In preparation for the electric mobility technological transition in Colombia, an impact assessment of the electric power system is required, considering the increasing loading that must be able to be managed in the future. In this paper, a plug-in electric vehicle (PEV) charging simulation methodology is developed in order to dimension the impact of this type of load on power grids. PEV electric properties, user charging behaviors, geographic location, trip distances, and other variables of interest are modeled from empirical or known probability distributions and later evaluated in different scenarios using Monte Carlo simulation and load flow analysis. This methodology is later applied to the transmission network of Antioquia (a department of Colombia) resulting in load increases of up to 40% on transmission lines and 20% on transformers in a high PEV penetration scenario in 2030, increases that are well within the expected grid capacity for that year, avoiding the need for additional upgrades.

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Due to the increasing size of electric power systems and its monitoring and operation needs, people at control rooms face complex situations, analyzing great amounts of information, protocols, operation states, alarms, and control parameters. Additionally, new renewable energy sources data is taking its place nowadays, hindering the process of quickly reading and interpreting information. This is known as the loss of Situational Awareness, SA, of system operators. This work presents proposals for displaying useful information in control rooms and visualization techniques to support accurate SA. Grid data displays, maps, trending graphics, lists, bars graphics, table plots, hierarchical levels, proximity regions, and connections are also proposed and analyzed, presenting an application case in a microgrid control room.

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