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A mid-term, market-based power systems planning model

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  • Koltsaklis, Nikolaos E.
  • Dagoumas, Athanasios S.
  • Georgiadis, Michael C.
  • Papaioannou, George
  • Dikaiakos, Christos

Abstract

This paper presents a generic Mixed Integer Linear Programming (MILP) model that integrates a Mid-term Energy Planning (MEP) model, which implements generation and transmission system planning at a yearly level, with a Unit Commitment (UC) model, which performs the simulation of the Day-Ahead Electricity Market. The applicability of the proposed model is illustrated in a case study of the Greek interconnected power system. The aim is to evaluate a critical project in the Ten Year Network Development Plan (TYNDP) of the Independent Power Transmission System Operator S.A. (ADMIE), namely the electric interconnection of the Crete Island with the mainland electric system. The proposed modeling framework identifies the implementation (or not) of the interconnection of the Crete Island with the mainland electric system, as well as the optimum interconnection capacity. It also quantifies the effects on the Day-Ahead electricity market and on the energy mix. The paper demonstrates that the model can provide useful insights into the strategic and challenging decisions to be determined by investors and/or policy makers at a national and/or regional level, by providing the optimal energy roadmap and management, as well as clear price signals on critical energy projects under real operating and design constraints.

Suggested Citation

  • Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S. & Georgiadis, Michael C. & Papaioannou, George & Dikaiakos, Christos, 2016. "A mid-term, market-based power systems planning model," Applied Energy, Elsevier, vol. 179(C), pages 17-35.
    • Handle: RePEc:eee:appene:v:179:y:2016:i:c:p:17-35
    DOI: 10.1016/j.apenergy.2016.06.070
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    Cited by:

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    3. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "Incorporating unit commitment aspects to the European electricity markets algorithm: An optimization model for the joint clearing of energy and reserve markets," Applied Energy, Elsevier, vol. 231(C), pages 235-258.
    4. Michael L. Polemis, 2018. "A mixed integer linear programming model to regulate the electricity sector," Letters in Spatial and Resource Sciences, Springer, vol. 11(2), pages 183-208, July.
    5. Scott, Ian J. & Carvalho, Pedro M.S. & Botterud, Audun & Silva, Carlos A., 2019. "Clustering representative days for power systems generation expansion planning: Capturing the effects of variable renewables and energy storage," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
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    8. Koltsaklis, Nikolaos E. & Nazos, Konstantinos, 2017. "A stochastic MILP energy planning model incorporating power market dynamics," Applied Energy, Elsevier, vol. 205(C), pages 1364-1383.
    9. Vrionis, Constantinos & Tsalavoutis, Vasilios & Tolis, Athanasios, 2020. "A Generation Expansion Planning model for integrating high shares of renewable energy: A Meta-Model Assisted Evolutionary Algorithm approach," Applied Energy, Elsevier, vol. 259(C).
    10. Barrera-Santana, J. & Sioshansi, Ramteen, 2023. "An optimization framework for capacity planning of island electricity systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    11. Maria Dicorato & Michele Trovato & Chiara Vergine & Corrado Gadaleta & Benedetto Aluisio & Giuseppe Forte, 2020. "Extended Flow-Based Security Assessment for Real-Sized Transmission Network Planning," Energies, MDPI, vol. 13(13), pages 1-19, July.
    12. Ravnik, J. & Hriberšek, M., 2019. "A method for natural gas forecasting and preliminary allocation based on unique standard natural gas consumption profiles," Energy, Elsevier, vol. 180(C), pages 149-162.
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    14. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S. & Panapakidis, Ioannis P., 2017. "Impact of the penetration of renewables on flexibility needs," Energy Policy, Elsevier, vol. 109(C), pages 360-369.
    15. Allard, Stéphane & Debusschere, Vincent & Mima, Silvana & Quoc, Tuan Tran & Hadjsaid, Nouredine & Criqui, Patrick, 2020. "Considering distribution grids and local flexibilities in the prospective development of the European power system by 2050," Applied Energy, Elsevier, vol. 270(C).
    16. Goudarzi, Arman & Swanson, Andrew G. & Van Coller, John & Siano, Pierluigi, 2017. "Smart real-time scheduling of generating units in an electricity market considering environmental aspects and physical constraints of generators," Applied Energy, Elsevier, vol. 189(C), pages 667-696.
    17. Stéphane Allard & Vincent Debusschere & Silvana Mima & Tuan Tran Quoc & Nouredine Hadjsaid & Patrick Criqui, 2020. "Considering distribution grids and local flexibilities in the prospective development of the European power system by 2050," Post-Print hal-03133109, HAL.
    18. Panapakidis, Ioannis P. & Dagoumas, Athanasios S., 2017. "Day-ahead natural gas demand forecasting based on the combination of wavelet transform and ANFIS/genetic algorithm/neural network model," Energy, Elsevier, vol. 118(C), pages 231-245.
    19. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    20. Martha N. Acosta & Francisco Gonzalez-Longatt & Juan Manuel Roldan-Fernandez & Manuel Burgos-Payan, 2021. "A Coordinated Control of Offshore Wind Power and BESS to Provide Power System Flexibility," Energies, MDPI, vol. 14(15), pages 1-17, July.
    21. Nikolaos Koltsaklis & Athanasios Dagoumas, 2018. "Policy Implications of Power Exchanges on Operational Scheduling: Evaluating EUPHEMIA’s Market Products in Case of Greece," Energies, MDPI, vol. 11(10), pages 1-26, October.
    22. Dagoumas, Athanasios S. & Koltsaklis, Nikolasos E. & Panapakidis, Ioannis P., 2017. "An integrated model for risk management in electricity trade," Energy, Elsevier, vol. 124(C), pages 350-363.
    23. Liu, Jinhui & Xu, Zhanbo & Wu, Jiang & Liu, Kun & Guan, Xiaohong, 2021. "Optimal planning of distributed hydrogen-based multi-energy systems," Applied Energy, Elsevier, vol. 281(C).
    24. Tang, Bao-Jun & Li, Ru & Li, Xiao-Yi & Chen, Hao, 2017. "An optimal production planning model of coal-fired power industry in China: Considering the process of closing down inefficient units and developing CCS technologies," Applied Energy, Elsevier, vol. 206(C), pages 519-530.
    25. Nikolaos E. Koltsaklis & Athanasios S. Dagoumas, 2021. "A power system scheduling model with carbon intensity and ramping capacity constraints," Operational Research, Springer, vol. 21(1), pages 647-687, March.

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