Resumo:
The new Smart Grid technologies offer increasingly integrated solutions, enabling customers to act as prosumers, incorporate electric vehicles, and use internet-connected appliances for load optimization. At the same time, the growing penetration of distributed generation, the intermittency of renewable sources, and the increase in energy costs make it essential to adopt efficient energy management strategies through Energy Management Systems (EMS) integrated with Advanced Distribution Management Systems (ADMS) and Microgrid Central Controllers (MGCC). These systems must be capable of quickly responding to high-impact, low-probability (HILP) events without large investments.
In this context, this work proposes an optimization approach to increase the service capacity of distribution networks using Mobile Battery Energy Storage Systems (MTBESS). The methodology combines a heuristic based on Artificial Immune Systems (AIS) with Mixed-Integer Linear Programming (MILP) for the optimal dispatch and relocation of units, considering travel routes. The multi-objective model aims, in addition to increasing service capacity, to reduce technical losses, minimize voltage deviations, and balance demand among circuits, ensuring efficient and reliable operation. Application to a modified 33-bus system and a large-scale real network, using real traffic data, demonstrated significant service capacity gains in contingencies and improvements in operational efficiency under normal conditions.
