Overview
The Hourly Time Series Viewer provides interactive visualization of annual energy profiles with advanced range selection capabilities. This tool is designed to handle large datasets (8,760+ hours) and allows you to zoom in on specific time periods to analyze heating and cooling loads in detail.
Template Download
📥 Download Excel Template
Excel File Requirements
Your Excel file must contain hourly data with the following columns:
- Period: Sequential hour numbers from 1 to 8760 (or more for multi-year data)
- Heating (kBtu): Hourly heating load values
- Cooling (kBtu): Hourly cooling load values
Note: The tool supports both single Y-axis and dual Y-axis configurations for comparing heating and cooling data.
Key Features
- Interactive Range Selection: Use the range slider to focus on specific time periods
- Quick Zoom Presets: One-click buttons for common time ranges (1 day, 1 week, 1 month, etc.)
- Simultaneous Load Analysis: Automatically identifies and quantifies periods of concurrent heating and cooling
- Dual Y-Axis Support: Optional separate axes for heating and cooling for better scale comparison
- Export Functionality: Download charts as PNG images
- Real-time Statistics: View total loads and simultaneous percentages
Understanding the Visualization
- Heating (Red): Positive values showing heating load demand
- Cooling (Blue): Negative values showing cooling load demand (displayed below zero line)
- Simultaneous Heating/Cooling (Purple): Highlighted areas where both loads occur together
- Zero Line: Bold horizontal line separating heating (above) from cooling (below)
Usage Instructions
- Step 1: Download the Excel template and populate it with your hourly data
- Step 2: Upload your completed Excel file using the upload button
- Step 3: Review the statistics panel showing annual totals and simultaneous load percentages
- Step 4: Use the zoom controls to focus on specific time periods:
- Click preset buttons (1 Day, 1 Week, 1 Month, etc.) for quick views
- Drag the range slider handles to select custom periods
- Click "All" to reset to the full year view
- Step 5: Export the chart as a PNG image using the export button
Tips for Best Results
- Start with the full year view to understand overall patterns before zooming in
- Use the 1-week or 1-month presets to analyze seasonal transitions
- Look for simultaneous load patterns that may indicate opportunities for heat recovery
- The dual Y-axis option is helpful when heating and cooling magnitudes differ significantly
- For very large datasets, zooming in improves chart readability and performance