This work pretends to take advantage of powerful capabilities of computational intelligence to improve the actual features of modeling, prognosis, diagnosis and optimization of load demand for EMS. This work gives a potent complement to the rising new paradigms about renewable energies, distributed generation, micro-grids and smart grids in general, which are in focusing in the optimization or improving of how the energy is generated and not how the energy is used.