AGU2014: Coupling residential end use and utility water energy models

COUPLING RESIDENTIAL END USEAND UTILITY WATER-ENERGY MODELS

by Alvar Escriva-Bou, Jay R. Lund, Manuel Pulido-Velazquez, Edward Spang and Frank Loge

AGU 2014 FALL MEETING SAN FRANCISCO, DECEMBER 15TH 2014

ALVAR ESCRIVA-BOU

[email protected]

@alesbou

notjustwater.wordpress.com

Water

Energy

Food

Environment

Climate

Industry

OUTLINE

• Residential Water-Energy-CO2 optimization model. Household minimize their bills and conservation costs

facing water and energy price shocks.

• Utility-scale hourly Water-Energy simulation model. Based on actual data we build a model that can simulate

demand changes.

3

RESIDENTIAL END-USE OPTIMIZATION MODEL

• Based on a previous water-energy-GHG assessment study.

• Using probability distribution functions based on a water end-use survey.

• 10,000 MC simulations for 10 different cities in CA.

4

Water

Energy

Uo

Indoor hot water

Indoor cold water

Outdoor water

Air conditioned

Appliances

Space heating

Water heating

Complementarity0

1

2

qw0 qw2qw1

qE1

qE0

qE2

The economics behind the model: Demand

5

DEMAND: CONSERVATION ACTIONS

6

• Each household has a set of available actions:– Long-term: Retrofits.

– Short-term: Behavioral.

• Each action has:– Cost.

• Annualized costs for retrofits.

• Hassle costs on a daily basis for behavioral changes.

– Effectiveness (Water or energy savings).

Conservation Actions: Savings - Technological

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 1 2 3 4 5 6 7 8 9 10

Flow (GPM)

Retrofitted Appliance

Normal Appliance

7

Conservation Actions: Savings - Behavioral

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 2 4 6 8 10 12 14 16 18 20

No

n-ex

cedan

ce pro

bab

ilityR

edu

ctio

n F

acto

r

Behavioral Factor - Shower Length (min/shower)

Household Reduction Factor

CDF of previous behavioral factor

Potential conservation

Consciousness

factor

8

Quantity

Price

D

Supply0

Q0

Supply ‘

Supply ‘’

Q’Q’’

P0

P’

P’’

The economics behind the model: Water Supply

Pw=120% (ρ=0.1)

Pw=110%(ρ=0.2)

Pw=100%(ρ=0.7)

9

The economics behind the model: Energy Supply

8

8.5

9

9.5

10

10.5

11

11.5

12

Jan

-09

Mar

-09

May

-09

Jul-

09

Sep

-09

No

v-09

Jan

-10

Mar

-10

May

-10

Jul-

10

Sep

-10

No

v-10

Jan

-11

Mar

-11

May

-11

Jul-

11

Sep

-11

No

v-11

Jan

-12

Mar

-12

May

-12

Jul-

12

Sep

-12

No

v-12

Jan

-13

Mar

-13

May

-13

Jul-

13

Sep

-13

No

v-13

Jan

-14

Mar

-14

Residential Natural Gas Price

Mean

110%

90%

10

Pe=115%(ρ=0.1)

Pe=100%(ρ=0.8)

Pe=85%(ρ=0.1)

OPTIMIZATION

𝑀𝑖𝑛𝑖𝑚𝑖𝑧𝑒 𝑇𝑂𝑇𝐴𝐿 𝐶𝑂𝑆𝑇 =

𝑤𝑙𝑡

𝐶𝑤𝑙𝑡 ∙ 𝑋𝑤𝑙𝑡 +

𝑒𝑙𝑡

𝐶𝑒𝑙𝑡 ∙ 𝑋𝑒𝑙𝑡 +

𝐵 ∙

𝑤𝑒

𝑝𝑤𝑒 ∙

𝑒𝑒

𝑝𝑒𝑒 ∙ 𝐷 ∙

𝑤𝑠𝑡

𝐶𝑤𝑠𝑡 ∙ 𝑋𝑤𝑠𝑡𝑤𝑒,𝑒𝑒 +

𝑒𝑠𝑡

𝐶𝑒𝑠𝑡 ∙ 𝑋𝑒𝑠𝑡𝑤𝑒,𝑒𝑒 + 𝐵𝑊𝑤𝑒 + 𝐵𝐸𝑒𝑒

• Subject to:

