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A simplified optimization model to short-term electricity planning

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  • Pereira, Sérgio
  • Ferreira, Paula
  • Vaz, A.I.F.

Abstract

Short-term optimization models, usually applied to traditional problems like UC (unit commitment) and economic dispatch problem, are essential tools for the planning and operation of power systems. However, the large number of variables and restrictions, necessary for a good and more accurate representation of any electricity system, require high computational resources, frequently resulting in high computation times. This study proposes a simplified approach of a model for the electricity planning of power plants allocation based on the available resources. The model resources to quadratic penalty functions and avoid on/off binary variables. The approach is then supported on a non-linear optimization model able to solve this electricity planning problem in shorter computation times, with solutions close to the ones obtained with more complex models. The model is fully described and tested under different scenarios of an electricity system comprising thermal, wind, and hydropower plants. The results were compared to the ones obtained with a more complex model, analysing the main differences obtained for cost, CO2 emissions and of wind power impacts on this electricity system. The most remarkable advantage of the simplified model comes from the significant reduction on computational time needed for state-of-the-art optimization solvers to provide an optimal solution, comparatively to mixed integer models.

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  • Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2015. "A simplified optimization model to short-term electricity planning," Energy, Elsevier, vol. 93(P2), pages 2126-2135.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:2126-2135
    DOI: 10.1016/j.energy.2015.10.040
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    References listed on IDEAS

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    1. Georgopoulou, Chariklia A. & Giannakoglou, Kyriakos C., 2009. "Two-level, two-objective evolutionary algorithms for solving unit commitment problems," Applied Energy, Elsevier, vol. 86(7-8), pages 1229-1239, July.
    2. Wang, Jiadong & Wang, Jianhui & Liu, Cong & Ruiz, Juan P., 2013. "Stochastic unit commitment with sub-hourly dispatch constraints," Applied Energy, Elsevier, vol. 105(C), pages 418-422.
    3. Troy, Niamh & Denny, Eleanor & O'Malley, Mark, 2010. "Base-load cycling on a system with significant wind penetration," MPRA Paper 34848, University Library of Munich, Germany.
    4. Hobbs, Benjamin F., 1995. "Optimization methods for electric utility resource planning," European Journal of Operational Research, Elsevier, vol. 83(1), pages 1-20, May.
    5. Lund, H. & Münster, E., 2003. "Management of surplus electricity-production from a fluctuating renewable-energy source," Applied Energy, Elsevier, vol. 76(1-3), pages 65-74, September.
    6. Liu, Wen & Lund, Henrik & Mathiesen, Brian Vad, 2011. "Large-scale integration of wind power into the existing Chinese energy system," Energy, Elsevier, vol. 36(8), pages 4753-4760.
    7. Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2014. "Short-term electricity planning with increase wind capacity," Energy, Elsevier, vol. 69(C), pages 12-22.
    8. Gutiérrez-Martín, F. & Da Silva-Álvarez, R.A. & Montoro-Pintado, P., 2013. "Effects of wind intermittency on reduction of CO2 emissions: The case of the Spanish power system," Energy, Elsevier, vol. 61(C), pages 108-117.
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    2. Wang, Xianxun & Mei, Yadong & Kong, Yanjun & Lin, Yuru & Wang, Hao, 2017. "Improved multi-objective model and analysis of the coordinated operation of a hydro-wind-photovoltaic system," Energy, Elsevier, vol. 134(C), pages 813-839.
    3. Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2017. "Generation expansion planning with high share of renewables of variable output," Applied Energy, Elsevier, vol. 190(C), pages 1275-1288.
    4. Morales-España, Germán & Ramírez-Elizondo, Laura & Hobbs, Benjamin F., 2017. "Hidden power system inflexibilities imposed by traditional unit commitment formulations," Applied Energy, Elsevier, vol. 191(C), pages 223-238.
    5. Min Xie & Yuxin Du & Peijun Cheng & Wei Wei & Mingbo Liu, 2019. "A Cross-Entropy-Based Hybrid Membrane Computing Method for Power System Unit Commitment Problems," Energies, MDPI, vol. 12(3), pages 1-18, February.

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