Improved genetic algorithms for optimal power flow under both normal and contingent operation States

This paper presents an improved genetic algorithm (IGA) to solve the problem of optimal power flow. The GA, with the dynamical hierarchy of the coding system developed in this paper, has the ability to code a large number of control variables in a practical system within a reasonable length string. It is, therefore, able to regulate the active power outputs of generators, bus voltages, shunt capacitors/ reactors and transformer tap-settings to minimize the fuel costs. Two cases in the IEEE 30-bus system for both normal and contingent operation states have been studied. In the contingent state, the circuit outage is simulated in one branch which causes a power flow violation in the other branch. The IGA always finds the best results and eliminates operational and insecure violations.