**3. Solar Generation Forecasting**

Planification of electrical networks that include renewable generators is a challenge, since it is necessary to consider their intermittency into the planning project. Due to that, in this research, we are interested in locating and sizing PV plants in DC networks to diminish greenhouse emissions produced by diesel generators for isolated areas, it being strictly necessary to know the PV potential in these areas. For this purpose, we consider that this electrical network is located in the Caribbean region in Colombia, and the solar power availability measured during a year is presented in Figure 1.

**Figure 1.** Historical data for solar prediction (adapted from [4,50]).

On the other hand, the uncertainty of primary sources for PV plants due to temperature and solar radiation produces a challenge for their optimal location and sizing. An improper location or sizing of PV plants can generate problems in the voltage profiles or cause transmission line overload and increase power loss [4]. Therefore, it is necessary to consider a methodology that takes into account the high variability of the temperature and solar radiation with the purpose of reducing the forecasting errors, and thus, avoiding problems that can be introduced due to incorrect location or sizing. For this purpose, we employ the methodology developed in [50], which uses an artificial neural network (ANN) in order to estimate the primary sources for PV plants adequately.
