A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Article number | 2787 |
Journal / Publication | Energies |
Volume | 13 |
Issue number | 11 |
Online published | 1 Jun 2020 |
Publication status | Published - Jun 2020 |
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DOI | DOI |
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Attachment(s) | Documents
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85085843115&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(07c00600-8881-40d9-969c-ec3a0b3b937b).html |
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.
Research Area(s)
- Dynamic programming, Genetic algorithm, Heuristic method, Hydropower generation, Optimal generation scheduling, Renewable energy
Citation Format(s)
A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems. / Hammid, Ali Thaeer; Awad, Omar I.; Sulaiman, Mohd Herwan et al.
In: Energies, Vol. 13, No. 11, 2787, 06.2020.
In: Energies, Vol. 13, No. 11, 2787, 06.2020.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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