Starting Point:
The starting point model generated an energy model with a predicted mean EUI of 74.4 kBtu.ft2/yr.
Baseline Model
Implementing the following measures yielded a predicted mean EUI of 51.4 kBtu/ft2/yr:
- Operating schedule: 12/5
- Roof construction: R38
Implementation of Building Envelope Measures
In order to explore the potential impact of power and lighting measures versus building envelope measures, I will modify the following measures to attempt to drive down the predicted mean EUI:
- Plug Load Efficiency (the equipment and appliances that draw power)
- Lowered the plug load efficiency to 1.0 W/Sq.ft. (46.6 EUI mean)
- Lighting Efficiency (based on the efficiency of the lighting fixtures)
- Set the lighting efficiency to 1.9 W/sf (55.2 EUI mean)
- Daylighting & Occupancy Controls
- Implemented Daylighting & Occupancy Controls (54.5 EUI mean)
Even after implementing these energy conservation measures, I was unable to achieve a mean EUI of 54 or less. Therefore, I will implement more measures.
- Implement greater lighting Efficiency (based on the efficiency of the lighting fixtures)
- Increase energy efficiency to 1.1 W/SF (45.9 EUI mean)
With these energy efficiency measure implementations, I was able to achieve a mean EUI of 45.9 kBtu/ft2/yr.
The Addition of Photovoltaic Panels
- Use the Insight Factor tiles to explore the impact of Photovoltaic Panels, varying the:
- Surface Coverage
- I adjusted the surface coverage to 60% and my EUI mean decreased quite a bit.
- Panel Efficiency
- I adjusted my PV panels to reflect an efficiency of 20.4% (44.4 kBtu/ft2/yr)
- I modified the payback limit to a 20-year period and the EUI mean dropped significantly — 35.9 kBtu/ft2/yr.
c. Payback Limit (how many years you will allow for the panels to pay for themselves
It is evident that in order to achieve a low EUI mean, drastic implementations must be considered within a building model, such as: the thermal properties of the building envelope, plug load efficiency, and PV panel surface coverage to name a few.