Generating statistically consistent synthetic power networks for testing renewable integration models

Abstract

Power grids deal with new challenges such as the integration of renewable energies. Research projects in this field develop power systems models to study RES integration. However, they find in the lack of available information about the power grid an obstacle to test those models. The generation of synthetic power networks is crucial to provide power-grid cases in order to design and test new renewable integration models. Although several algorithms were recently proposed to generate synthetic networks, they disregard the electrical features that characterize power grids. We introduce a new algorithm to generate synthetic networks that tries to mimic the historical evolution of power networks. It generates a set of nodes and links them based on economic and technical criteria. This new algorithm provides networks that are topologically consistent with the features of real power grids. It is also flexible by allowing generating grids with different topologies.