ABSTRACT
The large-scale use of distributed electricity generation is possibly associated with increasing grid congestion; hence, Distributed Generation (DG) curtailment is envisioned to solve those congestions in affected power systems. By resorting to curtailment as part of an Active Network Management (ANM) scheme under real-time supervision/control of the DG units, more distributed generation can be accommodated in a distribution grid, while keeping the power system secure. In this paper, a method, based on an importance sampling scheme systematically targeting electrically challenging scenarios, is given to assess the curtailment risk associated to DG unit connections to the grid. It simultaneously resorts to correlated sampling in order to estimate the risk evolution due to “perturbed” situations, i.e. due to a newly connected DG unit. This significantly reduces the computation time of the risk indicators. The effectiveness of the proposed method is demonstrated on a test power grid.
