In the past decade, thanks to abundant data and adequate soft- ware tools, complex networks have been thoroughly investi- gated in many disciplines. Most of this work has dealt with networks in which distances do not have physical meaning and are just dimensionless quantities measured in terms of edge hops. However, in many cases the physical space in which networks are embedded and the actual distances be- tween nodes are important, such as in geographical and trans- portation networks. The Random Geometric Graph (RGG) is a standard spatial network model that plays a role for spatial networks similar to the one played by the Erdo ̈s-Re ́nyi ran- dom graph for relational ones. In this work we present an extension of the RGG construction to define a new model to build bi-dimensional spatial networks based on energy as re- alistic constraint to create the links. The constructed networks have several properties in common with those of actual social networks.