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International Institute for Applied Systems Analysis (IIASA)

International Institute for Applied Systems Analysis (IIASA). RAINS-Asia: A Tool for Optimization Analysis of the Acidification Problem in Asia while Taking into Account the Potential for Use of Renewable Energy. M. Amann, J. Cofala, F. Gyarfas, W. Schöpp (IIASA)

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International Institute for Applied Systems Analysis (IIASA)

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  1. International Institute for Applied Systems Analysis (IIASA) • RAINS-Asia: • A Tool for Optimization Analysis of the Acidification Problem in Asia while Taking into Account the Potential for Use of Renewable Energy M. Amann, J. Cofala, F. Gyarfas, W. Schöpp (IIASA) C. Boudri, L. Hordijk, C. Kroeze (Wageningen University, NL) Li Junfen, Dai Lin (Energy Research Institute, Beijing) L. Srivastava, T.S. Panwar (Tata Energy Research Institute, Delhi)

  2. The model: RAINSdeveloped by IIASA Energy/agriculture projections Emission control options Emissions Costs Atmospheric dispersion Environmental targets Environmental impacts

  3. Optimization based upon ... • Some sources are more strongly linked than others via the atmosphere to sensitive receptors (as indicated by the source-receptor relationships) • Some sources are cheaper to control than others(as indicated by the cost curves)

  4. Optimization in RAINS Energy/agriculture projections Emission control options OPTIMIZATION Emissions Costs Atmospheric dispersion Environmental targets Environmental impacts

  5. Emission abatement cost curves • Estimate marginal costs for all available emission control options • Rank available options according to their marginal cost • Select an energy projection, calculate uncontrolled (or current legislation) emissions • List emission reduction potentials and costs, starting from the ‘uncontrolled’ case

  6. An example cost curve for SO2

  7. Optimization in RAINS: A systematic search for cost-effective solutions • Goal (objective) of the optimization: • For a given set of environmental targets (e.g., maximum S deposition) find the least-cost set of measures • Result (solution): • Least-cost set of emission controls/emission ceilings by • region/province • economic sector • LPS/area source

  8. Optimization in RAINS: A mathematical optimization problem • Objective function: • Minimize total SO2 control costs in the whole region/country • subject to: • so that user-specified constraints/limits on sulfur exposure/ deposition are met in the whole region • Decision variables/outcome: • the SO2emission controls for each source (province/LPS) within the bounds given by the cost curves or imposed by the user

  9. Optimization in RAINS: The mathematical formulation c …... control costs i …... source region j …... receptor point ei …... SO2 emissions tij …... atmospheric dispersion coefficient bgj …. background deposition dj …... deposition target ici  min subject to ci = fi(ei) i(ei.tij)+bgj  dj

  10. Deposition targets dij • Deposition targets • ‘drive’ the optimization • ‘policy’ choice of the user • can be specified for each grid cell

  11. Example targets for the optimization • In the year 2020 • Case A: limit total emissions in each region to the levels of 2000/1995/1990 • Case B:limit sulfur deposition in each grid cell to the levels experienced in 2000/1995/1990 • Case C:limit (harmful) excess sulfur deposition in each grid cell to the levels experienced in 2000/1995/1990

  12. Cost-savings through targeted (optimized) emission controls

  13. Cost savings through renewable energy(for Case B)

  14. Conclusions • RAINS-Asia optimization tool now available • Enables systematic search for cost-effective emission controls to achieve user-defined environmental targets • Optimized solutions can cut costs by 50% while maintaining same environmental benefits • Renewable energy offers additional cost-saving potential

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