Regionalizing input data for generation and transmission expansion planning models

Abstract

To support decision making in the context of restructuring the power system, models are needed which allow for a regional, long-term operation and expansion planning for electricity generation and transmission. Input data for these models are needed in a high spatial and temporal granularity. In this paper, we therefore describe an approach aimed at providing regionalized input data for generation and transmission expansion planning models. We particularly focus on a dynamic assignment of renewable energy sources and electrical load to potential buses of the transmission grid. Following a bottom up approach, we model the existing and potential distributed generation and load at the lowest possible spatial resolution based on various databases and models. Besides large power plants, which are directly connected to the transmission grid, a decentralized grid connection is modeled on the distribution grid level based on Voronoi polygons around the corresponding substations. By simplifying the load flow over the distribution grid to a shortest path problem, we model the feed-in into the transmission grid as a variable, depending on the nearest available transmission grid connection. As a result, the connection to the buses at transmission grid level is kept variable in case of grid expansion measures at substation level.