Dynamic and Static Transmission Network Expansion Planning via Harmony Search and Branch & Bound on a Hybrid Algorithm

This work presents a method based on metaheuristics to solve the problem of Static (STNEP) and Dynamic (DTNEP) Transmission Network Expansion Planning in electrical power systems. The result of this formulation is mixed-integer nonlinear programming (MINLP), where the difficulties are intensified in the DTNEP by the temporal coupling. Therefore, a methodology was developed to reach the solution in three different stages: The first one is responsible for obtaining an efficient set of best candidate routes for the expansion; the metaheuristic optimization process, Harmony Search (HS), is used to find STNEP’s optimal solution and its neighborhood that provides a DTNEP candidate zone; lastly, a hybrid algorithm that mixes the HS and Branch & Bound (B&B) concepts is adapted to provide the optimal DTNEP. In this study, the lossless linearized modeling for load flow is used as a representation of the transmission network. Tests with the Garver and southern Brazilian systems were carried out to verify the performance method. The computational time saving for the STNEP and DTNEP prove the efficacy of the proposed method.