Presented by Dr. Andrea Mammoli at OPAL-RT RT15 User Group event in Berkeley on May 13-14, 2015

1. Turning power distribution
feeders into microgrids:
challenges & opportunities
​
Andrea Mammoli
Mechanical Engineering
University of New Mexico
!

2. a"prototype"of"a"future"distribu/on"feeder
NEDO
microgrid
450 kW total
islanding
switch
Commercial
facility
300 kW PV
4MWh thermal store
ABQ studios
4MWh ice storage
Educational
facility
2MWh thermal
solar HVAC
Prosperity
500 kW PV
1MWh / 250 kW E
0.25 MWh / 500 kW P
Cogenra
1 MW CPV
2.5MWh kW ORC
Piller
21 MJ flywheel
1 MW C/T
Residential
300 houses
1 MW peak load
DR / scheduling
Studio14 @ Mesa del Sol
our goal: to turn the entire feeder into a microgrid

3. what"the"u/lity"sees
Studio14
Tramway11
Sewer14
quack!

4. Problems"and"possible"(microgrid)"solu/ons
• Naturally!increasing!PV!
penetra2on!at!the!distribu2on!
level!
• EVs!and!residen2al!ba9eries!
• Higher!cooling!loads!
• Need!for!higher!resilience!in!
the!face!of!extreme!events!
• Mismatch!between!regulatory!
framework!and!technology!
• Lots!of!poten2al!for!control!at!
the!commercial!and!residen2al!
level!from!pervasive!IT!
• Decreasing!cost!of!ba9ery!
storage!
• Growth!of!aggrega2on!service!
providers!
• Exis2ng!infrastructure!can!be!
modified!at!moderate!cost!

5. A"tradi/onal"microgrid
• 240!kW!recip!genset!
• 80!kW!phosphoric!acid!fuel!cell!
• 50!kW!PV!array!
• 160!kWh!ba9ery!storage!
• Heat!recovery!
• Cold!thermal!storage!
• Electric!&!absorp2on!chillers!
• MicroQEMS!for!districtQlevel!energy!
management!
• BEMS!to!manage!systems!inside!
microgrid!in!response!to!EMS!

6. U/lity=scale"distributed"PV"with"ba?ery
PV field (500 kW)
power and energy
batteries
(1 MWh total)
PV inverter
DAS
battery inverter
PNM-DOE PV + battery project
• Ba9eries!with!
ultracapacitors!smooth!
PV!intermi9ency!by!
injec2ng!kW!
• Storage!ba9eries!used!
for!mul2ple!purposes!
including!peak!shaving,!
arbitrage!and!firming,!
via!MPC!control!
!
!

7. Less"conven/onal"resources:"HVAC"fans
PV!power!
bandpass!filter!of!PV!
fan!speed!
fan!current!
net!power!
HVAC!fans!can!be!
used!to!absorb!the!
intermi9ent!part!of!
nearby!PV!
genera2on!with!
li9le!if!any!effect!on!
thermal!comfort!or!
energy!
consump2on!

8. More"op/ons"for"load"control
1000 residential units
- afternoon peak dominated by cooling
- can we put TCLs to good use?
20 large commercial units
- based on UNM building data
- cooling load could be shifted by active thermal storage

9. hidden"treasure:"TCLs"as"storage
! In!New!Mexico,!A/C!loads!are!
responsible!for!47%!of!peak!load!
(Itron!Q!2006)!
! Lots!of!other!TCLs!–!refrigerators,!
water!heaters,!clothes!dryers!
! increasingly,!these!devices!can!
talk!to!the!world!–!think!Google!!
! Can!these!do!more!that!
“conven2onal”!DR?!

10. Two"hours"in"the"life"of"a"thermostat

11. TCLs"in"undisturbed"state

12. How"an"aggregate"of"TCLs"can"track"a"signal

13. Opera/onal"desirables
• DayQahead!scheduling!
• ReQscheduling!when!be9er!informa2on!is!available!
• maintaining!power!balance!in!real!2me!
• avoiding!voltage!fluctua2ons!
• automated!islanding!based!on!voltage!or!frequency!
• maintain!power!quality!in!islanded!mode!
• synchroniza2on!and!reconnec2on!
• protec2on!/!safety!
• ancillary!services:!frequency!regula2on,!volt/VAR!support,!spinning!
reserve,!demand!response,!black!start!support!
• economic!benefits!to!service!area!

14. Scheduling"via"SoJware=as=a=Service

15. Example"of"an"op/mized"schedule
solar!chiller!operates!at!night!when!possible!
cold!storage!charging!from!electric!chiller!always!offQpeak!
no!storage!on!weekends!

16. Reac/ng"to"changing"circumstances
! DayQahead!schedules!are!
based!on!forecasts.!
! When!reality!deviates!from!
the!forecast,!adjustments!
must!be!made.!
! At!any!given!2me,!the!op2mal!
use!of!resources!should!s2ll!
be!sought.!
! Model!Predic2ve!Control!is!
applied!here!to!op2mize!
based!on!current!condi2ons,!
with!forecasts!made!on!a!
shorter!2me!horizon.!
Minimize"cost"˄"func/on
Subject"to"constraints"˅

17. First"we"decompose"frequency"bands
We!can!associate!resources!with!
slow!response!to!low!frequency!
band,!ones!with!moderately!fast!
response!to!medium!frequencies,!
and!so!on,!cascading.!

18. Then"we"solve"the"MPC"for"each"band
As!expected,!cheap!resources!
make!up!the!bulk!of!the!service,!
while!the!others!come!on!line!as!
needed.!
!
Individual!resources!can!consist!of!
selfQcontained!physical!systems,!or!
aggrega2ons!of!many,!and!can!be!
more!or!less!localized.!
!
!

19. What"we"have"learned
! Distribu2on!feeders!are!excellent!candidates!for!microgrifica)on+
! Some!DERs!are!s2ll!quite!expensive!–!a!0.5MW!microgrid!can!cost!several!$M!
–!on!the!order!of!approximately!$10/W.!O&M!can!also!be!problema2c!
! There!are!many!challenges!that!need!to!be!met!–!especially!in!islanded!mode,!
due!to!the!smaller!number!of!dispatchable!resources!–!so!control!is!key!
! There!are!opportuni2es!hiding!in!plain!sight!–!for!example,!control!of!TCLs!
provides!us!with!an!inexpensive!“ba9ery”!
! A!framework!to!integrate!the!design!and!control!of!the!feeder!microgrid!is!
star2ng!to!materialize!

20. Credits
! Ma9!Robinson!–!MS!UNM!ME!
! Leila!Ghanbari!–!MS!UNM!ECE!
! Feng!Cheng!–!PhD!UNM!ECE!
! Nicholas!Heine!–!PhD!UNM!ME!
! Yasser!Yasaei!–!PhD!UNM!ECE!
! Birk!Jones!–!PhD!UNM!ME!
! Alessandro!Pensini!–!PhD!DTU!