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Stochastic hydro-thermal scheduling optimization: An overview

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  • de Queiroz, Anderson Rodrigo

Abstract

This paper presents an overview about the hydro-thermal scheduling problem. In an electrical power system power generators have to be scheduled over a time horizon in order to supply system demand. The scheduling problem consists in dispatching the available generators to meet the system electric load while minimizing the operational costs related to fuel and possible load curtailments. In a system with a large share of hydro generation, different from a thermal dominant power system, the uncertainty of water inflows play an important role in the decision-making process. In this setting the scheduling of generators has to be determined considering different future possibilities for water availability. Also, in the existence of a cascade system, the availability of water to produce electricity in hydro plants is influenced by decisions taken in upstream reservoirs. These issues complicate the hydro-thermal scheduling problem that often in the literature is modeled as a multi-stage stochastic program. In this paper we aim to give an overview about the main ideas behind this problem. We present model formulations, a solution technique, and point out to new developments related to this research.

Suggested Citation

  • de Queiroz, Anderson Rodrigo, 2016. "Stochastic hydro-thermal scheduling optimization: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 382-395.
    • Handle: RePEc:eee:rensus:v:62:y:2016:i:c:p:382-395
    DOI: 10.1016/j.rser.2016.04.065
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    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. de Queiroz, A.R. & Mulcahy, D. & Sankarasubramanian, A. & Deane, J.P. & Mahinthakumar, G. & Lu, N. & DeCarolis, J.F., 2019. "Repurposing an energy system optimization model for seasonal power generation planning," Energy, Elsevier, vol. 181(C), pages 1321-1330.
    7. Paulo Vitor Larroyd & Renata Pedrini & Felipe Beltrán & Gabriel Teixeira & Erlon Cristian Finardi & Lucas Borges Picarelli, 2022. "Dealing with Negative Inflows in the Long-Term Hydrothermal Scheduling Problem," Energies, MDPI, vol. 15(3), pages 1-19, February.
    8. de Queiroz, Anderson Rodrigo & Marangon Lima, Luana M. & Marangon Lima, José W. & da Silva, Benedito C. & Scianni, Luciana A., 2016. "Climate change impacts in the energy supply of the Brazilian hydro-dominant power system," Renewable Energy, Elsevier, vol. 99(C), pages 379-389.
    9. Edson Bortoni & Zulcy de Souza & Augusto Viana & Helcio Villa-Nova & Ângelo Rezek & Luciano Pinto & Roberto Siniscalchi & Rafael Bragança & José Bernardes, 2019. "The Benefits of Variable Speed Operation in Hydropower Plants Driven by Francis Turbines," Energies, MDPI, vol. 12(19), pages 1-20, September.
    10. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Challenges, opportunities, and strategies for undertaking integrated precinct-scale energy–water system planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    11. Duenas, Pablo & Ramos, Andres & Tapia-Ahumada, Karen & Olmos, Luis & Rivier, Michel & Pérez-Arriaga, Jose-Ignacio, 2018. "Security of supply in a carbon-free electric power system: The case of Iceland," Applied Energy, Elsevier, vol. 212(C), pages 443-454.
    12. Yi Yu & Yonggang Wu & Binqi Hu & Xinglong Liu, 2018. "An enhanced artificial bee colony algorithm (EABC) for solving dispatching of hydro-thermal system (DHTS) problem," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-19, January.
    13. Hafiz, Faeza & Rodrigo de Queiroz, Anderson & Fajri, Poria & Husain, Iqbal, 2019. "Energy management and optimal storage sizing for a shared community: A multi-stage stochastic programming approach," Applied Energy, Elsevier, vol. 236(C), pages 42-54.
    14. Rasku, Topi & Miettinen, Jari & Rinne, Erkka & Kiviluoma, Juha, 2020. "Impact of 15-day energy forecasts on the hydro-thermal scheduling of a future Nordic power system," Energy, Elsevier, vol. 192(C).
    15. Zhang, Yi & Cheng, Chuntian & Cao, Rui & Li, Gang & Shen, Jianjian & Wu, Xinyu, 2021. "Multivariate probabilistic forecasting and its performance’s impacts on long-term dispatch of hydro-wind hybrid systems," Applied Energy, Elsevier, vol. 283(C).
    16. Anderson Passos de Aragão & Patrícia Teixeira Leite Asano & Ricardo de Andrade Lira Rabêlo, 2020. "A Reservoir Operation Policy Using Inter-Basin Water Transfer for Maximizing Hydroelectric Benefits in Brazil," Energies, MDPI, vol. 13(10), pages 1-26, May.
    17. Eshraghi, Hadi & Rodrigo de Queiroz, Anderson & Sankarasubramanian, A. & DeCarolis, Joseph F., 2021. "Quantification of climate-induced interannual variability in residential U.S. electricity demand," Energy, Elsevier, vol. 236(C).
    18. Jun Dong & Peiwen Yang & Shilin Nie, 2019. "Day-Ahead Scheduling Model of the Distributed Small Hydro-Wind-Energy Storage Power System Based on Two-Stage Stochastic Robust Optimization," Sustainability, MDPI, vol. 11(10), pages 1-27, May.
    19. Xiaoyu Shi & Xuewen Lei & Qiang Huang & Shengzhi Huang & Kun Ren & Yuanyuan Hu, 2018. "Hourly Day-Ahead Wind Power Prediction Using the Hybrid Model of Variational Model Decomposition and Long Short-Term Memory," Energies, MDPI, vol. 11(11), pages 1-20, November.
    20. de Queiroz, Anderson Rodrigo & Faria, Victor A.D. & Lima, Luana M.M. & Lima, José W.M., 2019. "Hydropower revenues under the threat of climate change in Brazil," Renewable Energy, Elsevier, vol. 133(C), pages 873-882.
    21. Nazari-Heris, M. & Mohammadi-Ivatloo, B. & B. Gharehpetian, G., 2017. "Short-term scheduling of hydro-based power plants considering application of heuristic algorithms: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 116-129.
    22. Razavi, Seyed-Ehsan & Esmaeel Nezhad, Ali & Mavalizadeh, Hani & Raeisi, Fatima & Ahmadi, Abdollah, 2018. "Robust hydrothermal unit commitment: A mixed-integer linear framework," Energy, Elsevier, vol. 165(PB), pages 593-602.
    23. Jian, Jinbao & Pan, Shanshan & Yang, Linfeng, 2019. "Solution for short-term hydrothermal scheduling with a logarithmic size mixed-integer linear programming formulation," Energy, Elsevier, vol. 171(C), pages 770-784.
    24. Tejada-Arango, Diego A. & Wogrin, Sonja & Siddiqui, Afzal S. & Centeno, Efraim, 2019. "Opportunity cost including short-term energy storage in hydrothermal dispatch models using a linked representative periods approach," Energy, Elsevier, vol. 188(C).
    25. Vanderson Aparecido Delapedra-Silva & Paula Ferreira & Jorge Cunha & Herbert Kimura, 2021. "Economic Evaluation of Wind Power Projects in a Mix of Free and Regulated Market Environments in Brazil," Energies, MDPI, vol. 14(11), pages 1-18, June.

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