Monte Carlo simulation-based probabilistic assessment of DG penetration in medium voltage distribution networks

•Uncertainties affect the evaluation of the system capacity to accommodate DG units.•Deterministic LF analysis may overlook the risk of limit violations.•DG penetration with Monte Carlo accounts for the variability of power consumption.•Load variability significantly affects the amount of DG to connect to the buses.•Probabilistic margins with respect to limit violations improve service quality. With the growing use of renewable energy sources, Distributed Generation (DG) systems are rapidly spreading. Embedding DG to the distribution network may be costly due to the grid reinforcements and control adjustments required in order to maintain the electrical network reliability. Deterministic load flow calculations are usually employed to assess the allowed DG penetration in a distribution network in order to ensure that current or voltage limits are not exceeded. However, these calculations may overlook the risk of limit violations due to uncertainties in the operating conditions of the networks. To overcome this limitation, related to both injection and demand profiles, the present paper addresses the problem of DG penetration with a Monte Carlo technique that accounts for the intrinsic variability of electric power consumption. The power absorbed by each load of a medium voltage network is characterized by a load variation curve; a probabilistic load flow is then used for computing the maximum DG power that can be connected to each bus without determining a violation of electric constraints. A distribution network is studied and a comparison is provided between the results of the deterministic load flow and probabilistic load flow analyses.