In the last two decades, Uruguay has been immersed in the process of significantly changing its energy generation matrix, especially by the introduction of wind and solar sources. In this context, SimSEE, a simulation and optimization software designed to help decision-making in generating and distributing electrical energy, is extensively used. The design of this tool is conceived for conventional CPUs and follows a sequential execution paradigm. This paper focuses on a refactoring of SimSEE that enables leveraging massively-parallel hardware platforms, seeking to adapt the tool for the increasing size and complexity of Uruguay’s electric market. We extend our previous ideas about reorganizing the software architecture to exploit the parallelism in each time-step of Sim-SEE’s simulation. In more detail, we present two variants following this parallelism pattern, a straightforward parallel version that requires replicating the used memory and a variant that implies limited performance restrictions but requires a minimal memory overhead.