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86025_3

86025_3. Fundamental of Energy Systems II. Energy Systems Constraints: Integration Demand - Supply. Physical: Matching form value Matching spatial scales Matching temporal scales Societal - Availability of: Capital Information Incentives Policy attention. Energy Constraints.

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86025_3

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  1. 86025_3 Fundamental of Energy Systems II Arnulf Grubler

  2. Energy Systems Constraints: Integration Demand - Supply Physical: • Matching form value • Matching spatial scales • Matching temporal scales Societal - Availability of: • Capital • Information • Incentives • Policy attention Arnulf Grubler

  3. Energy Constraints • Matching “form value”: need (and limits) of conversion (e.g. radiant→mechanical energy) • Spatial mismatch supply-demand: World trade in fuels >1000 Billion $ (2003 data); • Temporal mismatch supply-demand (load curves): Need for storage & interconnection (capital intensive) • Magnitude mismatch supply-demand: Power densities, e.g. renewables vs. urban energy use Arnulf Grubler

  4. Energy Constraints I: Space • Fossil fuels: Deposits determined by nature • Extremely uneven distribution of reserves: Oil<Coal<Gas • Transport costly: Electricity<LNG<Gas<Coal<Oil • Inventory (storage) minimization increases vulnerability (only 90 days oil use in strategic reserves) • Renewables: Land availability as major spatial constraint Arnulf Grubler

  5. http://www.bp.com/centres/energy2002/gas/trademovement.asp# Arnulf Grubler

  6. US – Gas Pipeline Transport Flows Arnulf Grubler

  7. World Oil Trade in 2004(net trade of crude and oil products) Source: BP Statistical Review of World energy 2005

  8. How Much Do Fuels Costs the World? • The power of “back-of-the envelope” calculations • World crude oil trade: 2.6 109 tons* • 1000 109 $* • World oil use: 3.8 Gtoe • World energy use: 10 Gtoe • World GDP: ~45 1012$* • Rough (upper) estimate is: ? * 2005 data from BP Stat. Review 2006 and IMF 2006using (high) oil prices: <10%;using avg. energy costs and long-term average oil prices: 3-5% of GWP

  9. Energy Constraints II: TimeWhy Electricity Load Curves Matter • Electricity can’t be stored at reasonable costs; storage of other energy forms also costly • Therefore: Electricity must be generated whenever demand arises • Therefore: Need enough installed generation capacity to meet peak demand (plus reserve margin), even though system peaks very rarely (few hrs/yr) • Result: Some plants run only a few hours per year (economics! efficiency!) • Peak load versus average load: Times 3 • Reserve margin: 10-30% of peak load • Fractality: Daily, weekly, monthly, yearly load curves Arnulf Grubler

  10. Cum. Annual Electricity Load Curveakin “load duration curve” (US) Pumped hydro, gas turbines Gas combined cycle, coal MEDIUM LOAD PLANTS Power demand Hydropower (rivers), nuclear, coal Arnulf Grubler

  11. Heat Load Curve of an Austrian Hotel with Electricity Cogeneration(“stacked” boilers due to inefficiency of low capacity utilization;Never design a heating system based on peak load!) x kWth electric boiler 50 kWth hours per year Arnulf Grubler

  12. Daily Load Curves: Tokyo Source: Mogouro et al., 2002 Arnulf Grubler

  13. Linking Space and Time in Tokyo: Power Density of Demand Source: Mouguro et al., 2002 Arnulf Grubler

  14. Tokyo – Electricity Demand vs. Solar Energy Supply kWh 100000 Electricity demand 10000 Solar radiation 1000 Solar radiation converted to electricity 100 10 km2 1 0 1000 2000 3000 Source: TEPCO & NIES, 2002

  15. Spatial Power Densities of Energy Production and Consumption Oil fields Coal fields Thermal power plants High-rises Supermarkets Cities Steel mills, Houses refineries Industry Flat plate collectors Photovoltaics Photovoltaics Photovoltaics Hydro Tidal Central solar towers Wind Photosynthesis Photosynthesis Source: Adapted from Smil 1991:243 Arnulf Grubler

  16. Energy Density Example I:Hambach Lignite Mine Germany Arnulf Grubler

  17. Large Scale Opencast Brown Coal Mining Germany New & West Havenfor scale comparison FORTUNAGARSDORF BERGHEIM NuclearResearchCentre HAMBACH INDEN Arnulf Grubler

  18. An IE Perspective on Hambach • The “1 TW hole” • 3000 billion tons lignite reserves= 1 BTCE = 1 TWyr = 30 EJ • 8500 ha mined between 1980-2040(all reclaimed) • Largest man-made machines in the world(240,000 m3/day bucket wheel excavators) 2004: 40 million tons lignite500 million tons overburden removed600 million tons water pumped1 ton of lignite (~2 bbls of oil) = 30 tons of material handling Arnulf Grubler

