ETH Zürich (CEA) City Energy Analyst

GUIDEBOOK · CEA v4.0

Import & Export

Import & Export

This category contains features for exchanging data between CEA and external applications, as well as generating summary reports.

Export to Rhino/Grasshopper

Overview

Exports CEA files into Rhino/Grasshopper-ready format, allowing you to visualise and further process CEA geometry and results in Rhinoceros 3D and Grasshopper.

When to Use

  • Visualising building geometry in 3D
  • Further geometric analysis in Rhino/Grasshopper
  • Integrating CEA workflows with architectural design tools
  • Using cea4gh (CEA for Grasshopper) plugin

Required Inputs

  • Zone geometry: Building footprints with geometry data

Key Parameters

  • Include zone: Export zone building geometries
  • Include site: Export site boundary polygon
  • Include surroundings: Export surrounding building geometries
  • Include streets: Export street network
  • Include trees: Export tree geometries
  • Include district heating network: Export DH network edges and nodes
  • Include district cooling network: Export DC network edges and nodes

How to Use

  1. Open the CEA-4 App and navigate to Import & Export
  2. Select Export to Rhino/Grasshopper
  3. Configure which elements to export:
    • Select zone buildings (typically always enabled)
    • Optionally include site, surroundings, streets, trees
    • Optionally include thermal networks if they exist
  4. Click Run
  5. Find exported files at: 
    {CEA Project}/{Current Scenario}/export/rhino/from_cea/

Output Files

The feature exports CSV files containing geometric coordinates:

  • zone.csv - Main zone building geometries
  • site.csv - Site boundary (if exists)
  • surroundings.csv - Surrounding buildings (if exists)
  • streets.csv - Street network (if exists)
  • trees.csv - Tree geometries (if exists)
  • DH_edges.csv / DH_nodes.csv - District heating network (if exists)
  • DC_edges.csv / DC_nodes.csv - District cooling network (if exists)

All coordinates are standardised to a projected coordinate system for use in Rhino/Grasshopper.

Next Steps

After exporting:

  1. Download cea4gh (CEA for Grasshopper) from https://www.cityenergyanalyst.com/cea4gh
  2. Use the cea4gh Grasshopper components to import the exported CSV files into Rhino
  3. Visualise and analyse your urban energy model in 3D

Tips

  • Export all available geometry layers for complete visualisation
  • The coordinate system is automatically reprojected for optimal use in Rhino
  • Use this feature to create presentation materials and 3D visualisations

Troubleshooting

Issue: Export folder is empty

  • Solution: Ensure you have valid zone geometry in your scenario

Issue: Missing network files

  • Solution: Run Thermal Network Part 1 (layout) before exporting networks

Import from Rhino/Grasshopper

Overview

Imports Rhino/Grasshopper-generated files back into CEA, allowing you to use external design tools to create or modify building geometry before CEA analysis.

When to Use

  • Creating new building geometries in Rhino/Grasshopper
  • Modifying existing geometries with architectural design tools
  • Preparing complex urban morphologies
  • Integrating architectural design workflows with CEA analysis

Prerequisites

  • cea4gh installed and configured
  • Scenario created using cea4gh in Grasshopper
  • Current CEA scenario matches the cea4gh-generated scenario

How to Use

  1. In Rhino/Grasshopper:

  2. In CEA-4 App:

    • Ensure the current scenario is the one generated by cea4gh
    • Navigate to Import & Export
    • Select Import from Rhino/Grasshopper
    • Click Run

What Gets Imported

The feature imports:

  • Building footprint geometries
  • Building heights
  • Building properties (if assigned in Grasshopper)
  • Site boundaries
  • Surroundings (context buildings)

Next Steps

After importing:

  1. Verify imported geometry using the 3D viewer in CEA-4 App
  2. Use Archetypes Mapper to assign building properties if not already set
  3. Continue with standard CEA workflow (Solar Radiation → Demand → Analysis)

Tips

  • Always use cea4gh to ensure CEA-compatible geometry
  • Verify that building footprints are valid polygons (no self-intersections)
  • Ensure buildings have positive heights
  • Name buildings systematically (e.g., B001, B002, etc.)

