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Determining energy and climate market policy using multiobjective programs with equilibrium constraints.

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Title: Determining energy and climate market policy using multiobjective programs with equilibrium constraints.
Authors: Siddiqui, Sauleh1,2 siddiqui@jhu.edu, Christensen, Adam3 adam.christensen@jhu.edu
Source: Energy. Jan2016, Vol. 94, p316-325. 10p.
Subjects: Energy policy, Climate change, Equilibrium, Renewable energy sources, Energy industries
Abstract: Energy and climate market policy is inherently multiobjective and multilevel, in that desired choices often conflict and are made at a higher level than influenced actors. Analyzing tradeoff between reducing emissions and keeping fuel prices low, while seeking compromise among producers, traders, and consumers is the crux of the policy problem. This paper aims to address this issue by combining multiobjective optimization problems, which allow the study of tradeoff between choices, with equilibrium problems that model the networks and players over which these policies are chosen, to produce a formulation called a Multiobjective Program with Equilibrium Constraints. We apply this formulation to the United States renewable fuel market to help understand why it has been so difficult in releasing the 2014 mandate for the RFS (Renewable Fuel Standard). The RFS ensures that a minimum volume of renewable fuel is included in transportation fuel sold in the United States. Determining the RFS volume requirements involves anticipating market reaction as well as balancing policy objectives. We provide policy alternatives to aid in setting these volume obligations that are applicable to a wide variety of climate and energy market settings and explain why the RFS is not an optimal policy for reducing emissions. [ABSTRACT FROM AUTHOR]
Copyright of Energy is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: Determining energy and climate market policy using multiobjective programs with equilibrium constraints.
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  Data: <searchLink fieldCode="AR" term="%22Siddiqui%2C+Sauleh%22">Siddiqui, Sauleh</searchLink><relatesTo>1,2</relatesTo><i> siddiqui@jhu.edu</i><br /><searchLink fieldCode="AR" term="%22Christensen%2C+Adam%22">Christensen, Adam</searchLink><relatesTo>3</relatesTo><i> adam.christensen@jhu.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Energy%22">Energy</searchLink>. Jan2016, Vol. 94, p316-325. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Energy+policy%22">Energy policy</searchLink><br /><searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br /><searchLink fieldCode="DE" term="%22Equilibrium%22">Equilibrium</searchLink><br /><searchLink fieldCode="DE" term="%22Renewable+energy+sources%22">Renewable energy sources</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+industries%22">Energy industries</searchLink>
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  Data: Energy and climate market policy is inherently multiobjective and multilevel, in that desired choices often conflict and are made at a higher level than influenced actors. Analyzing tradeoff between reducing emissions and keeping fuel prices low, while seeking compromise among producers, traders, and consumers is the crux of the policy problem. This paper aims to address this issue by combining multiobjective optimization problems, which allow the study of tradeoff between choices, with equilibrium problems that model the networks and players over which these policies are chosen, to produce a formulation called a Multiobjective Program with Equilibrium Constraints. We apply this formulation to the United States renewable fuel market to help understand why it has been so difficult in releasing the 2014 mandate for the RFS (Renewable Fuel Standard). The RFS ensures that a minimum volume of renewable fuel is included in transportation fuel sold in the United States. Determining the RFS volume requirements involves anticipating market reaction as well as balancing policy objectives. We provide policy alternatives to aid in setting these volume obligations that are applicable to a wide variety of climate and energy market settings and explain why the RFS is not an optimal policy for reducing emissions. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Group: Ab
  Data: <i>Copyright of Energy is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.energy.2015.11.002
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      – Code: eng
        Text: English
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        PageCount: 10
        StartPage: 316
    Subjects:
      – SubjectFull: Energy policy
        Type: general
      – SubjectFull: Climate change
        Type: general
      – SubjectFull: Equilibrium
        Type: general
      – SubjectFull: Renewable energy sources
        Type: general
      – SubjectFull: Energy industries
        Type: general
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      – TitleFull: Determining energy and climate market policy using multiobjective programs with equilibrium constraints.
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              Text: Jan2016
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              Value: 94
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