[PPT] - ISS4E or how can the Internet help smarten the grid? S K S. S. PowerPoint Presentation

SLIDE 1

ISS4E or how can the Internet help smarten the grid?

S K h K h d C R b d C R b S.

S. Keshav

Keshav and C. Rosenberg and C. Rosenberg

May 2011 May 2011

http://blizzard.cs.uwaterloo.ca/iss4e http://blizzard.cs.uwaterloo.ca/iss4e

SLIDE 2

Smart Grid

Bi‐directional energy flows Integration of renewables renewables Smart Grid Consumer’s Participation Communication Elastic Loads: EVs + smart appliances Storage

2

SLIDE 3

Smart Grid: large scale, heterogeneous, distributed system distributed system

Millions of sources

C i ti Millions of sources

Stochastic sources

l d l i i

Communication
Maintaining
New loads: elasticity,

variable demand reliability

Incentivization
Two‐way flows
Dealing with storage
Security
Non‐traditional utility

g g

Non‐traditional utility

players

3

SLIDE 4

The smart grid will require massive change

A relatively static, predictable, stable t ith i l ti A highly dynamic system with elastic loads and millions of points of control system with inelastic loads and a few points of control millions of points of control A di hift

4

A paradigm shift

SLIDE 5

Our Research Our Research

h id Use Internet concepts to smarten the grid

5

SLIDE 6

Why Is This Possible: Similarities y

Large‐scale

Large scale

Heterogeneous

C iti l i f t t

Critical infrastructure
Both match geographically distributed demands

with distributed generation

Distributed sources that are highly variables
Hierarchical
Balance centralization and decentralization
Balance centralization and decentralization

6

SLIDE 7

Differences Differences

Primarily one‐way vs primarily two‐way flows

Primarily one way vs. primarily two way flows

Grid has practically no storage

C d h i l i l bill

Consumers are used to see their electrical bill

reflect what they really use

7

SLIDE 8

Our Vision

To apply our expertise in Information Systems and Sciences to find innovative solutions to problems in energy f p gy systems. We work within Waterloo Institute for Sustainable Energy (WISE) in collaboration with

researchers in related disciplines
researchers in related disciplines
partners in industry

Initial focus is smart grids, where energy systems converge with information systems

8

SLIDE 9

ISS4E

 Faculty  S. Keshav, Canada Research Chair, Computer Sciences  C Rosenberg Canada Research Chair El t i l & C t E  C. Rosenberg, Canada Research Chair, Electrical & Computer Eng.



Post‐Doctoral Fellow



Weihong Wang



PhD students



PhD students



Pirathayini Srikantha



Tommy Carpenter



Masters students



Omid Ardakanian



Ryan Case



Bo Hu h d



Theodosios Tzoutzas



Hadi Zarkoob



Laboratory facilities include sensors for building monitoring, smart power strips for home monitoring and control, ENVI systems for data collection, wireless sensors for solar panel monitoring, etc.

9

SLIDE 10

Our expertise p

Modeling, mathematical analysis, and system building using techniques from: using techniques from:

 Internet and information technology (planning, design,

implementation, deployment, and management) p , p y , g )

 Telecommunications (wireline and wireless communication

systems)

 Distributed systems  Stochastic analysis  Large scale sim lation  Large‐scale simulation  Data mining and machine learning  Economics and game theory  Economics and game theory

10

SLIDE 11

Ongoing projects

1. Modeling and control of grid energy storage and DG

11

SLIDE 12

Ongoing projects

1. Modeling and control of grid energy storage and DG
2. Demand Response: a revisit based on
Internet views (allows fine grained DR)

Internet views (allows fine grained DR)

Elasticity

12

SLIDE 13

Ongoing projects

1. Modeling and control of grid energy storage and DG
2. Demand Response: a revisit based on
Internet views (allows fine grained DR)

Internet views (allows fine grained DR)

Elasticity
3. Smart Home
GW to appliances (control measurement)
GW to appliances (control, measurement)
Applications

13

SLIDE 14

Ongoing projects

1. Modeling and control of grid energy storage and DG
2. Demand Response: a revisit based on
Internet views (allows fine grained DR)

Internet views (allows fine grained DR)

Elasticity
3. Smart Home
GW to appliances (control measurement)
GW to appliances (control, measurement)
Applications
4. EV Integration
Charging control
Billing and roaming
Fleet integration

Fleet integration

14

SLIDE 15

Ongoing projects

1. Modeling and control of grid energy storage and DG
2. Demand Response: a revisit based on
Internet views (allows fine grained DR)

Internet views (allows fine grained DR)

Elasticity
3. Smart Home
GW to appliances (control measurement)
GW to appliances (control, measurement)
Applications
4. EV Integration
Charging control
Billing and roaming
Fleet integration

Fleet integration

5. Impact of context
Developed countries vs. developing countries (e.g., smart EPS)

15

SLIDE 16

Ongoing projects

1. Modeling and control of grid energy storage and DG
2. Demand Response: a revisit based on
Internet views (allows fine grained DR)

Internet views (allows fine grained DR)

Elasticity
3. Smart Home
GW to appliances (control measurement)
GW to appliances (control, measurement)
Applications
4. EV Integration
Charging control
Billing and roaming
Fleet integration

Fleet integration

5. Impact of context
Developed countries vs. developing countries (e.g., smart EPS)

6 Prototype systems & measurements

6. Prototype systems & measurements
ENVIs, Sensors, I‐smart, HomeOS

16

SLIDE 17

Measure

Fine grained

SLIDE 18

Measure

Fine grained

SLIDE 19

Measure

Fine grained

SLIDE 20

Measure Model

SLIDE 21

Measure Model Analyze Analyze

Trends Gain from storage g

SLIDE 22

Measure Model Analyze Analyze

Trends Gain from storage g

SLIDE 23

Measure Model Analyze Analyze

Trends Gain from storage g

SLIDE 24

Measure Model Analyze

Controller Broadcast

Analyze Control

House

EV charging

Lateral PHEV Pole-Top Transformer PHEV

SLIDE 25