Planning-oriented optimization strategy for visualizing power distribution networks: from global to local

Abstract

ABSTRACT The spatial distribution of power facilities is uneven, thereby making the topology of geographical wiring diagrams (GWDs) based on the actual coordinates unclear. A single-line diagram has the advantage of a clear topology but it lacks spatial locations. A GWD has the advantage of accurate spatial locations but it lacks a clear topology. Visualizing distribution networks for planning requires both features. We proposed a new planning-oriented method for optimizing the visualization of distribution networks. From the global perspective, we proposed an improved force-directed (FD) algorithm by introducing a space restriction strategy and node–edge repulsion strategy to promote the expansion of the distance between distribution facilities within a limited buffer. We then constructed the constrained Delaunay triangulation to identify the compact districts (CDs) and used a genetic algorithm to optimize the parameters for the improved FD algorithm. A novel visualization evaluation indicator was also proposed for quantitatively assessing the visualizations. From a local perspective, the fisheye algorithm was used to optimize the CDs to further improve the visualization of the distribution network. We verified the proposed methods with real-world data. We used limited spatial displacement in exchange for maximum topology clarity to balance the accurate spatial location and topology clarity.