Probabilistic Optimization of MV Distribution Network in Presence of Distributed Generation

Distributed Generation is predicted to play an increasing role in the electric power system of the near future. With so much new distributed generation being installed, the level of uncertainties that characterise the planning environment increases, particularly focused on the energy production of the DG units. These uncertainties are often so relevant that traditional deterministic paradigms can easily lead to uneconomical or unreliable solutions. To overcome this problem, a probabilistic load flow has been developed, taking into account the probability density function of the loads and of the annual power production associated to each generating unit. The possible existing correlations between DG units, between generators and loads and between loads have also been considered. This procedure has been implemented inside an heuristic optimisation algorithm to find the best MV distribution network architecture that minimises the overall cost (i.e. the costs of building, maintenance, losses and disruptions). Application examples are presented to illustrate the algorithm effectiveness, and comparative results between deterministic and probabilistic approaches are also discussed.