Management of building energy consumption and energy supply network on campus scale

Abstract

Building portfolio management on campus and metropolitan scale involves decisions about energy retrofits, energy resource pooling, and investments in shared energy systems, such as district cooling, community PV and wind power, CHP systems, geothermal systems etc. There are currently no tools that help a portfolio/campus manager make these decisions by rapid comparison of variants. The research has developed an energy supply network management tool at the campus scale. The underlying network energy performance (NEP) model uses (1) an existing energy performance toolkit to quantify the energy performance of building energy consumers on hourly basis, and (2) added modules to calculate hourly average energy generation from a wide variety of energy supply systems. The NEP model supports macro decisions at the generation side (decisions about adding or retrofitting campus wide systems) and consumption side (planning of new building design and retrofit measures). It allows testing different supply topologies by inspecting which consumer nodes should connect to which local suppliers and to which global suppliers, i.e. the electricity and gas utility grids. A prototype software implementation allows a portfolio or campus manager to define the demand and supply nodes on campus scale and manipulate the connections between them through a graphical interface. The NEP model maintains the network topology which is represented by a directed graph with the supply and demand nodes as vertices and their connections as arcs. Every change in the graph automatically triggers an update of the energy generation and consumption pattern, the results of which are shown on campus wide energy performance dashboards. The dissertation shows how the NEP model supports decision making with respect to large-scale building energy system design with a case study of the Georgia Tech campus evaluating the following three assertions: 1. The normative calculations at the individual building scale are accurate enough to support the network energy performance analysis 2. The NEP model supports the study of the tradeoffs between local building retrofits and campus wide energy interventions in renewable systems, under different circumstances 3. The NEP approach is a viable basis for routine campus asset management policies.