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Review

A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems

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Computer Engineering Techniques Department, Faculty of Information Technology, Imam Ja’afar Al-Sadiq University, Baghdad 10012, Iraq
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Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pahang, Pekan 26600, Malaysia
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State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
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College of Computing and Informatics, Universiti Tenaga Nasional, Selangor, Kajang 43000, Malaysia
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Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Johor, Batu Pahat 86400, Malaysia
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School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong, China
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College of Basic Education, University of Diyala, Diyala 32001, Iraq
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Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, Batu Pahat 86400, Malaysia
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Iraqi Ministry of Communications (M.O.C.), Mamoon, Baghdad 10012, Iraq
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Authors to whom correspondence should be addressed.
Energies 2020, 13(11), 2787; https://doi.org/10.3390/en13112787
Received: 19 April 2020 / Revised: 23 May 2020 / Accepted: 25 May 2020 / Published: 1 June 2020
The optimal generation scheduling (OGS) of hydropower units holds an important position in electric power systems, which is significantly investigated as a research issue. Hydropower has a slight social and ecological effect when compared with other types of sustainable power source. The target of long-, mid-, and short-term hydro scheduling (LMSTHS) problems is to optimize the power generation schedule of the accessible hydropower units, which generate maximum energy by utilizing the available potential during a specific period. Numerous traditional optimization procedures are first presented for making a solution to the LMSTHS problem. Lately, various optimization approaches, which have been assigned as a procedure based on experiences, have been executed to get the optimal solution of the generation scheduling of hydro systems. This article offers a complete survey of the implementation of various methods to get the OGS of hydro systems by examining the executed methods from various perspectives. Optimal solutions obtained by a collection of meta-heuristic optimization methods for various experience cases are established, and the presented methods are compared according to the case study, limitation of parameters, optimization techniques, and consideration of the main goal. Previous studies are mostly focused on hydro scheduling that is based on a reservoir of hydropower plants. Future study aspects are also considered, which are presented as the key issue surrounding the LMSTHS problem. View Full-Text
Keywords: renewable energy; optimal generation scheduling; heuristic method; genetic algorithm; dynamic programming; hydropower generation renewable energy; optimal generation scheduling; heuristic method; genetic algorithm; dynamic programming; hydropower generation
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MDPI and ACS Style

Thaeer Hammid, A.; Awad, O.I.; Sulaiman, M.H.; Gunasekaran, S.S.; Mostafa, S.A.; Manoj Kumar, N.; Khalaf, B.A.; Al-Jawhar, Y.A.; Abdulhasan, R.A. A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems. Energies 2020, 13, 2787. https://doi.org/10.3390/en13112787

AMA Style

Thaeer Hammid A, Awad OI, Sulaiman MH, Gunasekaran SS, Mostafa SA, Manoj Kumar N, Khalaf BA, Al-Jawhar YA, Abdulhasan RA. A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems. Energies. 2020; 13(11):2787. https://doi.org/10.3390/en13112787

Chicago/Turabian Style

Thaeer Hammid, Ali, Omar I. Awad, Mohd Herwan Sulaiman, Saraswathy Shamini Gunasekaran, Salama A. Mostafa, Nallapaneni Manoj Kumar, Bashar Ahmad Khalaf, Yasir Amer Al-Jawhar, and Raed Abdulkareem Abdulhasan. 2020. "A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems" Energies 13, no. 11: 2787. https://doi.org/10.3390/en13112787

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