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Towards a Data Calibrated, Simulation-Based Campus Energy Analysis Environment for Situational Awareness and Future Energy System Planning

[+] Author Affiliations
Scott Duncan, Michael Balchanos, Woongje Sung, Juhyun Kim, Yongchang Li, Yanal Issac, Dimitri Mavris, Adam Coulon

Georgia Institute of Technology, Atlanta, GA

Paper No. ES2014-6695, pp. V002T11A010; 10 pages
doi:10.1115/ES2014-6695
From:
  • ASME 2014 8th International Conference on Energy Sustainability collocated with the ASME 2014 12th International Conference on Fuel Cell Science, Engineering and Technology
  • Volume 2: Economic, Environmental, and Policy Aspects of Alternate Energy; Fuels and Infrastructure, Biofuels and Energy Storage; High Performance Buildings; Solar Buildings, Including Solar Climate Control/Heating/Cooling; Sustainable Cities and Communities, Including Transportation; Thermofluid Analysis of Energy Systems, Including Exergy and Thermoeconomics
  • Boston, Massachusetts, USA, June 30–July 2, 2014
  • Conference Sponsors: Advanced Energy Systems Division
  • ISBN: 978-0-7918-4587-5
  • Copyright © 2014 by ASME

abstract

Researchers at Georgia Tech (GT) have recently begun the GT Smart Energy Campus initiative, which combines campus energy metering data with physics-based modeling and simulation to create an integrated analysis environment for campus energy. The environment consists of a digital representation of campus, which supports situational awareness, as well as a virtual test bed for analyzing emerging energy technologies and future scenarios. The first year of the initiative has focused on evaluating campus energy metering data using visual analytics and statistical analysis techniques. Data analysis is presented as having value for two main uses: (1) as attention-directing information to help system operators diagnose anomalies and (2) as a precursor to modeling and simulation (M&S) in future phases of the Smart Energy Campus initiative. The environment is explained using the initial study scoping of the campus thermal energy generation and distribution systems. Furthermore, a modeling and simulation approach leveraging the Modelica M&S language is described, and preliminary results in using it to represent the campus chilled water system are presented.

Copyright © 2014 by ASME
Topics: Simulation

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