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volttron - VOLTTRON Distributed Control System Platform

  •    Python

VOLTTRON™ is an open source platform for distributed sensing and control. The platform provides services for collecting and storing data from buildings and devices and provides an environment for developing applications which interact with that data. From version 6.0, VOLTTRON supports two message buses - ZMQ and RabbitMQ.

building-server - A server to stream PostGIS 3D objects to the web

  •    Python

This is a prototype for a simple web server that retrieves polyhedral surfaces from a POSTGIS database and sends them back in a glTF or GeoJSON file. It relies on a Bounding Volume Hierarchy (BVH) to transmit progressively the geometric data. A script for building the BVH is provided in this repository.

modelica-buildings - Modelica Buildings library

  •    Modelica

This is the development site for the Modelica Buildings library and its user guide. Stable releases including all previous releases are available from the main project site at http://simulationresearch.lbl.gov/modelica.

TEASER - TEASER - Tool for Energy Analysis and Simulation for Efficient Retrofit

  •    Python

TEASER (Tool for Energy Analysis and Simulation for Efficient Retrofit) allows fast generation of archetype buildings with low input requirements and the export of individual dynamic simulation models for Modelica libraries AixLib and Modelica IBPSA library. It is being developed at the RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate. This GitHub page will be used to further develop the package and make it available under the MIT License.

seed - Standard Energy Efficiency Data (SEED) Platform™ is a web-based application that helps organizations easily manage data on the energy performance of large groups of buildings

  •    Python

The SEED Platform is a web-based application that helps organizations easily manage data on the energy performance of large groups of buildings. Users can combine data from multiple sources, clean and validate it, and share the information with others. The software application provides an easy, flexible, and cost-effective method to improve the quality and availability of data to help demonstrate the economic and environmental benefits of energy efficiency, to implement programs, and to target investment activity. The SEED application is written in Python/Django, with AngularJS, Bootstrap, and other javascript libraries used for the front-end. The back-end database is required to be PostgreSQL.

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