One of the new challenges arising from the transition of the energy industry to the path of intelligent development is to assess the effect of distributed generation (DG) on the prospects for the development of regional energy supply systems. Such an assessment requires that the factors characterized by high uncertainty be taken into account. In this case, it is expedient to employ a combination of the optimization method with the Monte Carlo method. Such an approach has already been adopted in a model (computer program) developed at the Melentiev Energy Systems Institute, Siberian Branch of the Russian Academy of Sciences. This model is designed to determine the rational mix of new power plants (with investment risks assessed and factored in) and the likely cost of electricity generation in a given aggregated region. We propose using this model as a source of projected data for an approximate assessment of the DG expansion, given the projected conditions for the energy sector and electric power industry development. It may also provide the basis for an array of research tools for relevant studies. The new toolkit requires a more detailed representation of the administrative division and the inclusion of consumers with their sources of electric power generation in the generating capacity. Although such an estimate is approximate, it can give an overall idea of the extent to which the cost and demand for electricity may vary under different options for the DG expansion in a region.