Life Cycle Optimization of a Zero Carbon Building for CO2e, Energy, and Cost Using Stochastic Controls for an Energy System Integrating a Heat Pump, Solar Air Wall, PV, and a Smart Grid-integrated Thermal Storage (SGTS) Hydronic Battery
AuthorStoyke, Godo Albert
Committee MemberHachem-Vermette, Caroline
Layzell, David B.
Tang, Lee G.
Blarke, Morten Boje
Engineering--Electronics and Electrical
SubjectGreen building rating systems
Carbon return on investment
least-cost climate abatement
residual carbon debt
global warming potential
model predictive control
energy efficiency retrofit
GHG emission reduction
Life cycle assessment
life cycle costing
net zero energy building
zero carbon building
Smart grid-integrated thermal storage (SGTS)
Coefficient of performance
solar thermal air wall
solar thermal collector
MetadataShow full item record
AbstractThe life cycle optimization (LCO) of zero carbon buildings (ZC) was examined, using a laneway house built with photovoltaic and solar air wall (SAW) renewable energy collection, air-to-water heat pump, smart grid-integrated thermal storage (SGTS) hydronic battery with an internet-connected stochastic (predictive) control system in subarctic Edmonton, Alberta, Canada. LCO is for global warming potential (GWP), energy, cost, and renewable friendliness. A life cycle assessment (LCA) based methodology (carbon return on investment – CROI) is proposed for design and retrofit decisions on the basis of GWP and cost. Sustainable building rating systems are modelled for their effectiveness in reducing GWP and energy use and are found to reduce life cycle GWP by 18.3% (LEED 2009 certified), 60.7% (PassivHaus 9.30), 96.9% (net zero) and 97.2% (zero carbon) compared to a home built to Alberta Building Code 2014 (base model – BM) over an 80 year life cycle. LCA of the ZC laneway house found a 94.4% reduction in GWP compared to the BM. In the BM, manufacturing, construction, maintenance and end of life phases contributed only 3.6% of life cycle GWP. A modelled HP with stochastic control, SAW and SGTS reduced annual energy consumption by 49.2% compared to a HP only, and by 61.8% compared to resistive heating. Using hourly grid pricing as a proxy of renewable friendliness, modelled optimization under a simulated dynamic pricing system by using hourly historic Alberta electrical pool pricing averaged over each month as a stochastic control mechanism for the HP showed a statistically significant 60.7% to 71.5% energy cost reduction, compared to a thermostatically controlled HP. Preliminary ZC real-life sensor readings are examined.
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