Modular Probabilistic Approach for Modelling Distribution Grids and its Application

Due to the high increase in installed distributed renewable energy sources (DRES) new challenges in the planning and operation of distribution grids (DG) exist. This paper proposes an approach to generate models of present and future synthetic DG based on statistical data of existing networks and operational planning. Compared to the utilization of grid samples a probabilistic network generator offers significant advantages, which are demonstrated in this paper. A modular design and a simple expandability is one of the most important requirements for its application in different issues. In this context four exemplary use cases are described - reactive power analysis, the identification of planning principles, analysing benefits of innovative network equipment and short circuit protection analysis.