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Energy  &  Smart  Grid  Research  @    Virginia  Tech  -­‐  Advanced  Research  Ins;tute  

(www.ari.vt.edu)  Presenta(on  to  Infotech  Enterprises  

       

April  2,  2012  Hyderabad,  India  

 Professor  Saifur  Rahman  

Virginia  Tech  –  Advanced  Research  Ins(tute  

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900  N  Glebe  Rd,  Arlington,  VA  

Virginia Tech Research Center Arlington, VA

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ARI Research Areas

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Smart  Grid

Microgrid  and  reliability  analysis

Renewable  energy  integra(on  and  

storage   Demand  response  

Energy  efficiency Electric  

vehicle      

•  Development  of  a  test  bed  to  analyze  reliability  and  resiliency  of  electric  power  microgrid    

•  Using  energy  storage  to  mi(gate  impacts  of  renewable  energy  fluctua(on  

•  Storage  sizing  to  balance  wind  forecast  mismatch  

•  NaS  baOery  storage  •  Compressed  air  energy  

storage  (CAES)    

•  Impact  of  DR  on  distribu(on  circuit  load  shape  

•  Demand  response  algorithms  

•  The  use  of  demand  response  to  mi(gate  power  system  stress  condi(ons    

•  Bi-­‐level  and  demand-­‐sensi(ve  LED  street  ligh(ng  system    

•  Solar  water  heater  vs  electric  water  heater  

•  Impact  of  energy  efficient  appliance  on  distribu(on  circuit  load  shape    

•  Impact  of  high  penetra(on  of  EV’s  on  distribu(on  transformers  

ARI Research Spectrum

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Transmission   Distribu(on  Substa(on  

Distribu(on  Circuit  

Distribu(on  Transformer  

Household  level  

Building  level  

Distribu(on   Customer  Transmission  

IT  Network  

Transmission:  Grid  scale  storage  and  demand  response  planning  tools    Distribu;on:  Transformer  level  demand  response,  smart  homes,  electric  vehicle  

penetra(on,  integra(on  of  distributed  energy  sources,  microgrid  resiliency  and  reliability  analysis  and  energy  efficiency  

 Customer:  Home  energy  management  (HEM)  systems,  peak  reduc(on  and  energy  

saving  poten(als  for  residen(al  and  commercial  customers    IT  Network:  Web  services  for  integra(on  of  smart  homes  in  the  smart  grid,  wireless  

communica(ons  for  HMS,  data  mining  and  data  sampling  rates  for  HMS  systems  

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Organiza;on  

1   Smart  Grid  Informa;on  Clearinghouse  

       Sponsor:  US  Department  of  Energy,  PI:  Dr.  Saifur  Rahman  

2   A  Test-­‐Bed  for  Analyzing  the  Security  and  Resiliency  of  the  DG-­‐integrated  Electric  Power  Distribu;on  Network  

       Sponsor:  US  Na(onal  Science  Founda(on,  PI:  Dr.  Manisa  PipaOanasomporn  

3   Feasibility  and  Guidelines  for  the  Development  of  Microgrids  in  Campus  Type  Facility  

       Sponsor:  US  Army  Corps  of  Engineers,  PI:  Dr.  Saifur  Rahman  

4   US-­‐Egypt  Coopera;ve  Research:  Managing  Grid  Integra;on  of  Large-­‐Scale  Wind  Power  Parks  using  Energy  Storage  Technology  and  Demand  Response  

       Sponsor:  US  Na(onal  Science  Founda(on,  PI:  Dr.  Saifur  Rahman  

5   Role  of  the  Smart  Grid  in  Allevia;ng  Electrical  Power  System  Stress  Condi;ons  Through  Demand  response  

       Sponsor:  US  Na(onal  Science  Founda(on,  PI:  Dr.  Saifur  Rahman  

6   Bi-­‐Level  Demand-­‐Sensi;ve  LED  Street  Ligh;ng  Systems  

       Sponsor:  US  Army  Corps  of  Engineers,  PI:  Dr.  Saifur  Rahman  

ARI Research Projects www.ceage.vt.edu/ceage_projects

Smart  grid  

Microgrid  

Renewable/storage  

Demand  response  

Energy  efficiency  

Smart Grid Information Clearinghouse

To  design,  populate,  manage  and  maintain  a  public  SGIC  web  portal  that  reaches  out  to  a  broad  user  community  both  for  informa(on  gathering  and  knowledge  delivery.  

 

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 www.SGIClearinghouse.org  

 

Objec(ve:  

PI:  Dr.  Saifur  Rahman  

Sponsored  by  US  Department  of  Energy  

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Smart Grid as an Enabler of Intermittent Sources of Electricity

   

02 April, 2012

Hyderabad, India

Invited Talk by Prof. Saifur Rahman

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Changing  Landscape  for  the  Electric  Utility  

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Load  Dura(on  Curve    Dominion  Virginia  Power  (2010)  

Peak load of 19,140 MW

Probability that peak loads exceed

16,000 MW is only 5% of the time

3,140 MW or 16.5% of peak load

 Peak  load  and  its  duration  

 •  In  the  US  20%  of  the  load  happens  5%  of  the  (me    

•  In  Australia  15%  of  the  load  happens  2.5  days  in  a  year  or  less  than  1%  of  the  (me  

•  In  Egypt  15%  of  the  load  happens  1%  of  the  (me      

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 Potential  Savings  from    Peak  Load  Reduction  

 US  has  an  installed  genera(on  capacity  of  1,000,000  megawaOs  

 20%  or  200,000  megawaOs  of  genera(on  capacity  and  associated  transmission  and  distribu(on  assets  are  worth  over  300  billion  dollars  

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Smart  Grid  Defini(on  •  According  to  United  States  Department  of  Energy’s  modern  

grid  ini(a(ve,  an  intelligent  or  a  smart  grid  integrates  advanced  sensing  technologies,  control  methods  and  integrated  communica(ons  into  the  current  electricity  grid.  

