A design methodology for energy infrastructures at the campus scale

Sang Hoon Lee, Godfried Augenbroe, Jin Kook Lee, Fei Zhao

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

To improve the design of large-scale energy infrastructures such as campuses, energy managers need to predict the outcomes of interventions in buildings, as well as have sufficient insights in the implications of changes to the supply and generation network. This article develops a methodology to express overall network energy performance (NEP) with the aim to manage the properties of and multiple relationships between energy consumers and producers in the network. It is based on a directed graph that contains consumers and producers at its nodes, while the connecting arcs represent modes of energy exchange, thus expressing the overall energy topology. The NEP model supports decisions at the generation side, the consumption side, and defines the macroenergy connections, that is, which consumer nodes connect to which suppliers. Our approach forms a bridge between two competing approaches at opposite ends of the spectrum, (1) network models that use high-fidelity dynamic building simulation models but typically break down under the computational weight of hundreds of buildings, and (2) the large scale geographical information system (GIS) approaches that are capable to handle large urban collections of buildings but whose building models are typically too shallow to inspect individual building performance. As an example, the article illustrates the use of the NEP model in the support of systematic improvement of a university campus energy performance.

Original languageEnglish
Pages (from-to)753-768
Number of pages16
JournalComputer-Aided Civil and Infrastructure Engineering
Volume28
Issue number10
DOIs
Publication statusPublished - 2013 Nov 1

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All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics

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