ClimateTriage - Impactful open source contributions

A free software toolbox for simulating and optimizing modern power systems that include features such as conventional generators with unit commitment, variable wind and solar generation, storage units, coupling to other energy sectors, and mixed alternating and direct current networks.

Wildfire Predictive Services to support decision making in prevention, preparedness, response and recovery.

Plant phenotyping using computer vision.

Enable your products and services to support the energy management protocol EEBUS, the communication interface that enables energy management relevant devices in buildings to connect and interact with each other and with grid and market operators.

Data analysis tools for working with historical PV solar time-series data sets.

A model for simplified evaluation of the approximate chemistry-climate impact of air traffic emissions.

A Python package designed to simplify and accelerate the process of analysing data from battery cyclers.

A lightweight Python-based tool that calculates the optimal time to run a compute job to minimise its carbon intensity enabling environmentally-conscious scheduling.

Developed collaboratively and mostly reusing existing open-source components, VEDA consolidates GIS delivery mechanisms, processing platforms, analysis services, and visualization tools and provides an ecosystem of open tools for addressing Earth science research and application needs through the public-facing VEDA Dashboard.

A Bayesian inference approach for using terrestrial ecosystem observations to optimize terrestrial carbon cycle model states and processes parameters.

An open source software stack for EV charging infrastructure from firmware to cloud: OCPP, ISO 15118, SunSpec, Modbus, energy management and load balancing and an entire flexible middle-ware framework based on MQTT. Part of the Linux Foundation Energy ecosystem.

Home Assistant integration for Anker Solix Power devices.

Provide an app that helps residential energy coaches or advocates, and some homeowners, estimate a home's heating requirements (heat load) and assess whether proposed heat pumps have sufficient heating capacity for the home.

Provides an efficient, scalable, and flexible way to store and access large, multi-dimensional arrays, the core data format used in climate models and observational datasets.

Provides a Python API and a CLI interface to extract data for various power infrastructure types, such as power lines, substations, and more.