Ant Colony Optimization Algorithm for the Multiyear Transmission Network Expansion Planning

Current Transmission Network Expansion Planning (TNEP) models are usually strongly simplified in order to achieve optimal solutions within reasonable execution times and computational resources. Examples of these simplifications are the use of reduced network equivalents and the consideration of only a few years within the planning horizon. Due to these simplifications, current TNEP models do not always meet the requirements needed for practical applications. This is particularly true in case of power systems with increased use of renewable energies in which case the levels of variability and uncertainty require a better representation of the system. To meet these new challenges and achieve a time-effective increase of the transmission capacity for the integration of renewable energies, models that consider more accurate representations of power systems are needed. These models must also be able to handle realistic-size power systems in order to serve as supporting tool for real planning processes. In this article, a novel heuristic model based on Ant Colony Optimization for the multi-year TNEP is presented. The characteristics of ACO algorithms make the proposed model especially suitable for considering several expansion options, larger planning horizons, and several load-generation profiles. For validating the model, 25 years plans were calculated in the Garver's 6-bus system and in the IEEE 118-bus system. In both cases, several independent simulations were executed and the results were compared with the ones obtained using a traditional MILP approach. The results showed that all runs found the optimal solution within reasonable computation times, which enables us to validate our model.