Troubleshooting

Issue: Import fails with geometry errors

  • Solution: Verify geometry validity in Grasshopper using cea4gh validation components

Issue: “Scenario mismatch” error

  • Solution: Ensure the active CEA scenario matches the one created by cea4gh

Issue: Missing building properties

  • Solution: Assign properties in Grasshopper, or use Archetypes Mapper after import

Export Results to CSV (Summary & Analytics)

Overview

Generates CSV files containing aggregated CEA results for custom analysis, reporting, and data exchange. This feature provides flexible data export by building, time period, and metric.

When to Use

  • Creating custom reports and dashboards
  • Performing statistical analysis in Excel, Python, or R
  • Comparing scenarios side-by-side
  • Generating data for publications and presentations
  • Integrating CEA results with other software tools

Required Inputs

  • Zone geometry: Building footprints
  • Analysis results: At least one completed CEA analysis (e.g., demand, solar, emissions)

Key Parameters

  • Building filter: Select specific buildings or all buildings
  • Time aggregation: Hourly, daily, monthly, or yearly summaries
  • Metrics: Choose which results to export (demand, emissions, costs, solar, etc.)

How to Use

  1. Complete at least one CEA analysis (e.g., Energy Demand, Emissions, PV assessment)
  2. Navigate to Import & Export
  3. Select Export Results to CSV (Summary & Analytics)
  4. Configure export options:
    • Select buildings to include (or use “All buildings”)
    • Choose time aggregation level (hourly/daily/monthly/yearly)
    • Select metrics to export
  5. Click Run
  6. Find exported CSV files in: 
    {CEA Project}/{Current Scenario}/outputs/data/exports/

Output Structure

The feature generates structured CSV files with:

  • Building-level aggregations
  • Time-series data (if selected)
  • Summary statistics
  • Customised metric columns based on selection

Example output columns:

  • Name - Building identifier
  • GFA_m2 - Gross floor area
  • Qhs_MWhyr - Annual space heating demand
  • Qcs_MWhyr - Annual space cooling demand
  • E_MWhyr - Annual electricity demand
  • Additional columns based on available results

Use Cases

Scenario Comparison

  1. Export results for Scenario A
  2. Export results for Scenario B
  3. Compare CSV files in Excel or Python

Custom Reporting

  1. Export all metrics for selected buildings
  2. Import into Excel/PowerBI
  3. Create custom charts and pivot tables

Statistical Analysis

  1. Export hourly time-series data
  2. Analyse in Python/R
  3. Perform statistical tests and regressions

Tips

  • Export yearly summaries for high-level comparisons
  • Export hourly data for detailed temporal analysis
  • Use building filters to focus on specific building types
  • Combine with Excel pivot tables for flexible reporting

Troubleshooting

Issue: Empty export files

  • Solution: Ensure you have completed at least one CEA analysis before exporting

Issue: Missing metrics in export

  • Solution: Some metrics only appear after specific analyses (e.g., PV data requires PV analysis)

Issue: Too large file for hourly data

  • Solution: Use daily or monthly aggregation, or filter to fewer buildings

Common Workflows

Workflow 1: CEA to Rhino Visualisation

  1. Complete CEA analysis (demand, solar, emissions)
  2. Export to Rhino/Grasshopper with all layers
  3. Open exported files in Rhino using cea4gh
  4. Create 3D visualisations and renderings

Workflow 2: Rhino to CEA Analysis

  1. Design building geometry in Rhino/Grasshopper
  2. Use cea4gh to export CEA-compatible scenario
  3. Import from Rhino/Grasshopper in CEA-4 App
  4. Run standard CEA analysis workflow

Workflow 3: Results Export for Custom Analysis

  1. Complete CEA analyses
  2. Export Results to CSV with desired metrics
  3. Perform custom analysis in Excel, Python, or R
  4. Create custom reports and visualisations

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