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Short-term scheduling of hydro-based power plants considering application of heuristic algorithms: A comprehensive review

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  • Nazari-Heris, M.
  • Mohammadi-Ivatloo, B.
  • B. Gharehpetian, G.

Abstract

Optimal generation scheduling of hydro-based power units has a significant place in electric power systems, which considerably has been dealt with as a subject of investigations for several years. Hydrothermal system is introduced as an important hydro-based power generation system. The objective of short-term hydrothermal scheduling (STHS) problem is obtaining the power generation schedule of the available hydro and thermal power units, which aims to minimize total fuel cost of thermal plants during a determined time period. Many conventional optimization procedures are first introduced for solving STHS problem. Recently, heuristic and meta-heuristic optimization methods, which are defined as an experience-based procedure, are implemented for obtaining optimal solution of generation planning of hydrothermal systems. This paper provides a comprehensive review on the application of heuristic methods to obtain optimal generation scheduling of hydrothermal systems, which compares the implemented procedures from different points of view. Optimal solutions obtained by employment of multiple heuristic and meta-heuristic optimization methods for different test instances are demonstrated and the introduced methods are compared in terms of convergence speed, attained optimal solutions, and constraints. Future research trends are discussed, which can be introduced as the subject of studies in the area of STHS problem.

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  • 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.
    • Handle: RePEc:eee:rensus:v:74:y:2017:i:c:p:116-129
    DOI: 10.1016/j.rser.2017.02.043
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    6. Pedro H. M. Nascimento & Vinícius A. Cabral & Ivo C. Silva Junior & Frederico F. Panoeiro & Leonardo M. Honório & André L. M. Marcato, 2021. "Spillage Forecast Models in Hydroelectric Power Plants Using Information from Telemetry Stations and Hydraulic Control," Energies, MDPI, vol. 14(1), pages 1-16, January.
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    9. Maha Mohamed & Abdel-Raheem Youssef & Salah Kamel & Mohamed Ebeed & Ehab E. Elattar, 2021. "Optimal Scheduling of Hydro–Thermal–Wind–Photovoltaic Generation Using Lightning Attachment Procedure Optimizer," Sustainability, MDPI, vol. 13(16), pages 1-24, August.
    10. Krešimir Fekete & Srete Nikolovski & Zvonimir Klaić & Ana Androjić, 2019. "Optimal Re-Dispatching of Cascaded Hydropower Plants Using Quadratic Programming and Chance-Constrained Programming," Energies, MDPI, vol. 12(9), pages 1-25, April.
    11. Kheshti, Mostafa & Ding, Lei & Ma, Shicong & Zhao, Bing, 2018. "Double weighted particle swarm optimization to non-convex wind penetrated emission/economic dispatch and multiple fuel option systems," Renewable Energy, Elsevier, vol. 125(C), pages 1021-1037.
    12. Daneshvar, Mohammadreza & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Asadi, Somayeh, 2020. "Two-stage stochastic programming model for optimal scheduling of the wind-thermal-hydropower-pumped storage system considering the flexibility assessment," Energy, Elsevier, vol. 193(C).
    13. Gupta, Akshita & Kumar, Arun & Khatod, Dheeraj Kumar, 2019. "Optimized scheduling of hydropower with increase in solar and wind installations," Energy, Elsevier, vol. 183(C), pages 716-732.
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