Sustainable Infrastructure for Energy and Water Supply (SINEWS)
Arizona State University, Georgia Institute of Technology, The University of Georgia - Athens
National Science Foundation, EFRI RESIN Project
Steve French, Ke Li
George Karady, Eric Williams, Miroslav Begovic, Bert BrasJohn Crittenden, Eric Williams, Sam Ariaratnam
Dynamic life cycle energy of
multicrystalline-Silicon Photovoltaic
EIOLCA = economic input-output
LCA
Process LCA = bottom up materials
flow based LCA
Aqua
ConserveWeathermatic
HydroPoint
Data
Systems
Life cycle CO2
savings (kg/yr)39 to 92 43 to 122 -2 to 190
Annual water bill
savings-$3 to $62 $7 to $66 -$37 to $95
Life cycle CO2 and cost for different models
of smart irrigation controllers for Phoenix households
Reliability of Energy Production System
Life Cycle Assessment of Decentralized Energy Production
and Electrified Transportation
Reliability of Water Distribution System
0
1
2
3
4
5
6
7
8
Ene
rgy
Use
Pe
r P
asse
nge
r D
ista
nce
(M
J/p
ers
on
-km
)
-500
50100150200250300350400450500
CO
2O
utp
ut
Pe
r P
asse
nge
r D
ista
nce
(g
/pe
rso
n-k
m)
PTW CO2 Output Per Passenger DistanceWTP CO2 Output Per Passenger Distance
• Poor environmental performance of electric vehicles, all sizes, due
to coal fired powerplants (Georgia Power’s Plant Bowen emits
about 0.9kgCO2/kWh_
• Marta rail & bus performance bad due to low ridership
• Renewable distributed generators (such as PV)
may be located at several locations across
distribution feeders or microgrids
• At strategic locations, reclosers are installed to
allow the possibility or system separation into islands
• Islanded operation within zones with balanced
generation and load is expected to be allowed under
future standards, such as IEEE 1547.4, currently
undergoing balloting
• In such cases, faults within any of the islands
(outlined by dashed lines) would only affect the loads
within the island and not the entire feeder
• That would create positive impact on overall
reliability of the feeder, but requires that the topology
of the feeder (or microgrid), distributed generators
and recloser(s) be optimized (ongoing work)
Land Use and Policy
Land Use Scenarios and Forecasting
Unit :
kWh/106 gal
Raw Water
AcquisitionTreatment Distribution
Surface
Water
0 ~ 9,200 (depending on
the conveyance
distance)
~1,200 (can be up to
5,200 for
desalination)
~ 1,100 (varies depending
on the topography
and distance)Groundwater
500 – 2,000 (depending on
depth)
100 – 5,000 (depending on
water quality)
WastewaterTypically
gravity flow~ 2,500 N/AE
ne
rgy f
or
Wa
ter
Wa
ter
for
En
erg
y
Membrane Bioreactor (MBR)
Centralized Wastewater Treatment with MBR
Decentralized
Stormwater Management
- Bioretention Area
Fu
ture
Fail
ure
Rate
Pre
dic
tio
n
Wa
ter
Ma
in B
rea
k D
ata
Bre
ak
/Mil
e/Y
ea
r (1
99
1-9
6) Decade ACP DIP CIP RCP GALV STL.CYL PVC STL
1900 0 0 0 0 0 0 0 0
1910 0 0 0 0 1.58 0 0 0
1920 0.38 5.11 2.72 0 9.53 0 0 0
1930 0.23 1.06 0.31 0.09 0.82 0 0 0
1940 1 1 0.48 0.38 3.71 0 0 0.98
1950 0.19 0.72 0.38 0.04 3.67 0.02 0 0.36
1960 0.19 0.77 0.25 0.05 3.16 0 0 4.16
1970 0.13 0.37 0.27 0.03 2.83 0.72 1.37 0.09
1980 0.1 0.24 0.2 0.03 5.08 0 0 0.47
1990 0.13 0.19 0.89 0.01 0 0 0 0
Legend:
ACP: Asbestos Cement Pipe,
DIP: Ductile Iron Pipe,
CIP: Cast Iron Pipe,
RCP: Reinforced Concrete Pipe,
