Why Every Energy Modeler Should Use a Text Editor

(And Why You’re Missing Out If You’re Not)

If you're doing energy modeling—especially in eQUEST or EnergyPlus—and you're not using a text editor, you're working way too hard.

Let me explain.

eQUEST uses .inp and .pd2 files. EnergyPlus uses .idf or .epJSON. All of these are plain text files. That means every parameter, schedule, or zone definition is editable with a simple text editor—if you know where to look. And once you get the hang of it, editing text files can be way faster (and more powerful) than clicking through GUIs.

Why Use a Text Editor?

Here’s what a good text editor gives you:

• Global search: Instantly find all instances of a keyword like ZONE or EIR-FUNCTION.
• Batch edit: Replace hundreds of entries in seconds.
• Regex power: Use regular expressions to match patterns (I'll show you an example below).
• Compare tools: See the difference between two models side by side.
• Syntax highlighting and folding: Makes long files readable—fast.

Top Text Editors for Energy Modelers

If you're new to this, here are a few excellent choices:

• Atom – Open-source, clean interface, great packages
• Sublime Text – Fast, elegant, powerful search
• VS Code – Heavier, but excellent for more advanced workflows
• Notepad++ – My personal go-to

Why I Use Notepad++

It’s lightweight, fast, and portable. But the killer feature?

🔍 The “Compare” Plugin

Notepad++ has a plugin that lets you compare two files side by side and highlight differences line-by-line.
When you're trying to figure out why your eQUEST results changed, this is a game-changer.

I’ve used it to compare different .inp files and immediately spot where a zone definition or system assignment changed—something you might miss when clicking through the interface.

Bonus Tip: Regular Expressions in Search

Ever need to find all your ZONE definitions in an .inp file? Or extract all SCHEDULE names from an .idf?

In Notepad++, you can use regular expressions in the “Find” box. Here’s an example:

^  ZONE\s.*$

This matches any line that starts with two spaces followed by the word ZONE, then captures the whole line. It’s super helpful when you want to copy/paste or analyze just the zones without clicking through every screen.

You can do similar tricks to extract all SPACE-TYPE, SCHEDULE, or EIR-FUNCTION blocks.

⚡ Bonus Section: Automate Everything with Python

Once you're comfortable reading and editing raw text files, you're ready for the next level: automation.

Using Python or similar scripting languages, you can:

• Parse and extract objects like ZONE, SCHEDULE, or HVAC-SYSTEM
• Search and replace hundreds of values based on naming rules
• Batch-generate variations of a model for sensitivity studies
• Convert data from Excel/CSV to .idf or .inp format
• Automatically edit, insert, or reorganize sections

Example: Want to multiply every lighting power value in your IDF file by 0.9 for an efficiency case? One Python script and it’s done—in under a second.

For anyone working with 179D, LEED, or utility rebate compliance, the time savings add up fast—especially when making iterative updates across dozens of files.

Need a head start? Libraries like re (for regular expressions), pandas (for spreadsheet data), and even eppy (for IDF parsing) are your best friends.

Final Thoughts

GUIs are great for initial modeling and visual feedback—but if you’re not cracking open the text files, you’re leaving power on the table. Whether you’re trying to debug a model, copy/paste zones, validate schedule definitions, or automate thousands of lines with Python, a little text-savvy goes a long way.