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Energy demand forecasting

This workflow automatically generates hourly and daily energy demand forecasts by analyzing historical consumption data, weather patterns, and real-time grid conditions to optimize generation scheduling and grid operations.

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Workflow Trigger

Scheduled execution every 4 hours or manual trigger for updated forecast requirements

Visual Flow

Each node represents an automated step. Connections show how data and decisions move through the workflow.

Step-by-Step Breakdown

Detailed explanation of each automated stage in the workflow.

  1. 1
    Trigger

    Initiate Demand Forecast Cycle

    Workflow starts automatically every 4 hours or when manually triggered by grid operators requiring updated demand projections.

    n8n Scheduler
  2. 2
    Action

    Collect Historical Energy Data

    Retrieves past 12 months of energy consumption patterns, load profiles, and seasonal trends from the PI historian database.

    OSIsoft PI historian
  3. 3
    Action

    Gather Weather and External Data

    Pulls current weather conditions, 7-day forecasts, and economic indicators that influence energy demand patterns.

    Weather APIExternal Data Sources
  4. 4
    Decision

    Evaluate Forecast Complexity Requirements

    Determines whether to use simple trend analysis for normal conditions or advanced modeling for extreme weather events or special circumstances.

    AI Analytics Engine
  5. 5
    Action

    Generate Demand Predictions

    Runs machine learning algorithms to create hourly demand forecasts for next 48 hours and daily forecasts for next 7 days.

    PowerWorld simulationAI Analytics Engine
  6. 6
    Action

    Validate Against Grid Constraints

    Cross-references forecasted demand with transmission capacity and generation limits using SCADA system data.

    SCADA systemsPowerWorld simulation
  7. 7
    Output

    Distribute Forecast Reports

    Sends formatted demand forecasts to grid operators, generation schedulers, and trading teams through automated dashboards and alerts.

    Oracle UtilitiesDashboard Systems

Outputs

  • 48-hour hourly demand forecast
  • 7-day daily demand projection
  • Peak demand alerts and warnings
  • Forecast accuracy metrics report

Key Metrics

  • Forecast accuracy percentage
  • Mean Absolute Percentage Error (MAPE)
  • Peak demand prediction variance

Tools & Integrations

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