– Decision variables are binary

– Savings are less than initial use (upper bound)

– Mutually exclusive actions

– Interdependence among actions

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Results: Adoption rate and water savings for long-term actions

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Results: Adoption rate and energy savings for water-related actions

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Results: When energy cost is included (respect the only-water scenario)

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• Adoption rate:• Retrofit shower: +7.9%

• Retrofit clotheswasher: +1.7%

• Reduce shower length: +3.2%

• …

• Increased savings:• Indoor water savings: +24%

• Energy savings: +30%

• GHG savings: +53%

Results: Demand function and elasticities

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Results: Own- and cross-price elasticities (averages)

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• Water own-price elasticity Ɛww = -0.05

• Energy own-price elasticity Ɛee = -0.03

• Energy water-price elasticity Ɛew = -0.02

• Water energy-price elasticity Ɛwe = -0.004

• Own-price values are relatively low.

• Water price affects energy consumption more than energy price affects water use.

• Literature about cross-price elasticities reviewed: Only 1 paper!! Lars Garn Hansen (Land Economics, 1996) obtained a Ɛwe = -0.2, but none obtained Ɛew.

UTILITY-SCALE HOURLY WATER-ENERGY SIMULATION MODEL

• Based on a real data from EBMUD water utility.

• We select a only a part that represents 27% of total EBMUD water use.

• We want to simulate real operation to obtain results for different scenarios.

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EBMUD: Selected scheme of study

WTPWWTP

PP

PP

PP

LelandPop. ≈ 130,0006,391 MG/year

Elevation:150 feet – 45 m

Danville Pop. ≈ 75,0003661 MG/year

Elevation:350 feet – 107 m

San RamonPop. ≈ 150,0007553 MG/year

Elevation:550 feet – 168 m

Total Supply:17604 MG/year

(out of 64868 MG/year)

Pardee and Camanche Reservoirs

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Water utilityWater users

Assembling the model

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Total AnnualWater Use

Energy Utility

Hourly water demand

Hourly water supply

Water-related energy

GHG Emissions

Shares of use by customer category

Indoor vs. Outdoor

Hourly distribution of end uses

Irrigation Necessities (P-ET)

Pumping and treatment patterns

Water regulation

Water treatment

Pumping and distribution

Wastewater treatment

Water-related energy

Regressions and pumping

patternsEnd-uses energy

intensity

Some Results: Energy break down

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• Annual water use: 17,604 MG/year

• Annual energy use: 558,000 MWh/year

• Energy Intensity: 31.7 MWh/MG

• Water utility energy cost: $3,355,451

Simulating scenarios

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• Scenario 1: Residential optimal conservation

• Annual water use: 16,541 MG/year (-6%)

• Reduction Energy Use: 36,940 MWh/year (-6.6%)

• Water utility energy savings: $115,493 (3.5%)

• GHG savings: 7023 metric tons / year (93.5% residential and 6.5% Utility)

Simulating scenarios

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• Scenario 2: Peak shaving

• Outdoor consumption shift to off-peak hours

• The same water and energy use (but different hours)

• Water utility energy savings: $51,023 (1.5%)

• Energy utility benefits: ??? But some!

TAKE HOME MESSAGES

• Increased water (and water-related energy and GHG emissions) conservation when energy is included.

• Most of water-related energy is from water heating in households.

• There are gains for water and energy utilities working together.

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Thanks ;)

AGU 2014 FALL MEETING SAN FRANCISCO, DECEMBER 15TH 2014

ALVAR ESCRIVA-BOU [email protected]

@alesbou

notjustwater.wordpress.com