The Open Source Renewable Energy Data Warehouse : Part 1

In a previous post, I mentioned that Candy and I have been working on a project which was creating an open source Battery Energy Storage System (BESS) data warehouse. This project is now well advanced, has been extended to cover all renewable energy classes and in the next few weeks we'll be posting a little bit about how the software works as well as how it can be installed.

The Pitch

Renewable Asset Data Analytics (RADA) — free, open-source asset monitoring for communities and organisations

Renewable energy assets are inherently distributed — solar panels on rooftops, wind turbines across a hillside, batteries in separate substations. Whether you're a local authority, a housing cooperative, an NGO, or an isolated community running off-grid, managing dispersed assets over a wide area is hard.

RADA is a free, open-source platform that centralises real-time data from all your energy assets into a single normalised database — with full historical storage. From that foundation you get:

• Operations dashboards — live status and alerts at a glance
• Asset-level detail — remote diagnostics, trend analysis, cross-asset comparison
• Forecasting datasets — spot degradation and capacity changes before they bite
• Anomaly detection — flag suspicious activity on the network

Most existing tools are expensive, clunky, and built for large utilities. This one is lightweight, straightforward to deploy, and designed for technicians who need clarity. Importantly, it costs nothing.

Once the core platform is stable, the project opens to contributors — developers who want to add integrations, analytics, and new asset types.

Technical Architecture

The system is designed to run on a minimal Ubuntu Server installation running Docker with different containers.

The back-end is a Python application using FastAPI, running inside a Docker container, backed by a SQLite database during development and PostgreSQL in production. The database accumulates historical asset telemetry to support analytics across the full asset fleet.

The front-end is a React/Next.js application in a separate container which can be run on mobile devices as well as a desktop. Candy will be writing more about the development challenges in her blog.

Integration Connectivity

The biggest challenge of this project is to allow integration with different assets. All assets have their own telemetry communications protocols and the development needs to have a library of common protocols and map them to the integration layer of the warehouse, but also allow a technician to configure a specific one themselves.

Communication itself would either use internet connectivity to assets, but will also have the option to solicit and receive information via Long Range (LoRa) radio signals — a low-power radio protocol designed for long-range communication with remote devices — for assets which are located more remotely.

The database design, seed data creation and API build will be the subject of the second part of this blog post.

Part 2 can be found here.