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A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems

Hammid, Ali Thaeer and Awad, Omar I. and M. H., Sulaiman and Saraswathy Shamini, Gunasekaran and Mostafa, Salama A. and Kumar, Nallapaneni Manoj and Khalaf, Bashar Ahmad and Al-Jawhar, Yasir Amer and Abdulhasan, Raed Abdulkareem (2020) A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems. Energies, 13 (11). pp. 1-21. ISSN 1996-1073

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Abstract

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.

Item Type: Article
Uncontrolled Keywords: Renewable energy; optimal generation scheduling; heuristic method; genetic algorithm; dynamic programming; hydropower generation
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Institute of Postgraduate Studies
Depositing User: Noorul Farina Arifin
Date Deposited: 15 Jun 2020 07:27
Last Modified: 15 Jun 2020 07:27
URI: http://umpir.ump.edu.my/id/eprint/28439
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