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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Presented by: Tommy Carpenter Computer science University of Waterloo. Outline. The grid has real problems t hat smart grids can solve These problems are intrinsic and difficult s o progress has been slow Three areas where changes are imminent are solar , storage , and sensing - PowerPoint PPT Presentation

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Page 1: Presented by: Tommy Carpenter Computer science University of Waterloo

PRESENTED BY:TOMMY CARPENTERCOMPUTER SCIENCEUNIVERSITY 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 carbonStorage richSensing richControl richEfficientDecentralized

High carbon footprintLittle to no storage

Poorly measuredPoorly controlled

InefficientCentralized

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

SolarStorageSensing (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

Tem

pera

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 rateSolution 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 AnalysisEV 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