Transmission expansion planning with wind sources based on constructive metaheuristics

In this work, a new methodology is proposed to solve the transmission expansion planning (TEP) problem, considering the intermittence of renewable energy, in particular wind power sources. The variability of these sources is represented by means of scenarios, obtained with the K-Means classification algorithm, which allows preserving the correlation among generating stations. The identification of the best expansion plan for each defined scenario is initially performed based on the use of a constructive metaheurístic algorithm (CMA-TEP). Then, by means of two heuristic steps, an interactive and a combinatorial one, the solutions obtained for each scenario are converged to a single solution, capable of attending to all considered wind generation scenarios. The performance of the proposed methodology is tested through the IEEE-RTS system, modified to include a significant share of wind energy. A linear DC network model with losses is used to represent the system grid and the “N-1” security criterion is ensured during the search for the best solutions.