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Dynamic Carbon-Constrained EPEC Model for Strategic Generation Investment Incentives with the Aim of Reducing CO 2 Emissions

Author

Listed:
  • Jaber Valinejad

    (Bradley Department of Electrical Computer Engineering, Virginia Tech, Northern Virginia Center, Greater Washington, D.C., VA 22043, USA)

  • Mousa Marzband

    (Department of Maths, Physics and Electrical Engineering, Faculty of Engineering and Environment, Northumbria University Newcastle, Newcastle upon Tyne NE1 8ST, UK)

  • Michael Elsdon

    (Department of Maths, Physics and Electrical Engineering, Faculty of Engineering and Environment, Northumbria University Newcastle, Newcastle upon Tyne NE1 8ST, UK)

  • Ameena Saad Al-Sumaiti

    (Advanced Power and Energy Center, Electrical Engineering and Computer Science, Khalifa University, P.O. Box 127788, Abu Dhabi, UAE)

  • Taghi Barforoushi

    (Department of Electrical and Computer Engineering, Babol Noshirvaini University of Technology, Babol 4714871167, Iran)

Abstract

According to the European Union Emissions Trading Scheme, energy system planners are encouraged to consider the effects of greenhouse gases such as CO 2 in their short-term and long-term planning. A decrease in the carbon emissions produced by the power plant will result in a tax decrease. In view of this, the Dynamic carbon-constrained Equilibrium programming equilibrium constraints (DCC-EPEC) Framework is suggested to explore the effects of distinct market models on generation development planning (GEP) on electricity markets over a multi-period horizon. The investment incentives included in our model are the firm contract and capacity payment. The investment issue, which is regarded as a set of dominant producers in the oligopolistic market, is developed as an EPEC optimization problem to reduce carbon emissions. In the suggested DCC-EPEC model, the sum of the carbon emission tax and true social welfare are assumed as the objective function. Investment decisions and the strategic behavior of producers are included at the first level so as to maximize the overall profit of the investor over the scheduling period. The second-level issue is market-clearing, which is resolved by an independent system operator (ISO) to maximize social welfare. A real power network, as a case study, is provided to assess the suggested carbon-constrained EPEC framework. Simulations indicate that firm contracts and capacity payments can initiate the capacity expansion of different technologies to improve the long-term stability of the electricity market.

Suggested Citation

  • Jaber Valinejad & Mousa Marzband & Michael Elsdon & Ameena Saad Al-Sumaiti & Taghi Barforoushi, 2019. "Dynamic Carbon-Constrained EPEC Model for Strategic Generation Investment Incentives with the Aim of Reducing CO 2 Emissions," Energies, MDPI, vol. 12(24), pages 1-35, December.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4813-:d:298980
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    References listed on IDEAS

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    1. Taheri, S. Saeid & Kazempour, Jalal & Seyedshenava, Seyedjalal, 2017. "Transmission expansion in an oligopoly considering generation investment equilibrium," Energy Economics, Elsevier, vol. 64(C), pages 55-62.
    2. Jaber Valinejad & Mousa Marzband & Mudathir Funsho Akorede & Ian D Elliott & Radu Godina & João Carlos de Oliveira Matias & Edris Pouresmaeil, 2018. "Long-Term Decision on Wind Investment with Considering Different Load Ranges of Power Plant for Sustainable Electricity Energy Market," Sustainability, MDPI, vol. 10(10), pages 1-19, October.
    3. Antonio J. Conejo & Miguel Carrión & Juan M. Morales, 2010. "Decision Making Under Uncertainty in Electricity Markets," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7421-1, April.
    4. S. Siddiqui & S. Gabriel, 2013. "An SOS1-Based Approach for Solving MPECs with a Natural Gas Market Application," Networks and Spatial Economics, Springer, vol. 13(2), pages 205-227, June.
    5. Marzband, Mousa & Azarinejadian, Fatemeh & Savaghebi, Mehdi & Pouresmaeil, Edris & Guerrero, Josep M. & Lightbody, Gordon, 2018. "Smart transactive energy framework in grid-connected multiple home microgrids under independent and coalition operations," Renewable Energy, Elsevier, vol. 126(C), pages 95-106.
    6. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
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