  19. Energy/Carbon Densities: Example II:C sequestered by fuel substitution vs. forest sinks and sources Substitution (bio for fossils) Source (deforestation) Sinks (afforestation) Source: Science 317(17 August 20907):902

  20. Power Densities II • Spatial mismatch between demand and supply requires imports (domestic+international) • >80% of world energy use in urban high demand density areas • Power density mismatch biggest for renewables (except large hydro) • Hence: Renewables best suited for niche markets: low population/energy density areas (rural), Arnulf Grubler

  21. Europe: Power Density of Demand (W/m2): Grey areas indicate where biomass or wind can satisfy local energy demand (< 0.5 W/m2) England: Energy demand footprint larger than country area

  22. Orders of Magnitude: 1 W/m2 upper energy yield of biomass/wind ~10 kWh/m2 resulting annual energy yield ~30 MJ/m2 ~300 GJ/ha ~10,000 liters/ha liquid fuel with 100% conversion efficiency ~1,000 gal/acre (for the non-metric inclined) ~10 toe/ha tons oil equivalent yield (max. yield, no losses!)~3 toe/ha realistic yield incl. conversion losses US transport energy use: ~600 Mtoe = 200 million ha = ~100% of all cropland World energy use (PE): ~10 Gtoe = 3000 million ha = 200% of cropland area, or 75% of forests

  23. The Economics of Land-use Conflicts:Bioenergy and Agricultural Crop Yields(typical, rounded values)

  24. Choice of Energy Systems and Technologies • Need to satisfy first all energy systems constraints • Need to satisfy demand for energy services rather than fuels • Economics not all (invisible costs, convenience, social visibility, etc.) • Choices available inverse of scale (family home, plant, vs. planet) • Analysis needs large system boundaries Arnulf Grubler

  25. Energy Chains and Analysis For MEMs: LCA Arnulf Grubler

  26. Energy Chain Analysis:Example of IIASA CO2DB • Broad coverage (end-use to extraction, ~2000 technologies) • Comprehensiveness (technological, economic, emissions characteristics) • Multiple entries (uncertainties, regional differences) • No single „best guess“ (reflecting dynamicsin time, process variation, heterogeneity) • Analysis (queries, energy chain analysis) Arnulf Grubler

  27. The Cost of Lighting$/k-lumen-yr Arnulf Grubler

  28. CO2 Emissions of Lighting(kg C/k-lumen-yr) 2 Cheapest and 2nd cheapest chains 3 4 6 1 5 Arnulf Grubler

  29. Energy Chain & LCA Analysis +Easy comparison at investment margin + Analytical simplicity + Data sharing + Good for project-specific analysis(GEF „additionality) + Imports can be considered • Representativeness of examples under proliferation of combinations (xn!) • Largely static analysis (what‘s the investment „margin“?) • Reconciliation of multiple criteria(costs, emissions) • System aspects: Diffusion potentials and constraints (capital, vintage structure, environment, relative shares of various chains) Arnulf Grubler

  30. I-O: Input-Output Analysis • Basically a matrix of monetary flows across sectors of an economy • Info: one unit of output of sector i needs how much ($) inputs from other sectors (j..n) • Based on detailed (but lagged) nationally reconciled sectorial statistics • Complemented by physical flows(e.g. energy, CO2 emissions) Arnulf Grubler

  31. US- Energy per $ Value Added(TJ per Million $, energy embodiment, 1992 I-O data)Source: Carnegie Mellon Univ. www.eiolca.net Direct energy Indirect energy Note product and value orientation: Energy embodied in car vs. total energy use over lifetime of car Energy $ per VA $: industry vs. services (energy price differences) Arnulf Grubler

  32. I-O Tables for Energy and Environmental Analysis + Comprehensive national accounting + Widely available (mostly in OECD however) + Basically only data source for “indirect” energy and “rucksack” environmental impacts (=things happening outside the sector of consideration but linked to it) + Possibility to combine with physical I-O info • Static and often delayed (-5 to -10 yrs) snapshot • Average sectorial picture (difference to marginal investments) • Little end-use (consumption) detail • Constrained by national border systems boundary Arnulf Grubler

  33. B-U Engineering Modeling • Representation of conversion technologies linking I-O • Simulation or optimization (LP) based • Dynamic (back-and forecasting) • LPs: Clear, simple decision rule: (discounted) cost minimization under constraints • Trade explicitly considered • Data rich Arnulf Grubler

  34. Energy Flows in MESSAGE Model 1990 --2020 Arnulf Grubler

  35. B-U Engineering Models +technology detail + multi-criteria analysis + environmental constraints explicitly considered + dynamic, systems view • Extremely data intensive • Decision rule simplistic(global cost minimization) • Consumer choices poorly modeled(“rational choice” assumed) • Linkage to other sectors: only captured if coupled with macro-economic models (complex) Arnulf Grubler

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