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A robust optimisation approach for identifying multi-state collaborations to reduce CO2 emissions
by
McGarvey, Ronald G.
, Aguilar, Francisco X.
, Dundar, Bayram
in
carbon
/ coal
/ compliance
/ electricity
/ Energy
/ environmental studies
/ forestry
/ operations research
/ ORIGINAL ARTICLE
/ woody biomass
2019
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A robust optimisation approach for identifying multi-state collaborations to reduce CO2 emissions
by
McGarvey, Ronald G.
, Aguilar, Francisco X.
, Dundar, Bayram
in
carbon
/ coal
/ compliance
/ electricity
/ Energy
/ environmental studies
/ forestry
/ operations research
/ ORIGINAL ARTICLE
/ woody biomass
2019
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Do you wish to request the book?
A robust optimisation approach for identifying multi-state collaborations to reduce CO2 emissions
by
McGarvey, Ronald G.
, Aguilar, Francisco X.
, Dundar, Bayram
in
carbon
/ coal
/ compliance
/ electricity
/ Energy
/ environmental studies
/ forestry
/ operations research
/ ORIGINAL ARTICLE
/ woody biomass
2019
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A robust optimisation approach for identifying multi-state collaborations to reduce CO2 emissions
Journal Article
A robust optimisation approach for identifying multi-state collaborations to reduce CO2 emissions
2019
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Overview
Co-firing woody biomass with coal is one approach electricity providers can take to achieve emissions reductions without significantly modifying their existing infrastructure. An important aspect of EPA recommendations for reducing carbon emissions from coal-fired power plants is an allowance for states to enter into multi-state compliance partnerships. This study presents mixed integer linear programming models to identify min-cost approaches for reducing carbon emissions via biomass co-firing subject to spatially-explicit biomass availability constraints, utilising a robust optimisation approach to address uncertainties in costs and emission rates. We apply these models to a set of 18 states in the Northern US, to demonstrate how one state could identify efficient sets of multi-state collaborators.
Publisher
Taylor & Francis,Taylor & Francis, Ltd
Subject
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