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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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    1. Wang, Yongqiang & Zhou, Jianzhong & Mo, Li & Zhang, Rui & Zhang, Yongchuan, 2012. "Short-term hydrothermal generation scheduling using differential real-coded quantum-inspired evolutionary algorithm," Energy, Elsevier, vol. 44(1), pages 657-671.
    2. de Queiroz, Anderson Rodrigo, 2016. "Stochastic hydro-thermal scheduling optimization: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 382-395.
    3. Mahor, Amita & Prasad, Vishnu & Rangnekar, Saroj, 2009. "Economic dispatch using particle swarm optimization: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 2134-2141, October.
    4. Nguyen, Thang Trung & Vo, Dieu Ngoc & Truong, Anh Viet, 2014. "Cuckoo search algorithm for short-term hydrothermal scheduling," Applied Energy, Elsevier, vol. 132(C), pages 276-287.
    5. H.A. Oliveira, Jr. & A. Petraglia & L. Ingber & M.A.S. Machado & M.R. Petraglia, . "Stochastic global optimization and its applications with fuzzy adaptive simulated annealing," Lester Ingber Books, Lester Ingber, number 12a2, December-.
    6. L. Ingber, 2012. "Adaptive simulated annealing," Lester Ingber Papers 12as, Lester Ingber.
    7. Zhang, Huifeng & Zhou, Jianzhong & Fang, Na & Zhang, Rui & Zhang, Yongchuan, 2013. "Daily hydrothermal scheduling with economic emission using simulated annealing technique based multi-objective cultural differential evolution approach," Energy, Elsevier, vol. 50(C), pages 24-37.
    8. Catalão, J.P.S. & Pousinho, H.M.I. & Mendes, V.M.F., 2011. "Hydro energy systems management in Portugal: Profit-based evaluation of a mixed-integer nonlinear approach," Energy, Elsevier, vol. 36(1), pages 500-507.
    9. Narang, Nitin & Dhillon, J.S. & Kothari, D.P., 2012. "Multiobjective fixed head hydrothermal scheduling using integrated predator-prey optimization and Powell search method," Energy, Elsevier, vol. 47(1), pages 237-252.
    10. Corsatea, Teodora Diana & Giaccaria, Sergio & Covrig, Catalin-Felix & Zaccarelli, Nicola & Ardelean, Mircea, 2016. "RES diffusion and R&D investments in the flexibilisation of the European electricity networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 1069-1082.
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    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.
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