Distributed Generation Siting and Sizing under Uncertainty

The necessity for flexible electric systems, changing regulatory and economic scenarios, energy savings and environmental impact are providing impetus to the development of distributed generation, which is predicted to play an increasing role in the future electric power system; with so much new Distributed Generation (DG) being installed, it is critical that the power system impacts be assessed accurately so that DG can be applied in a manner that avoids causing degradation of power quality, reliability and control of the utility system. Considering that uncertainties on DG power production are very relevant and different scenarios have to be taken into consideration, traditional deterministic planning techniques should not be used to take the right decisions. In this paper a three step procedure, based on Genetic Algorithms and Decision Theory, is applied to establish the best distributed generation siting and sizing on an MV distribution network, considering technical constraints, like feeder capacity limits, feeder voltage profile and three-phase short circuit currents in the network nodes. In the last part of the paper the procedure is applied to an actual distribution network