  This paper presents an analysis of the stability and quality of the
distributed generation planning problem's investment solution. The entry of
distributed generators power based on non-conventional energy sources has been
extensively promoted in distribution grids. In this paper, a two-stage
stochastic programming model is used to find the optimal distributed
generators' installed capacities. We emphasize the design of scenarios to
represent the stochasticity of power production on renewable sources. In the
scenario generation, a method is proposed based on the clustering of real
measurements of meteorological variables. We measure the quality and stability
of the investment solution as a function of the number of scenarios. The
results show that a reduced selection of scenarios can give an inadequate
solution to distributed generators' investment strategy.
