Abstract
The development of distribution systems consists in determining the optimal site and size of new substations and feeders in order to optimize the future power demand with minimum investment and operational costs and a suitable level of consistency. This problem is a combination of, non-linear and constrained optimization problem. Several optimization methods, such as genetic algorithms, simulated annealing, hybrid genetic algorithm and variable neighbourhood search have been reported in the literature where several optimization methods have been stated with the uses of the minor structures while the others have extensive solution time. The main goal behind this thesis is to presents optimization methodologies in the aim to provide a close optimum solution for the (DG) in distribution networks. In the presented methods we take into our account the randomness of distributed generation based on renewable energies, as well as the randomness of electric demand in the planning horizon. First, state-of-the-art research is carried out on existing models for generation planning in electrical systems and distribution network planning models...
D.Ing. (Electrical and Electronic Engineering)