Transmission Expansion Planning (TEP) is a process of selection of transmission construction plans to meet growing demand in the future. The selected construction plan must have the lowest total cost while maintaining the ability of the transmission system to securely transfer power. Mathematically, TEP is classified as a Mixed Integer Nonlinear Programming problem (MINLP). This problem combines difficulties of both nonlinear programming and integer programming together. Considering planning period, TEP can also be divided into 2 problems, i.e. single stage planning which does not consider change of demand and multi stage planning where demand growth is taken into account. Genetic Algorithm (GA) is one of the techniques to solve the optimization problem which is suitable for handling the MINLP. In this thesis, the GA is used to solve multi stage transmission expansion problems. The TEP considering in this thesis comprises construction of transmission lines, and installation of shunt reactive compensators. In addition, system voltage stability constraint is also considered through the PQ-Voltage Stability Index (PQVSI). All the TEPs in this thesis are formulated using AC models. The proposed method has been tested with the modified-Garver 6-bus and the IEEE-RTS79 test systems. Satisfactory results were obtained.
