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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
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)

the model rains developed by iiasa
The model: RAINSdeveloped by IIASA

Energy/agriculture

projections

Emission control

options

Emissions

Costs

Atmospheric dispersion

Environmental

targets

Environmental impacts

optimization based upon
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)
optimization in rains
Optimization in RAINS

Energy/agriculture

projections

Emission control

options

OPTIMIZATION

Emissions

Costs

Atmospheric dispersion

Environmental

targets

Environmental impacts

emission abatement cost curves
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
optimization in rains a systematic search for cost effective solutions
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
optimization in rains a mathematical optimization problem
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
optimization in rains the mathematical formulation
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

deposition targets d ij
Deposition targets dij
  • Deposition targets
  • ‘drive’ the optimization
  • ‘policy’ choice of the user
  • can be specified for each grid cell
example targets for the optimization
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
conclusions
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