Optimal Power Flow by Enhanced Genetic Algorithm

Anastasios G. Bakirtzis, Senior Member, IEEE, Pandel N. Biskas, Student Member, IEEE, Christoforos E. Zoumas, Student Member, IEEE, and Vasilios Petridis, Member, IEEE

Abstract: Tis paper presents an enhanced genetic algorithm (EGA) for the solution of the optimal power flow (OPF) with both continuous and discrete control variables. The continuous control variables modeled are unit active power outputs and generator-bus voltage magnitudes, while the discrete ones are transformer-tap settings and switchable shunt devices. A number of functional operating constraints, such as branch flow limits,
load bus voltage magnitude limits, and generator reactive capabilities, are included as penalties in the GA fitness function (FF). Advanced and problem-specific operators are introduced in order to enhance the algorithm’s efficiency and accuracy. Numerical results on two test systems are presented and compared with
results of other approaches.

Index Terms: Genetic algorithms (GAs), optimal power flow (OPF).

VER MAS...