Building Agent Dashboard Development and Use - Presented at haystack connect 2015
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Transcript of Building Agent Dashboard Development and Use - Presented at haystack connect 2015
Building Agent:A Better Energy Dashboard
Stephen M. FrankShanti Pless
National Renewable Energy Laboratory
Track 2 – Session 2: Visualization & Tools
Tuesday, May 19, 2015
NREL Research Support Facility
Location: Golden, COPrimary Use: OfficeSize: 360,000 ft2
Occupants: Approximately 1,325LEED Rating: PlatinumConstruction Cost: $254/ft2 (excl. PV)Energy Budget: 35 kBtu/ft2/yrNet Zero Energy
Background
2Image: Dennis Schroeder, NREL
3
Occupant Impact
Images: Dennis Schroeder, NREL
Occupants influence about 30%of total energy consumption
4
RSF Performance Targets
Pie Chart: Chad Lobato, NREL; Graphic: Marjorie Schott, NREL, and Stockphoto
5
Occupant Engagement
Image: Nicholas Long, NREL
How do we engage occupantsin order to meet (or exceed)aggressive efficiency goals?
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Building Agent
Graphics: Nicholas Long, NREL
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Effective Visualization?
What doesthis tell us?
Building Agent Dashboard
8Graphic Design: Marjorie Schott, NREL
What about this?
Creating Expectations
10
Upper Expectation
Measured Performance
Lower Expectation
Expectations combine statistical and physical energy models
Modeling Consumption
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Vertical Irradiance (W/m2)
LPD
(W/m
2)
Statistical ModelsLighting
Physical ModelsPV Generation
Combined ModelsPlug Loads
Henze, G.P.; Pless, S.; Petersen, A.; Long, N.; Scambos, T. (2015). “Control limits for building energy end use based on frequency analysis and quantile regression." Energy Efficiency, published online. DOI: 10.1007/s12053-015-9342-6
Fault Detection Example: Daylighting
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Lighting higher than expected
Lighting out of range despite full daylighting potential
Root Cause: Daylighting controls overridden during repair of ballast and fixtures; controls weren’t reset
6-Nov-20136-Nov-2013
Fault Detection Example: Lighting Controls
13
Lighting load is too highin evening hours (6–10 PM)
Response: Reduce auto-off delays; staff outreach; lessons learned for future lighting system design
Multiple Causes: Cleaning staff, individuals working late
1-Jan-2014 5-Apr-2014
Fault Detection Example: Air Handler
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Solution: Installation of new evaporative cooling unit to meet local demand, enabling the AHU to turn off at night
Problem: Large AHU on all night: manually overridden to provide air and cooling to a few night shift security employees
16-Aug-2013
7-Oct-2013
Fault Detection Example: PV Inverter Offline
15
PV output too low. Why? Time series suggests inverter outage; offline inverter confirmed via vendor web portal and repair dispatched
20-Mar-2015 20-Mar-2015
Fault Detection Example: Open Windows
16
9-Mar-2015
9 AM on a MondayHeating well above predicted Root Cause: Windows open all weekend in
a conference room. 35 °F Monday morning; heat in room running at 100%
Image: Shanti Pless, NREL
Fault Detection Example: Open Windows
17
9-Mar-2015
9-Mar-2015
Windows closedaround 9:30 AM
Back in line!
What’s Next?
• Automated model construction• OpenStudio integration?• Haystack!
18
19
Haystack
id: @rsf-mainelecmetersiteMetersiteRef→dis: “RSF”
elecmetersubMeterOf:
@rsf-mainmechanical
20
Questions?
Stephen Frank, Ph.D.Commercial Building Systems IntegrationNational Renewable Energy Laboratory303-275-4249 (office)[email protected]