleration concepts; steepest descent method; Acceleration; Algorithm design and analysis; Genetic programming; Linear programming; Load flow; Optimization methods; Power engineering computing; Power system analysis computing; Power system economics; Power systems;
Conference_Titel :
Power Engineering Society Summer Meeting, 1999. IEEE
Conference_Location :
Edmonton, Alta.
Print_ISBN :
0-7803-5569-5
DOI :
10.1109/PESS.1999.787503