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Optimal non-anticipative scenarios for nonlinear hydro-thermal power systems

Author

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  • Periçaro, Gislaine A.
  • Karas, Elizabeth W.
  • Gonzaga, Clóvis C.
  • Marcílio, Débora C.
  • Oening, Ana Paula
  • Matioli, Luiz Carlos
  • Detzel, Daniel H.M.
  • de Geus, Klaus
  • Bessa, Marcelo R.

Abstract

The long-term operation of hydro-thermal power generation systems is modeled by a large-scale stochastic optimization problem that includes nonlinear constraints due to the head computation in hydroelectric plants. We do a detailed development of the problem model and state it by a non-anticipative scenario analysis, leading to a large-scale nonlinear programming problem. This is solved by a filter algorithm with sequential quadratic programming iterations that minimize quadratic Lagrangian approximations using exact hessians in L∞ trust regions. The method is applied to the long-term planning of the Brazilian system, with over 100 hydroelectric and 50 thermoelectric plants, distributed in 5 interconnected subsystems. This problem with 50 synthetically generated inflow scenarios and a horizon of 60 months, amounting to about one million variables and 15000 nonlinear constraints was solved by the filter algorithm in a standard 2016 notebook computer in 10 h of CPU.

Suggested Citation

  • Periçaro, Gislaine A. & Karas, Elizabeth W. & Gonzaga, Clóvis C. & Marcílio, Débora C. & Oening, Ana Paula & Matioli, Luiz Carlos & Detzel, Daniel H.M. & de Geus, Klaus & Bessa, Marcelo R., 2020. "Optimal non-anticipative scenarios for nonlinear hydro-thermal power systems," Applied Mathematics and Computation, Elsevier, vol. 387(C).
    • Handle: RePEc:eee:apmaco:v:387:y:2020:i:c:s0096300319308124
    DOI: 10.1016/j.amc.2019.124820
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    References listed on IDEAS

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    1. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    2. Fredo, Guilherme Luiz Minetto & Finardi, Erlon Cristian & de Matos, Vitor Luiz, 2019. "Assessing solution quality and computational performance in the long-term generation scheduling problem considering different hydro production function approaches," Renewable Energy, Elsevier, vol. 131(C), pages 45-54.
    3. Guigues, Vincent & Sagastizábal, Claudia, 2012. "The value of rolling-horizon policies for risk-averse hydro-thermal planning," European Journal of Operational Research, Elsevier, vol. 217(1), pages 129-140.
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    Cited by:

    1. Jia Chen, 2021. "Long-Term Joint Operation of Cascade Reservoirs Using Enhanced Progressive Optimality Algorithm and Dynamic Programming Hybrid Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2265-2279, May.
    2. Sun, Lu & Xu, Qingshan & Song, Yun, 2022. "Game-theoretic genetic-priced optimization of multiple microgrids under uncertainties," Applied Mathematics and Computation, Elsevier, vol. 426(C).
    3. Kun Yang & Kan Yang, 2021. "Short-Term Hydro Generation Scheduling of the Three Gorges Hydropower Station Using Improver Binary-coded Whale Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3771-3790, September.
    4. Suiling Wang & Zhiqiang Jiang & Yi Liu, 2022. "Dimensionality Reduction Method of Dynamic Programming under Hourly Scale and Its Application in Optimal Scheduling of Reservoir Flood Control," Energies, MDPI, vol. 15(3), pages 1-17, January.

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