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