OpenBuildNet framework for distributed co-simulation of smart energy systems

Truong X. Nghiem, Altuǧ Bitlislioǧlu, Tomasz Gorecki, Faran A. Qureshi, Colin N. Jones

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

The complexity and diversity of future energy systems will require co-simulation solutions that enable the integration of tools from multiple domains for research and development. We introduce an open-source framework, OpenBuildNet, for distributed co-simulation of large-scale smart energy systems. Using a loose-coupling approach to co-simulate parallel processes, it can leverage and seamlessly integrate specialized simulation and computation tools in a common platform. Users can therefore benefit from the capabilities of state-of-the-art and widely used tools in each domain. OpenBuildNet is scalable and highly flexible as it uses a decentralized architecture, message-based communication, and peer-to-peer data exchange between subsystem nodes. It also provides a set of easy-to-use software tools tailored for researchers and engineers. This paper presents the architecture and tool suite of OpenBuildNet, and demonstrates its usefulness in a case study of controlling multiple buildings for demand response.

Original languageEnglish (US)
Title of host publication2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509035496
DOIs
StatePublished - 2016
Externally publishedYes
Event14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016 - Phuket, Thailand
Duration: Nov 13 2016Nov 15 2016

Publication series

Name2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016

Conference

Conference14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016
Country/TerritoryThailand
CityPhuket
Period11/13/1611/15/16

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Optimization
  • Instrumentation
  • Computer Vision and Pattern Recognition

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