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Long-Term Decision on Wind Investment with Considering Different Load Ranges of Power Plant for Sustainable Electricity Energy Market

Author

Listed:
  • Jaber Valinejad

    (Bradley Department of Electrical and Computer Engineering, Virginia Tech, Northern Virginia Center, Falls Church, VA 24043, USA)

  • Mousa Marzband

    (Department of Physics and Electrical Engineering, Faculty of Engineering and Environment, Northumbria University Newcastle, Newcastle upon Tyne NE18ST, UK
    Department of Electrical Engineering, Lahijan Branch, Islamic Azad University, Lahijan 4416939515, Iran)

  • Mudathir Funsho Akorede

    (Department of Electrical & Electronics Engineering, Faculty of Engineering and Technology, University of Ilorin, P.M.B. 1515, Ilorin 240003, Nigeria)

  • Ian D Elliott

    (Department of Physics and Electrical Engineering, Faculty of Engineering and Environment, Northumbria University Newcastle, Newcastle upon Tyne NE18ST, UK)

  • Radu Godina

    (Centre for Aerospace Science and Technologies—Department of Electromechanical Engineering, University of Beira Interior, 6201-001 Covilhã, Portugal)

  • João Carlos de Oliveira Matias

    (DEGEIT—Department of Economics, Management, Industrial Engineering and Tourism, University of Aveiro, 3810-193 Aveiro, Portugal
    GOVCOPP—Research Unit on Governance, Competitiveness and Public Policies, University of Aveiro, 3810-193 Aveiro, Portugal)

  • Edris Pouresmaeil

    (Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland)

Abstract

The aim of this paper is to provide a bi-level model for the expansion planning on wind investment while considering different load ranges of power plants in power systems at a multi-stage horizon. Different technologies include base load units, such as thermal and water units, and peak load units such as gas turbine. In this model, subsidies are considered as a means to encourage investment in wind turbines. In order that the uncertainties related to demand and the wind turbine can be taken into consideration, these effects are modelled using a variety of scenarios. In addition, the load demand is characterized by a certain number of demand blocks. The first-level relates to the issue of investment in different load ranges of power plants with a view to maximizing the investment profit whilst the second level is related to the market-clearing where the priority is to maximize the social welfare benefits. The bi-level optimization problem is then converted to a dynamic stochastic mathematical algorithm with equilibrium constraint (MPEC) and represented as a mixed integer linear program (MILP) after linearization. The proposed framework is examined on a real transmission network. Simulation results confirm that the proposed framework can be a useful tool for analyzing the investments different load ranges of power plants on long-term strategic decision-making.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3811-:d:177291
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    References listed on IDEAS

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    9. 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.
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