A Review of Optimization Algorithms in Solving Hydro Generation Scheduling Problems

Ali Thaeer Hammid, 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
Additional contact information
Ali Thaeer Hammid: Computer Engineering Techniques Department, Faculty of Information Technology, Imam Ja’afar Al-Sadiq University, Baghdad 10012, Iraq
Omar I. Awad: State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
Mohd Herwan Sulaiman: Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pahang, Pekan 26600, Malaysia
Saraswathy Shamini Gunasekaran: College of Computing and Informatics, Universiti Tenaga Nasional, Selangor, Kajang 43000, Malaysia
Salama A. Mostafa: Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Johor, Batu Pahat 86400, Malaysia
Nallapaneni Manoj Kumar: School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong, China
Bashar Ahmad Khalaf: College of Basic Education, University of Diyala, Diyala 32001, Iraq
Yasir Amer Al-Jawhar: Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, Batu Pahat 86400, Malaysia
Raed Abdulkareem Abdulhasan: Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, Batu Pahat 86400, Malaysia

Energies, 2020, vol. 13, issue 11, 1-21

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.

Keywords: renewable energy; optimal generation scheduling; heuristic method; genetic algorithm; dynamic programming; hydropower generation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/11/2787/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/11/2787/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:11:p:2787-:d:365787

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().