Team: Yinchen Yi, Yutong Li
A census-tract–scale modeling pipeline to (i) simulate earthquake-induced substation damage, (ii) propagate disruption to tract-level service via a tract–substation mapping matrix, and (iii) compare post-earthquake repair prioritization strategies under three objectives:
- Network robustness (connectivity / fragmentation proxies)
- Population service restoration
- Equity-aware restoration across census tracts (e.g., SVI-weighted objectives)
The pipeline supports both an unconstrained baseline and a logistics-aware restoration setting (multi-crew, multi-depot, travel-time constraints). We further perform PCA + K-means to group census tracts into resilience typologies using simulated outage/recovery metrics and socioeconomic indicators.
Scope note: robustness metrics here are connectivity-based (e.g., largest connected component) and do not enforce power-flow feasibility unless operational constraints are added.
- Topological network construction from transmission line and substation data using endpoint snapping, line splitting at substations, and graph extraction of substation-to-substation direct links
- Tract-substation weighting matrix (W) construction based on Inverse Distance Weighting
- Centrality and percolation analysis of topological network
- Scenario-based stress testing using ShakeMap PGA fields (1933 Long Beach, 1971 San Fernando, 1994 Northridge, 2%-in-50yr)
- Probabilistic substation damage-state modeling using lognormal fragility with Monte Carlo sampling
- Tract-level service estimation through tract–substation weighting matrix (W)
- Restoration simulation under:
- Baseline (no constraints)
- Logistics-aware rule-based and GA optimisation-based scheduling (multi-crew, multi-depot, travel-time constraints)
- Strategy comparison (Theoretical Limit / Random Baseline / Betweenness (Bridges) First / Impact (Population) First / Degree (Hubs) First / Hospital First / Impact λ2 (Grid) First / Closeness First / Balanced GA / HospFirst GA / Efficiency GA) using service restoration metrics and connectivity-based robustness metrics
- Tract resilience typology via PCA + K-means using simulated + socioeconomic features
Topology_and_Weight.py— Construct substation-level transmission topology (snapping/splitting + direct links) and export tract–substation influence weights (W / mapping CSVs)IDW.py— Interpolate scenario PGA grids to substations (IDW/KDTree), producing per-scenario PGA_* columns for downstream simulationsbuild_travel_matrices_osm.py— Precompute base→substation and substation→substation travel-time matrices from OSM road network for crew schedulingC257H_Project_Main.py— End-to-end pipeline (hazard→damage MC→network impact→restoration scheduling/GA→KPIs→typology clustering), outputs organized by Stage foldersProject_Visualizer.py— Post-processing visualizer: maps and comparative figures from Stage outputs (e.g., supply maps + histograms, logistics heatmaps, KPI bars, Gantt charts, cluster profile plots)
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Topology + W-matrix
python Topology_and_Weight.py
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Intensity measure interpolation
python IDW.py
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Travel matrix
python build_travel_matrices_osm.py
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Main pipeline (simulation + restoration + KPIs + typology)
python C257H_Project_Main.py
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Visualization
python Project_Visualizer.py
This repository expects external datasets, all of which included in the "data" folder.
- OpenStreetMap contributors (Open Database License): https://www.openstreetmap.org/
- California Energy Commission GIS Data (transmission lines): https://gis.data.ca.gov/datasets/CAEnergy::california-electric-transmission-lines-1/about
- California Energy Commission GIS Data (electric substations): https://hub.arcgis.com/datasets/c2d4e65fe7b84c67a94e98ff9555c3ac_0
- California Geological Survey Map Sheet 48 (2% in 50 years probabilistic ground motion; source for the "2pc50" scenario): https://www.conservation.ca.gov/cgs/publications/ms48
- USGS ShakeMap (Peak Ground Acceleration, source for the other scenarios): https://earthquake.usgs.gov/data/shakemap/
- FEMA National Risk Index (NRI): https://www.fema.gov/flood-maps/products-tools/national-risk-index
- US Census TIGER/Line (tract boundaries): https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html
- US Census ACS 5-year estimates: https://api.census.gov/data.html
- CDC/ATSDR Social Vulnerability Index (SVI): https://www.atsdr.cdc.gov/place-health/php/svi/index.html
- HIFLD Electric Substations (ID crosswalk / supplemental attributes): https://catalog.data.gov/dataset/electric-substations
- City of Los Angeles GeoHub (city boundary layer): https://geohub.lacity.org/maps/city-boundary
Depending on enabled stages, the pipeline can export:
- Substation-level hazard/intensity sampling outputs (e.g., PGA assigned per substation per scenario)
- Substation-level damage-state probabilities (MC) and recovery trajectories
- Tract-level service and recovery trajectories (via tract–substation mapping W)
- Network robustness / topology metrics
- Logistics: travel-time matrices (base→task, task→task) and derived heatmaps
- Strategy-level KPI tables (system / population-weighted / equity-weighted), plus efficiency summaries (e.g., T50/T80/AUC)
- Comparative restoration curves across strategies
- Scheduling: rule-based schedules and Gantt plots, GA schedules and Gantt plots
- PCA & clustering outputs: PCA stats/loadings/scree plots, k-means diagnostics, final cluster labels, and tract typology summaries
- Maps and figures generated from Stage outputs (recovery curves, KPI comparisons, clusters)
- Connectivity-based robustness metrics are graph proxies and do not guarantee operational feasibility (e.g., AC/DC power flow, voltage constraints) unless such modules are added.
- Service estimation depends on the tract–substation mapping matrix (W); results are sensitive to how W is constructed (distance decay, assignment rules, normalization, etc.).
- Cheng, B., Nozick, L., Dobson, I., Davidson, R., Obiang, D., Dias, J., & Granados, M. (2024). Quantifying the earthquake risk to the electric power transmission system in Los Angeles at the census tract level. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3408797
- Çağnan, Z., Davidson, R. A., & Guikema, S. D. (2006). Post-earthquake restoration planning for Los Angeles electric power. Earthquake Spectra, 22(3), 589–608. https://doi.org/10.1193/1.2222400
- Xu, N., Guikema, S. D., Davidson, R. A., Nozick, L. K., Çağnan, Z., & Vaziri, K. (2007). Optimizing scheduling of post-earthquake electric power restoration tasks. Earthquake Engineering & Structural Dynamics, 36(3), 265–284. https://doi.org/10.1002/eqe.623
- Cavdaroglu, B., Hammel, E., Mitchell, J. E., Sharkey, T. C., & Wallace, W. A. (2013). Integrating restoration and scheduling decisions for disrupted interdependent infrastructure systems. Annals of Operations Research, 203(1), 279–294. https://doi.org/10.1007/s10479-011-0959-3