cyber-physical energy systems: focus on smart buildings presentation by francis usher cs 525 fall...
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Cyber-Physical Energy Systems: Focus on Smart Buildings
Presentation by Francis Usher
CS 525 Fall 2012
Monday September 19, 2012
Goals
● Examine challenges for energy systems● Virtual case study
– Implementation challenges in RL scenario– Estimated energy costs and prodction
● Thought experiment– How close can we get to self-sufficiency?
Motivation
● Buildings: 70% electricity, 40% GHG● Push for Zero Net Energy Buildings (ZNEB)● Coupled generation, sensing, & control
– Just one or two of these inadequate
Energy Metrics & Concepts
● Detailed breakdown of energy usage– “Mixed-use” building– Lighting, mechanical, machine-room, plug– Baseline load
● Large % total load● Unreasonably high
Experimental Design
● UCSD CSE building (mixed-use)● Normal weekday occupancy● Lots of permanent heavy-duty IT equipment● Large roof space● Climate control (overlooked)
Mitigation Approach
● IT Infrastructure (Somniloquy)● Lighting (Motion sensors & LED)● Generation (Solar PV)
– Other generation forms not widely suitable
Somniloquy
● People don't put their computers to sleep!● Must allow lightweight, always-on net apps● Pilot test on 30 CSE desktop users
– 60-80% savings
● Server estimate 50%– Workload consolidation– Virtual machine migration
Lighting
● Off-hours mitigation– Don't jeopardize productivity– 20% of baseline = safety critical lights– Other lights on motion sensor
● LED lights– Reduction to 1/3
Solar PhotoVoltaic (PV)
● Function of available roof space (2700m²)● AC conversion efficiency vs. requirements
– 15% (standard)– 25-48% (necessary with tracking)– 31-66% (thermodynamic limit)– 32% (laboratory multi-junction)
● Update– 30% (ZTJ space-application multi-junction)– 43% (laboratory multi-junction)
Main Results
● Breakdown of metered energy use– Baseline plug load (PC energy use) ~ 50%
● Savings capacity– Mostly IT, some light
● Comparison with PV generation capability– Contemporaneous PV technology inadequate
Future Work
● Real-world tests– Implement changes– Collect data– Fine-tune, tweak
● Analysis of cooling & ventilation optimization– Make climate control ~ actual needs– More efficient fans & pumps– Closed-loop zonal climate control– (assumed savings of 20%)
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