Load uncertainty based transmission network expansion planning

Transmission expansion planning (TEP) is more robust and reliable when it is able to tackle the uncertainty generated by load. In this, paper in order to handle the demand uncertainty a mathematical model is presented. In particular, the uncertainty of each bus load analyzes individually and is expressed in interval number. To solve the DC-Static transmission network expansion planning problem a meta-heuristic population based algorithm named Gbest Artificial Bee Colony (GABC) is proposed. Garver´s 6-bus test system is used to simulate the proposed method and results shows that minimum investment cost can be found considering the uncertainty in demand.