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Dynamics Model of a Net-Zero Neighborhood Brandon Davis Alabama Agricultural and Mechanical University Dr. Gilbert Weigand Computing and Computational.

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Presentation on theme: "Dynamics Model of a Net-Zero Neighborhood Brandon Davis Alabama Agricultural and Mechanical University Dr. Gilbert Weigand Computing and Computational."— Presentation transcript:

1 Dynamics Model of a Net-Zero Neighborhood Brandon Davis Alabama Agricultural and Mechanical University Dr. Gilbert Weigand Computing and Computational Science Directorate August 2009

2 2Managed by UT-Battelle for the U.S. Department of Energy Overview Background Methods Results Conclusions Future work

3 3Managed by UT-Battelle for the U.S. Department of Energy Background America is – addicted to foreign oil In 1970, imported 24% of oil currently nearly 70% and rising Largest wealth transfer ever known to world underway from west to Middle East – losing jobs to foreign competitors Since 1999 25% of manufacturing jobs lost to foreign competition* Between 2001 and 2003 (that’s 2 years), Goldman Sachs and Company estimates that 20% of technology jobs have moved overseas, including sophisticated design and innovation jobs – Not leading in the global energy and climate debate Between 1990 and 2005 U.S. CO 2 emissions rose by 1 billion tons (GT) to 7.2 GT/yr Between 2005 and 2030, additional growth of CO 2 emissions will be 2.5 GT** (35%) U.S. faces growing energy needs and costs in all sectors: residential, commercial, industrial, and Transportation U.S. faces progressive environmental policy discussion for future, Cap and Trade, higher CAFÉ standards, renewables and conservation incentives, climate protocols, and NIMBY and BANANA*** * Apollo Alliance, www.apolloalliance.orgwww.apolloalliance.org ** U.S Department of Energy, Energy Information Agency *** NIMBY: Not In My Back Yard; BANANA: Build Absolutely Nothing Anywhere Near Anything 3

4 4Managed by UT-Battelle for the U.S. Department of Energy U.S. energy consumption flow Renewables and Nuclear 5.9% Renewables 8.1% Nuclear Fossil 22.9% coal (0% imported) 40.1% oil (>60% imported) 22.7% gas (16% imported) Electricity generation 29% renewables & nuclear 70% fossil (coal & gas only) 14% 86% Lost energy (from electricity generation, transmission, and distribution) 27% 38% 20% 24% 28% Industrial 14% electricity 33% gas 39% oil Transportation 99% oil % of Total Energy Sources = Energy sources Energy consumption 2005 U.S. Energy Flows from: Lawrence Livermore National Laboratory (Total U.S. energy sources = approximately 100 Quadrillion BTUs 50 million railroad cars full of coal or 50 billion gas-tanks full of gasoline) Residential and Commercial 45% electricity 41% gas 12% oil 4

5 5Managed by UT-Battelle for the U.S. Department of Energy Take transportation off the gasoline grid And Take residential off the grid Net-zero neighborhood Bio = biologically derived energy generation Industrial Scale Wind ESP Solar 5 Net-Zero Neighborhood Model Battery grid Industrial scale-solar grid Cloud

6 6Managed by UT-Battelle for the U.S. Department of Energy Methodology Use Stella simulation software to create a dynamic model Represents energy consumption of population of 300,000 Prove Net-Zero neighborhood trend works Show lower CO 2 emissions Show decrease in gasoline consumption

7 7Managed by UT-Battelle for the U.S. Department of Energy Net-Zero Neighborhoods and the Smart Grid Net-Zero Commercial and ESPs Fossil Coal, Oil & Gas Nuclear Electric transportation National Grid Hydro Solar Wind Geo- thermal National Grid E-Storage and local smart grid Other E-Storage and local smart grid Net-Zero Residential and ESPs Central power 500-mile batteries Local Gen Electric transportation Energy storage Incorporate the energy storage (e.g., batteries) into local smart grid Electric transportation becomes point to point mass transit Net-zero neighborhoods use local generation Energy service providers net-zero neighborhoods along with providing local generation 7

8 8Managed by UT-Battelle for the U.S. Department of Energy Governing Equations Model as an initial value problem dE k = f i dt and solve using Euler’s method Euler’s equation first terms of Taylor series expansion E k = energy f i = generation t i = time 24 hour time period

9 9Managed by UT-Battelle for the U.S. Department of Energy Net-Zero Neighborhood Simulation Map Model Net-Zero Commercial & ESPs Fos sil Co al, Oil & Ga s Nuclear Electric Transportation National Grid Hydro Solar Wind Geo- thermal National Grid E-Storage & Local Smart Grid Other E-Storage & Local Smart Grid Net-Zero Residential & ESPs Ce ntr al Po we r 500-Mile Batteries Local Gen Electric Transportation Energy Storage Net-zero neighborhood EV Commercial ESP Residential Nuclear Coal Oil Gas Electricity Storage Hybrid NZN = Local Storage + Local Generation + Electrify Transportation NZN integrates seamlessly with other energy generation plans and the national grid Stella model

10 10Managed by UT-Battelle for the U.S. Department of Energy Stella model

11 11Managed by UT-Battelle for the U.S. Department of Energy Results Storage Consumption

12 12Managed by UT-Battelle for the U.S. Department of Energy Simulation Results

13 13Managed by UT-Battelle for the U.S. Department of Energy Discussion of Results Comparison between 2010 and 2030 were analyzed account 50 percent net-zero generation and 50 percent transportation Local storage switches all energy generation forms, e.g., solar and wind, into base load capacity At 50% market penetration – NZN reduces CO 2 emissions by more than 50% – NZN can reduce oil imports by as much as 50%

14 14Managed by UT-Battelle for the U.S. Department of Energy Conclusion NZN effectively reduces U.S.: – CO 2 emissions and oil imports – creates U.S. jobs in NZN locals – national environmental sustainability goals – energy security goals

15 15Managed by UT-Battelle for the U.S. Department of Energy Future Work Develop more comprehensive model to include time zone, seasonal, and regional affects, and multiple year Investigate specific R&D options for 500-mile battery to electrify transportation and 50% efficient solar cells

16 16Managed by UT-Battelle for the U.S. Department of Energy Acknowledgements Dr. Gilbert Weigand, Debbie McCoy, Rashida Askia, Dr. Z.T. Deng, Alabama A&M University Office of science Oak Ridge National Laboratory Department of Energy

17 17Managed by UT-Battelle for the U.S. Department of Energy Questions


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