Researchers built an open-source GUI and database tool that makes EnergyPlus simulations easier to run, analyze, and store—cutting data size 20x and boosting usability for building energy research.
Buildings aren’t just bricks and mortar anymore—they’re major players in energy use. In the U.S. alone, they account for about 27.6% of total energy consumption. From heating and cooling to lighting and plugging in EVs, buildings are at the center of our daily energy demand.
But there’s more: with solar panels, batteries, and smart HVAC systems, modern buildings can become grid-edge resources. That means they don’t just consume energy, they can also help balance the grid ⚡—absorbing renewable power when it’s available, and adjusting demand during peak times.
To unlock this potential, we need detailed models of buildings. Enter EnergyPlus.
EnergyPlus is the go-to software for engineers and researchers who want to model how a building uses energy. It can simulate:
By feeding in a building’s geometry, materials, HVAC system, and local weather, EnergyPlus produces high-resolution time-series data—basically a detailed energy diary of how that building behaves across hours, days, or even years.
👉 But here’s the catch: EnergyPlus is powerful but not user-friendly.
So while EnergyPlus is amazing for creating building simulations, actually managing and analyzing the data is still a pain.
Other tools exist:
But here’s the issue:
What engineers really need is a simple, flexible, and powerful tool that sits right in the middle:
✅ Easy simulations
✅ Custom variables
✅ Data aggregation
✅ Visualization
✅ Efficient storage
That’s exactly what this new research delivers.
Researchers at Washington State University developed an open-source simulation and data management tool for EnergyPlus.
It has two main parts:
This tool makes working with EnergyPlus simulations as simple as clicking through menus instead of editing cryptic files.
It has three apps:
Buildings often have multiple thermal zones. Sometimes you don’t need that much detail—you just want a simplified model.
This app lets you:
👉 Perfect for creating reduced-order models that are still accurate but computationally cheaper.
No more staring at raw numbers. This app allows:
Interactive charts (thanks to Plotly) make it easy to zoom, pan, and export PNGs for reports.
The second half of this research tackles a big problem: storage and querying.
Raw EnergyPlus outputs (especially in pickle format) are huge and messy:
The solution? A relational SQL database schema.
This means faster research, smaller storage costs, and smoother workflows.
This tool addresses the three pain points of EnergyPlus research:
For building energy engineers and researchers, this means:
The authors see this tool as just the beginning. Potential directions include:
Ultimately, this tool could help transform buildings into active participants in the energy grid, supporting decarbonization and resilience goals.
EnergyPlus is already the gold standard for building energy simulation, but its complexity has limited accessibility.
This new open-source simulation + data management tool makes it easier, faster, and more efficient to:
For the world of building energy research, this is a game-changer. By simplifying workflows and enabling big-data analysis, it opens doors to smarter buildings and a cleaner energy future 🌱.
🔹 EnergyPlus - An open-source building energy simulation software used by engineers to predict how much energy a building will use for heating, cooling, lighting, and more. Think of it as a “virtual lab” for buildings. - More about this concept in the article "Smarter HVAC Systems with AI 🔥".
🔹 GUI (Graphical User Interface) - A visual, click-and-use interface with buttons, menus, and charts—so you don’t have to type complicated commands. In this research, the GUI makes EnergyPlus much easier to use.
🔹 IDF (Input Data File) - A text file that tells EnergyPlus everything about a building—its geometry, materials, HVAC systems, schedules, etc. It’s like the blueprint + instruction manual for the simulation.
🔹 EPW (EnergyPlus Weather File) - A file containing detailed local weather data (temperature, humidity, wind, solar radiation). EnergyPlus uses this to test how a building performs under real-world weather.
🔹 Thermal Zone - A part of a building (like a room or floor) that is treated as having a uniform temperature in the simulation. Splitting buildings into zones makes energy modeling more accurate.
🔹 HVAC (Heating, Ventilation, and Air Conditioning) - The system in buildings that heats, cools, and ventilates indoor spaces. In EnergyPlus, HVAC is one of the biggest factors affecting energy use. - More about this concept in the article "🌿 Vertical Greening Systems: The Green Revolution in Sustainable Buildings 🏢".
🔹 PNNL Prototypical Buildings - A library of standardized building models (residential, commercial, manufactured) created by the Pacific Northwest National Laboratory. These serve as ready-to-use templates for simulations.
🔹 PostgreSQL - An advanced open-source database system. In this research, it’s used to store and organize huge amounts of EnergyPlus data efficiently.
🔹 Relational Database Schema - A structured way of organizing data into tables with relationships (like “Buildings,” “Zones,” “Variables”). It helps reduce redundancy and makes data querying faster.
🔹 Data Aggregation - The process of combining data from multiple zones into simplified groups (like averaging room temperatures). This reduces complexity while keeping useful insights.
🔹 Plotly-Dash - A Python-based framework for building interactive dashboards and GUIs. Here, it powers the user-friendly interface for running simulations and making visualizations.
Source: Ninad Gaikwad, Kasey Dettlaff, Athul Jose P, Anamika Dubey. An Open-Source Simulation and Data Management Tool for EnergyPlus Building Models. https://doi.org/10.48550/arXiv.2508.09130
From: Washington State University.