GALV: Galvanized Steel Pipe,
PVC: Polyvinyl Chloride Pipe,
STL.CYL.: Steel Cylinder pipe
STL: Steel pipe
Past
an
d C
urr
en
t R
ate
Reliability can be defined as “the probability that
the system performs its specified tasks under
specified conditions in specified time” (Kaufmann
et al. 1977)
Life Cycle Assessment of Centralized and Decentralized Water/Wastewater Systems
Energy SourceGallons Per kWh
(Evaporative loss)
Hydro 18.27
Nuclear 0.62
Coal 0.49
Oil 0.43
PV Solar 0.030
Wind 0.001
Household Wastewater
Effluent to Dosing/Distribution Network
Discharge to subsurface
Septic Tank Intermittent Sand
Filter (Single Pass)
Decentralized Wastewater Treatment
Smart Irrigation
Controller
Phoenix growth scenarios (above)
and urban form indicator(below)
Atlanta growth scenarios (above)
and employment location(below)
Employees /Acre
POWER
FLOW
ENGINE
(MATLAB)
Input (Feeder
Information)
- LOAD profiles
- Voltage
Controls
Power Flow
Solutions
- Voltages
- Currents
- Power, loss,
power
factor,…
METHODOLOGY
MONTE
CARLO
SIMULATION
- Impact of PV penetration
- Inverter control
strategies
- Impact of DG placement
- Voltage profile, power
factor, losses, reliability
improvement
Input
- Random DG
size and
locations
- Transformable
feeder
topologies
- Random DG
generation
Load Profiles
PV Output Boundaries of Islands
• ASU developing a design method for design
Urban, Electrical Micro-grid with Distributed
Generation
• The first step is the determination of the capacity of
the existing infrastructure:
– How many kW the water, gas etc system can
support
• Preliminary results:
– In a community which has 81 houses and 475
kW maximum electrical load the water is
supplied by a 6” pipe
– The capacity of this pipe is: < 415 gal/min
– The present water surplus is: > 22.4 gal/min
– The available surplus water can support:
• 112 kW combined cycle gas turbine
• > 7465 kW Fuel cell
– Similar analysis has been done for the natural
gas and sewer
Mobility System Design & Assessment: Initial Energy & CO2 Results
for Atlanta
The relationship between local policy,
urban structure, and actual consumption
is being explored by examining two
decades of 'planning for quality growth'
in communities in the Atlanta, Georgia
area www.georgiaencyclopedia.org
2030
2030
#0836046
CityMean House
Price
Increase in
Plant
Richness
Increasing
distance to
water course
WTP change %
METRO AREA $167,344 2.37% -0.15%
PEORIA $160,646 6.02% -0.78%
SCOTTSDALE $302,579 -3.14% -0.49%
PHOENIX $140,802 -6.77% -0.18%
GLENDALE $145,922 -9.07% -0.22%
MESA $146,538
TEMPE $178,749 -5.90% -0.58%
AVONDALE $134,961 -35.3% -0.97%
GILBERT $179,702 -0.66%
CHANDLER $150,438 -0.46%
SURPRISE $155,464
GOODYEAR $167,673 1.38%
Willingness to pay for reliability of
supply through a hedonic price
function-Phoenix Vi
Charles Perrings, Doug Noonan, Marilyn Brown Hedonic Price Estimation for Infrastructure Reliability
Hedonic price analysis
ZX
0lnP
– Determine how price affected by
reliability of infrastructures
Breakpoint analysis
– Sup-Wald tests track price jump point
– Compare to infrastructure changes.
Where P: House sale price
: Infrastructure reliability
: Other factors affecting sale
price
ε: error term
X
Z
-10
sup-Wald test
time
Floods and house value in Atlanta
Property ValueLow High
Flash point