Chalida U-tapao Steven A. Gabriel, Christopher Peot and Mark Ramirez
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Transcript of Chalida U-tapao Steven A. Gabriel, Christopher Peot and Mark Ramirez
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Identification of optimal strategies for energy management and reducing carbon dioxide emission at
the Blue Plains Advanced Wastewater Treatment Plant (AWTP)
Chalida U-tapao Chalida U-tapao Steven A. Gabriel, Christopher Peot and Mark RamirezSteven A. Gabriel, Christopher Peot and Mark Ramirez
Dept. of Civil & Env. Engineering, University of Maryland, Dept. of Civil & Env. Engineering, University of Maryland, College Park, MarylandCollege Park, Maryland
District of Columbia Water and Sewer Authority, Washington DCDistrict of Columbia Water and Sewer Authority, Washington DC13 November 200913 November 2009
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Outline
•Overview of energy, wastewater treatment process and objective of this research
•Flowchart of modeling decisions/processes (the Blue Plains AWTP is case study)
•Ongoing work
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(Source: EIA, Energy perspective , June 2009)
U.S. Primary Energy Overview
• Imports fill the gap between U.S. energy use and production• Petroleum is the major imported fuel
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U.S. Energy Consumption by Energy Source, 2008
(Source: EIA, Renewable Energy Consumption and Electricity 2008 Statistics)
Pretoleum, 37%
Coal, 23%
Natural gas, 24%Nuclear Electric
Power, 9%
Renewable Energy, 7%
Wind7%
Geothermal5%
Hydropower34%
Biomass53%
Solar1%
• More renewable energy will decrease imported petroleum, coal and natural gas
• Many renewable energy sources can be selected
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Wastewater Treatment Process
(Source: DC Water and Sewer Authority)
• Contaminated substances are separated in solid form
• Almost all solids are biomass
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Biosolids is a Significant Renewable Energy Source
(Source: DC Water and Sewer Authority)
• Biosolids is biomass that is renewable energy source
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A Huge Plant Such as The Blue Plains AWTP Has Great Potential to Produce Renewable Energy
(Source: DC Water and Sewer Authority)
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Objectives of this research
• Find optimal strategies for energy management • Use energy sources that can reduce the carbon footprint at the Blue Plains AWTP
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SEWAGE
WASA Operations
BiosolidsBiogas
Land application
Electricity
Use at WASA
Outside sales
Investment $
Other clean energywind, solar, etc
Outside salestransp.indust.
Operations/Investments
IdigesterIwind
Isolar
PB 1-PB
PE,W
1- PE,W
electric power grid/market
Flowchart
PB=% of sewage to be converted to biosolids
PE,W=% of power from methane to be used at WASA
PG,W=% of methane to be used at WASA
PG,W
natural gas grid/market
Methane
Use at WASA
carbon allowance market
$$
$IWASA
1-PG,W
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330 MGD
GHG (CO2)
GHG (CO2)
Biosolids
1,163 tons/day
GHG
(CO2 CH4 ,N2O)
Odor
736,087 kWH/day
The Blue Plains AWTP operating process
(Source: Gabriel, S.A., et al., Statistical Modeling to Forecast Odor Levels of Biosolids Applied to Reuse Sites. Journal of Environmental Engineering, 2006).
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The Average Amount of Biosolids Per Day for the Blue Plains AWTP
-
200
400
600
800
1,000
1,200
1,400
Jun-08 Jul-08 Sep-08 Oct-08 Dec-08 Feb-09 Mar-09 May-09 Jul-09
months (2008-2009)
amou
nt o
f bi
osol
ids
per
day/
(ton
s)
Average 1,163 tons per day
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The Average Amount of Organic Dry Matter of Biosolids Per Day for the Blue Plains AWTP
-
50
100
150
200
250
300
Jun-08 Jul-08 Sep-08 Oct-08 Dec-08 Feb-09 Mar-09 May-09 Jul-09
months (2008-2009)
orga
nic
dry
mat
ter
of b
ioso
lids
pe
r da
y/(t
ons)
Average 239 tons per day
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The Anaerobic Biodegradation Production Process
Active biomass + C-substance CH4 + CO2 + stabilized biomass + H2O
Biogas composition
Methane gas 55-65%
Carbon dioxide 30-40%
Water vapor, traces of H2S and H2 0-5%
(Source: Appels, L., et al., Principles and potential of the anaerobic digestion of waste-activated sludge).
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ODS : organic dry solids of the sludge (wt%)
Biogas is 0.4 x 239 x 1000 = 95.6 x 103 cubic meters per day
Methane is 60 % = 57.3 x 103 cubic meters per day
Carbon dioxide is 35% = 33.5 x 103 cubic meters per day
The Relation Between Biogas Production and Retention Time
(Source: Appels, L., et al., Principles and potential of the anaerobic digestion of waste-activated sludge).
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Historic Daily Power Consumption Data for The Blue Plains AWTP
600
650
700
750
800
850
900
Jan Feb Mar Apil May Jun Jul Aug Sep Oct Nov Dec
x 103 kWH
2008
2007
2006
Average 2008 = 736 x 103 kilowatt hours per day
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From Methane Gas to Electricity
• Methane 1 ft3 = 1,028 BTU• 3,412 BTU methane = 1 kWH• Blue Plains AWTP will have almost 534 x 103 kilowatt
hours per day from methane gas( Source: http://tonto.eia.doe.gov/kids/goodstuff.cfm?page=about_energy_conversion_calculator-basics)
• Plant needs 736 x 103 kilowatt hours per day (not enough)
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Other Renewable Options are at Blue Plains
• Methane from biosolids generate electricity that is not enough for the Blue Plains AWTP operations
(Need 736 x 103 kilowatt hours per day but it is able to
generate only 534 x 103 kilowatt hours per day )
• Other options more than methane or electricity is to invest in renewable energy source (e.g., wind, solar, hydropower and geothermal)
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Prediction of Carbon Dioxide (CO2) Credits
• 0.8 tons CO2 credits per dry ton biosolids
(Brown, S., H. Gough, and et al., Green Aspects of Biosolids Processing and Use 2009)
• 0.8 x 1,163 tons biosolids per day
• CO2 credits are 930 tons per day
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Financial Benefit from CO2 Credits
Market Volume (MtCO2) Value( US$ million)
RGGI 27.4 108.9
Transaction Volume and Value, Global Carbon Market, 2008
Source: Ecosystem Marketplace, New Carbon Finance
108.9/27.4 = $ 3.94 per ton CO2
• The Blue Plains AWTP
$3.94 x 930 tons per day = $ 3,692 per day
= $ 1.3 million per year
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Summary
• Biosolids from the Blue Plains AWTP is a significant renewable energy source. It has a high efficiency to generate methane and electricity
Methane is 57.4x103 cubic meters per day Electricity is 534.5x103 kilowatt hours per day
• CO2 credits is 930 tons CO2 per day • Financial benefit from CO2 credits is about $ 3,692 per day
• Methane for transportation grid
• Selling Electricity to Grid Electric Power
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Ongoing Work
• Build a multiobjective optimization model in order to make best decisions to:– minimize DCWASA’s CO2 footprint
– minimize energy usage– minimize costs– other considerations (as appropriate)
• Will consider both investment decisions as well as operational ones