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What  Makes  it  Smart?  

Intelligence  Two-­‐way  communica(on  

Real-­‐(me  monitoring  &  control    

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Difference  Between  a  Normal  Grid      And  a  Smart  Grid  

Normal  Phone   Smart  Phone  

Power Plant Transmission

Distribution Home

Business End-use

Appliances

Starting  and  End  Points  of  a  Smart  Grid  

From  Generator  to  Refrigerator  

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Components  of  the  Smart  Grid  

Source: Michael Montoya, SCE, Smart Grid Strategy & Development

SCADA, PMUs,

FACTs, Advanced Conductors

Substation Automation

Advanced Metering, Demand Response and Distributed Resources Distribution Automation

Microgrid

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Merging  Power  Flow  with  Informa(on  Flow:  

   Integrated  Communica(ons  

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Electric  Power  &    Communica(on  Infrastructures  

Central Generating Station Step-Up

Transformer

Distribution Substation Receiving

Station Distribution Substation

Distribution Substation

Commercial

Industrial Commercial

Gas Turbine

Recip Engine

Cogeneration

Recip Engine

Fuel cell

Micro- turbine

Flywheel Residential

Photo voltaics

Batteries

Residential Data Concentrator

Control Center

Data network Users

2. Information Infrastructure

1.Power Infrastructure

Source: EPRI 19

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AMR Customer Outage Detection

Automated Meter Reads

Theft ID Remote TFTN

Remote Meter Programming

AMR Capability+

Load Control

Price Signals sent to Customer

New Rate Design

AMI

Smart Grid AMI Capability+

Remote detection – sensors everywhere

Central and distributed analysis

Correction of disturbances on the grid

Optimizes grid assets

Distribution Automation

Leverage data to understand system performance better

“Self Healing”

Enable use of renewable resources

Enable electrification of transportation

Hourly Remote Meter Reads

Customer Voltage Measurement

Source: EnerNex

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U.S.  Smart  Grid  Projects  by  Category  

Advanced  Metering  

Infrastructure    (AMI)  40%  

Customer  Systems  (CS)  4%  

Distribu(on  Systems  (DS)  

7%  

Equipment  Manufacturing  

(EM)  1%  

Integrated/Crosscujng  systems  (IS)  

27%  

Transmission  Systems  (TS)  

5%  

Regional  Demonstra(on  

(RD)    8%  

Storage  Demonstra(on  

(SD)  8%  

AMI: installation of smart meters to allow the use of real-time pricing, demand response, load management, and more. CS: enabling smart grid functions to equipment and/or software applications at the customer level. DS: adding smart grid functions to devices, equipment, and/or software applications in electric distribution systems. EM: production of smart grid equipment, software, or communications and control systems that can enable smart grid functions. IS: adding smart grid functions to multiple portions of the electric system, which include AMI, equipment manufacturing, customer systems, distribution systems and transmission systems. TS: adding smart grid functions to devices, equipment, and/or software applications in electric transmission systems. RD: demonstrating smart grid functions at a regional level. SD: demonstrating grid-scale energy storage systems.

•  The  network  must  be  absolutely  reliable  •  Endpoints  must  be  much  lower  cost  •  Device  hardware  can’t  be  upgraded  olen  •  Can’t  just  ignore  very  rural  customers  •  Need  security  all  the  (me,  not  just  some(mes  

•  Applica(ons  are  s(ll  being  defined  

Physical

- Application

- Network

The  Smart  Grid  is  different  than  the  Internet  

 

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Plamorm  for  Smart  Grid  R&D    The  electric  power  industry  provides  the  plamorm  and  the  context  

Telecommunica(on,  IT  and    computer  industries  provide  the  technology  and  solware  to  interface  with  the  electric  power  network  

The  electric  power  industry  will  require  new  genera(on  of  engineers  who  are  versa(le  in  several  disciplines  

   

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Who  else  is  ac(ve  in  smart  grid?    

The  non-­‐tradi(onal  players  

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CISCO’s  Smart  Grid  

http://www.cisco.com/web/strategy/energy/external_utilities.html

GE’s  Plug  into  the  Smart  Grid  http://ge.ecomagination.com/smartgrid/

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IBM’s  Smarter  Planet  http://www.ibm.com/smarterplanet/

Siemens’  Smart  Grid  http://www.energy.siemens.com/hq/en/energy-topics/smart-grid/

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Building  Blocks  of  the  Smart  Grid  

© Saifur Rahman

Thank  you  

   Prof.  Saifur  Rahman  

www.saifurrahman.org      

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Poten(al  of  the  Smart  Grid  

Source: US DoE