high-fidelity building energy monitoring network
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High-Fidelity Building Energy Monitoring
Network
Computer Science DepartmentUniversity of California - Berkeley
LoCal Retreat 2009
Xiaofan Jiang and David Culler
In collaboration with Stephen Dawson-Haggerty, Prabal Dutta, Minh Van Ly, Jay Taneja
My PG&E Statement
Current level of visibility Delayed Aggregated over
time Aggregated over
space Inaccessible
Want Real-time Per-appliance
[Stern92], [Raaii83]
2
Aggregate is Not Enough
What percent is plug-load
What percent is wasted by idle PCs at night?
3
What’s the effect of server load on energy?
What’s the effect of turning off A?
What caused the spike at 7:00AM?
This would be nice…4
Architecture
ACme application Standard networking
tools Python driver + DB +
web ACme network
IPv6 wireless mesh Transparent connectivity
between nodes and applications
ACme node Plug-through Small form factor High fidelity energy
metering Control Simple API
5
ACme Node6
Two Designs7
ACme-A ACme-B
ACme-A vs ACme-B
Resistor + direct rectification + energy metering chip
Real, reactive, apparent power (power factor)
Idle power 1W Low CPU utilization
Hall-Effect + step-down transformer + software
Apparent power Idle power 0.1W Medium CPU
utilization
8
ACme-A ACme-B
A tradeoff between fidelity and efficiency
ACme Node API9
ASCII shell component running on UDP port provides direct access to individual ACme node: Adjust sampling parameter Debug network connection Over-the-air reprogramming
Separate binary UDP port for data Periodic report to ip_addr at frequency rate
Node API function Purpose
read() -> (energy, power) Read current measurements
report(ip_addr, rate) -> Null Begin sending data
switch(state) -> Null Control the SSR
ACme Network
IPv6 mesh routing Each ACme is an IP
router Header compression
using 6loWPAN/IPv6 (open implementation -blip)
Modded Meraki/OpenMesh as “edge router”
Diagnostics using ping6/tracert6
ACme send per-minute digest / no in-network aggregation
10
internetinternet
backhaul linksedge routersAcme nodes
data repository
app 1app 2
Network Performance
49 nodes in 5 floors
Single edge router
6 month to-date 802.11
interference (on channel 19)
11
ACme Application
N-tier web application ACme is just like
any data feed Python daemon
listening on UDP port and feed to MySQL database
Web application queries DB and visualize
UDP Packets
Python Daemon
MySQL DB
ApacheACme Driver
6loWPAN
12
Visualization http://acme.cs.berkeley.edu/
13
Building Energy Monitoring14
1. Understanding the load tree
2. Disaggregation Measurements Estimations
3. Re-aggregation Functional Spatial Individual
Understanding the Load Tree
15
Deployment16
Edge router obtaining IPv6 address
Ad-hoc deployment Un-planned
Online “registration” using ID and KEY Meta data collection Security
Online for 6 month and counting
10 million rows
Deployment17
Raw Data18
Additivity using Time Correlated Data
19
Multi-Resolution20
Appliance Signature21
Functional Re-aggregation22
Correlate with Meta-data23
Spatial Re-aggregation24
Individual Re-aggregation25
Improvements in Energy Usage
26
Reducing Desktop Idle Power
27
Discussion and Conclusion
Measurement fidelity vs coverage
Non-intrusive Load Monitoring (NILM)
IP node level API vs application layer gateway
Easy of deployment is key
DB design Multiple input
channel / power strip
ACme is a fine-grained AC metering network that provides real-time high-fidelity energy measurement and it’s easy to deploy
3 steps to building energy monitoring – understanding load tree; disaggregation; re-aggregation
28
Discussion Conclusion
Discussion29
LoCal web site: http://local.cs.berkeley.edu ACme web site: http://acme.cs.berkeley.edu Contact: fxjiang@cs.berkeley.edu
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