Energy Demand

Access pre-calculated energy demand estimates for residential buildings across Germany using syte's physics-based calculation engine.

Prerequisites

This guide assumes you're familiar with API authentication and geocoding addresses.

How syte Calculates Energy Demand

syte uses its proprietary syte Renovate calculation engine to determine energy demand for all residential buildings in Germany. This physics-based approach employs a surface-based methodology to calculate heat losses and solar gains.

Calculation Methodology:

• Surface-based heat loss calculation (Q_T = U × A × F)
• Solar gain analysis for windows (Q_s = g × A × G)
• Age-typical building component properties from TABULA database
• Building orientation and location-specific climate data
• Comprehensive surface analysis (roof, walls, basement, windows)

Learn more: Energy Calculation Overview | Detailed Calculation Methodology

Note: Energy demand values are estimates based on building characteristics and should be validated with actual consumption data or professional energy audits for renovation planning.

Accessing Energy Demand Data

Pre-calculated energy data in building responses

Energy demand attributes are automatically included when fetching building or property data through the cadastral APIs. These values use syte's standard assumptions for heating systems and renovation states.

For single buildings: Use any of the three building endpoints ( see Building Data guide)
For aggregated property data: Use either property endpoint ( see Property Data guide)

Advanced: Custom Energy Calculations with syte Renovate

For full control over energy demand calculations, you can use syte Renovate APIs to compute energy demand with custom parameters. This allows you to override syte's assumptions for heating systems, current renovation states, and all other input parameters to model specific scenarios or validate against known building configurations. Learn how in our renovation plan creation guide.

Example Workflow

Step 1: Geocode the Address

First, convert your address to coordinates. See the geocoding guide for details.

Step 2: Fetch Building Data with Energy Information

Use the building-near-by API to get building data including energy demand:

Fetch Building with Energy Data

Step 3: Understanding the Energy Demand Response

The energy demand attributes are included in the properties field of the building response:

{
  "type": "Feature",
  "geometry": { ... },
  "properties": {
    "identifier": "DENW49AL00009XBy",
    "address": "Fernholzstraße 31 a",
    
    // Energy demand attributes
    "energy_demand": 142.5,             // Specific demand in kWh/m²·a
    "energy_demand_label": "E",         // Energy efficiency class (A+ to G)
    "energy_demand_total": 21000.0,     // Total annual demand in kWh/a
    "heating_system_estimate": "gas",   // Estimated heating system type
    "heating_systems_estimate": [       // Detailed heating system breakdown
      {
        "type": "gas",
        "probability": 0.85
      },
      {
        "type": "oil",
        "probability": 0.10
      }
    ],
    
    // Other building attributes...
    "floorspace": 147.20683,
    "construction_year_estimate": 1983
  }
}

Energy Demand Field Descriptions

Field	Description	Example
energy_demand	Specific energy demand per square meter per year	142.5 kWh/m²·a
energy_demand_label	Energy efficiency class from A+ (best) to G (worst)	"E"
energy_demand_total	Total annual energy demand for the building	21000.0 kWh/a
heating_system_estimate	Most likely heating system type	"gas", "oil", "district_heating"
heating_systems_estimate	Probability distribution of heating system types	Array with type and probability

Energy demand is calculated for all residential buildings in Germany. Fields will be null for non-residential buildings (e.g., commercial, industrial) as the calculation methodology specifically targets residential usage.

Common Use Cases

Portfolio Energy Analysis
Assess energy efficiency across multiple properties for investment decisions
Renovation Planning
Identify buildings with poor energy ratings for targeted renovation programs
Energy Cost Estimation
Calculate approximate heating costs based on current energy prices
Carbon Footprint Assessment
Estimate CO₂ emissions based on energy demand and heating system type

Additional Resources

Renovation Plan Creation Guide
Use energy demand data to create renovation plans and optimize building efficiency
Photovoltaic Potential
Combine energy demand with solar potential for net-zero planning
Fetching Building Data
Learn how to access complete building information including energy data