presented by: tommy carpenter computer science university of waterloo

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PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

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Page 1: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

PRESENTED BY:

TOMMY CARPENTER

COMPUTER SCIENCE

UNIVERSITY OF WATERLOO

Page 2: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Outline

The grid has real problems

• that smart grids can solve

These problems are intrinsic and difficult

• so progress has been slow

Three areas where changes are imminent are solar, storage, and sensing

• examples of our work in these areas

Page 3: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

The Grid

Page 4: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

…is old

Post-war infrastructure is reachig EOL

Page 5: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

…inefficient

US DOE: http://www.southeastchptap.org/cleanenergy/chp/

Page 6: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

…poorly measured

Page 7: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

…poorly controlledElectrons are not addressable

RealityPerception

Page 8: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

…dirty (mostly)

Page 9: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

…without storage (mostly)

Needed capacity

http://ieso-public.sharepoint.com/

Page 10: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Smart grid

Page 11: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Current gridRenewables/low carbon

Storage rich

Sensing rich

Control rich

Efficient

Decentralized

High carbon footprint

Little to no storage

Poorly measured

Poorly controlled

Inefficient

Centralized

Smart grid

Page 12: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

…but Consumers & Utilities lack incentives

Savings of 10%: $5-10/month

Utilities make $$ regardless

Page 13: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

hence slow progress:

-Demand response: only time of use pricing

-Grid storage: tiny

-Smart buildings and homes: demo stage

-Microgrids: rare

-Electric vehicles: early mainstream

-Security and privacy: mostly missing

Page 14: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Three inflection points

Solar

Storage

Sensing (and control)

Page 15: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO
Page 16: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO
Page 17: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Storage research, investment growthGlobal investment to reach $122 Billion by 2021 – Pike Research

LiON Declining. $600 down to <$200

Largest change: EVs Some grid storage

Page 18: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Sensing & Control

Michigan Micro Mote

HomeGrid

Pervasive

Page 19: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Our Contributions

Page 20: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

GRIDRenewable Source

ElectronsStorage

Transmission lineTransmission network

Distribution networkDemand response

INTERNET =Variable bit-rate source=Bits=Buffer=Communication link=Tier 1 ISP=Tier 2/3 ISP=Congestion control

Insight: Grid-Net Isomorphism

Page 21: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

SSS: Solar, Storage, Sensing

Page 22: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Sensing: auto thermal comfort (Spotlite) - Uses ML to learn comfort levels, occupancy patterns

- Pre-heat prior to occupancy periods, lower heat afterwards

- Cooling

6 7 8 9 10111213141516171820212223242526

Time of a day

Te

mp

era

ture

Page 23: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Sensing: preserving data privacy

App

VEE

API

App Store

Gateway

Host

-Certification and Validation

-Data collection

-Data access control-Application

framework

-High density hosting

-Integrating cloud storage

Each user’s data is stored and processed (by apps) in user-owned virtual execution environments, enabling:

Data ownershipData privacyData applications

Page 24: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Sensing + Storage: distributed charging

1 EV = 5 homes

• Creates hotspots

Real-time AIMD control of EV charging rate

Solution is both fair and efficient

- Goal: fairly allocate resources during congestion periods- Our work: distributed, model free and real time via congestion signals- Prior work: centralized, perfect network knowledge, day ahead,

Page 25: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Solar + Storage: Solar EV Charging - Base case (no solar): try meeting all charging deadlines - If infeasible; perform fair allocation

- Integrate solar to reduce emissions while ensuring same (or greater) utility

Page 26: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Solar + Storage: ROI, EROEI of Solar Systems w/ Storage

-Advanced modeling of stochastic inputs, comprehensive battery model

Page 27: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Storage: EV ecosystem & adoption modeling

Page 28: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Storage: EV Sentiment Analysis

EV Ops gauged using:

- Field Trials: Expensive = usually short, not many participants

- Surveys: Hard to target

- But lots of opinions buried in discussion forums!

Page 29: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Storage: EV Sentiment Analysis

Page 30: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Storage (EVs): Vehicle Access networks for EV owners- Range Anxiety: long trips not possible yet. Prohibitive to ownerswithout another car.

- EV owners sometimes need access to ICEVs

- Solution: operate some form of multi pool network (a carshare)

- Can be integrated into dealership, operated by gov, community nonprofit, etc.

- Regardless of business model, sizing/managing the fleet is hard

Page 31: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Storage (EVs): Vehicle Access networks for EV owners

Challenge: Ensure maintained over timeDemand patterns constantly changing, non-stationary, arbitrary

Page 32: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Sensing + storage + solar: WeBike- A fleet of 25-30 ebikes on campus

- Tons of sensors, data collection

- Bikes now being deployed!

Page 33: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Why study eBikes?

Page 34: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Conclusions

- We are networking and smart grid researchers exploiting similarities between the net and grid

- Currently working in 3 main areas:

- Solar- Storage (EVs)- Sensing/Control

Page 35: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Extra Slides

Page 36: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Sensing: TOU pricing analysis

Current

Page 37: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Sensing: TOU pricing analysis

Current

Page 38: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Sensing: TOU pricing analysis

Current

Proposed

Page 39: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Solar + Storage: Cost-Efficient Energy Storage

Page 40: PRESENTED BY: TOMMY CARPENTER COMPUTER SCIENCE UNIVERSITY OF WATERLOO

Source: European technology platform: Smart Grids

Smart grid vision