Location
Grand Wailea, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2020 12:00 AM
End Date
10-1-2020 12:00 AM
Description
Interest in promoting innovation for large, high-voltage power grids has driven recent efforts to reproduce actual system properties in synthetic electric grids, which are fictitious datasets designed to be large, complex, realistic, and totally public. This paper presents new techniques based on system planning sensitivities, integrated into a synthesis methodology to mimic the constraints used in designing actual grids. This approach improves on previous work by explicitly quantifying each candidate transmission line’s contribution to contingency robustness, balancing that with geographic and topological metrics. Example synthetic grids build with this method are compared to actual transmission grids, showing that the emulated careful design also achieves observed complex network properties. The results shed light on how the underlying graph structure of power grids reflects the engineering requirements of their design. Moreover, the datasets synthesized here provide researchers in many fields with public power system test cases that are detailed and realistic.
Planning Sensitivities for Building Contingency Robustness and Graph Properties into Large Synthetic Grids
Grand Wailea, Hawaii
Interest in promoting innovation for large, high-voltage power grids has driven recent efforts to reproduce actual system properties in synthetic electric grids, which are fictitious datasets designed to be large, complex, realistic, and totally public. This paper presents new techniques based on system planning sensitivities, integrated into a synthesis methodology to mimic the constraints used in designing actual grids. This approach improves on previous work by explicitly quantifying each candidate transmission line’s contribution to contingency robustness, balancing that with geographic and topological metrics. Example synthetic grids build with this method are compared to actual transmission grids, showing that the emulated careful design also achieves observed complex network properties. The results shed light on how the underlying graph structure of power grids reflects the engineering requirements of their design. Moreover, the datasets synthesized here provide researchers in many fields with public power system test cases that are detailed and realistic.
https://aisel.aisnet.org/hicss-53/es/resillient_networks/3