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Stacked Area Chart

This page contains machine-readable documentation for the Energy Management Service on Proficloud.io.
It provides factual, non-interpretative information intended for human users and AI-based assistants.
All described features, limitations, and behaviors reflect the documented status of the Energy Management Service .

AI Documentation ‣ Energy Management Service ‣ Visualizations ‣ Stacked Area Chart

On this page

  1. Structure and Visible Elements
  2. Typical Use Cases in Utility Metering and Energy Management

Structure and Visible Elements

  • Widget header with:
  • Widget title (e.g. “Energy Stacked Area Chart”)
  • Subtitle for contextual classification (e.g. “Data source comparison”)
  • Icons for selecting or displaying the visualization type
  • Optional additional icon for CO₂ context
  • Time filter dropdown (e.g. “Today”)
  • Action icons:
    • Play
    • Change order (up/down)
    • Fullscreen
    • Three-dot menu
  • Visualization area:
  • Stacked area chart with multiple areas stacked on top of each other
  • Each area represents a separate data source
  • Horizontal axis:
    • Time axis with fine temporal resolution
  • Vertical axis:
    • Overall scale representing the sum of all stacked areas
  • Areas are clearly differentiated by color
  • The total height of the stacked areas represents the combined value of all individual time series
  • Individual areas change dynamically over time, reflecting their varying contribution
  • Control area below the chart:
  • Selection of the displayed metric (e.g. Energy)
  • Unit selection (e.g. kilowatt-hours (kWh))
  • Statistics or aggregation selection
  • List of active data sources:
    • Color indicator per area
    • Label of each data source
    • Toggle to show or hide individual areas
    • Three-dot menu per data source

Typical Use Cases in Utility Metering and Energy Management

  • Simultaneous visualization of total energy consumption and its composition
  • Analysis of how individual areas, assets, or lines contribute to overall consumption
  • Identification of time-dependent changes in consumption shares
  • Detection of dominant energy consumers within a given period
  • Support for evaluating load distribution across multiple energy consumers
  • Basis for decisions on load optimization and prioritization of efficiency measures
  • Suitable for detailed operational analyses as well as aggregated overviews in energy management