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The increasing penetration of distributed generation (DG) could cause positive and adverse impacts on distribution power grids. The study of these effects could lead to methodological guidelines for sizing and location of renewable energy sources. In this paper several simulations of a distibution system of MV with different locations and penetration levels of DG are performed. Performance parameters as transmission capacity and voltage level are calculated and the impact of the different penetration scenarios is assessed. Finally a relationship among benefits, the Hosting Capacity (HC), and the distance between feeder-head and DG location is characterized. A new index is proposed to value the better location of units and generation power based on this relationship.

The conventional structure of distribution grids has been changing due to the inclusion of distributed generation (DG) near to consumption centers. This inclusion could have several impacts on chargeability and voltage levels of the distribution systems. In this paper positive and negative impacts of DG penetration are characterized in terms of sizing and location of the DG. Three scenarios of DG sources located at head-feeder, mid-feeder and end-feeder busbars and several penetration levels of DG power are simulated in a local MV network. Indexes for lines chargeability and voltage levels are calculated to assess the impact of different scenarios of DG. We find that in this case voltage level variations are not significantly different for the all simulated scenarios of DG. On the other hand, we find that the magnitude and direction of the power flow affect the chargeability index and downstream locations of DG have stronger impact on this index.

The occurrence of different types of faults and connection of heavy loads could cause voltage sags in several busbars in distribution grids. In this paper a Susceptible-Infected (SI) epidemic model is proposed to assess the propagation of voltage sags in distribution systems. In the SI model, the infectious nodes are the bus-bars where faults or connection of big loads could occur. On the other hand, susceptible nodes are the bus-bars in which voltage sags could occur. Parameters that affect the voltage sags propagation as system topology and detection threshold are modeled using the concept of infection rate (β). + A directed graph representing the voltage sags propagation is calculated based on the values of β between every pair of nodes. Finally, the propagation is characterized in terms of fault impedance and nodes are classified using graph theory indexes.