High-Fidelity Building Energy Monitoring Network Computer Science Department University 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 Node 6

Two Designs 7 ACme-AACme-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-AACme-B A tradeoff between fidelity and efficiency

ACme Node API 9  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 functionPurpose read() -> (energy, power)Read current measurements report(ip_addr, rate) -> NullBegin sending data switch(state) -> NullControl 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 internet backhaul links edge routers Acme nodes data repository app 1 app 2

Network Performance  49 nodes in 5 floors  Single edge router  6 month to-date  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 Apache ACme Driver 6loWPAN 12

Visualization 13

Building Energy Monitoring Understanding the load tree 2. Disaggregation  Measurements  Estimations 3. Re-aggregation  Functional  Spatial  Individual

Understanding the Load Tree 15

Deployment 16  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

Deployment 17

Raw Data 18

Additivity using Time Correlated Data 19

Multi-Resolution 20

Appliance Signature 21

Functional Re-aggregation 22

Correlate with Meta-data 23

Spatial Re-aggregation 24

Individual Re-aggregation 25

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 DiscussionConclusion

Discussion 29  LoCal web site:  ACme web site:  Contact: