ANDREA: A long-term dynamic planning tool for subtransmission electricity networks

Network expansion planning is a complex, nonconvex, combinatorial problem. Different techniques, such as mathematical optimization, heuristics, and metaheuristics, have been traditionally used to solve this problem. This paper presents a new model, ANDREA, which is intended to obtain near optimal networks for both the static and dynamic planning. This tool has been developed to determine when and where new lines and transformers have to be installed in subtransmission real size networks to supply the estimated future demand considering security of supply criteria, with a low computational effort. A fast guided tree search algorithm (GTSA) using smart selection criteria has been designed to solve this problem. Comparison of the obtained results has been made with those provided by a slower genetic algorithm (GA). Both algorithms were tested in a real subtransmission network.