2022
DOI: 10.3390/su142316205
|View full text |Cite
|
Sign up to set email alerts
|

Extracting Optimal Operation Rule Curves of Multi-Reservoir System Using Atom Search Optimization, Genetic Programming and Wind Driven Optimization

Abstract: This research aims to apply optimization techniques using atom search optimization (ASO), genetic programming (GP), and wind-driven optimization (WDO) with a reservoir simulation model for searching optimal rule curves of a multi-reservoir system, using the objective function with the minimum average quantity of release excess water. The multi-reservoir system consisted of five reservoirs managed by a single reservoir that caused severe problems in Sakon Nakhon province, Thailand, which was hit by floods in 20… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(2 citation statements)
references
References 39 publications
0
2
0
Order By: Relevance
“…During operation, operation rule curves need to be meticulously prepared and frequently modified to ensure project safety and maximize comprehensive utilization benefits. Scholars have conducted research to enhance the value of operation rule curves [27][28][29][30][31]. For example, a self-adaptive simulation-GA Model was introduced for the simultaneous optimization of operating rules and rule curves in multireservoir systems [23].…”
Section: Introductionmentioning
confidence: 99%
“…During operation, operation rule curves need to be meticulously prepared and frequently modified to ensure project safety and maximize comprehensive utilization benefits. Scholars have conducted research to enhance the value of operation rule curves [27][28][29][30][31]. For example, a self-adaptive simulation-GA Model was introduced for the simultaneous optimization of operating rules and rule curves in multireservoir systems [23].…”
Section: Introductionmentioning
confidence: 99%
“…However, with the increase in the operation period and the number of reservoirs, the problems of slow convergence and "dimension disaster" will appear [14]. With the development of intelligent optimization algorithms, the genetic algorithm [15][16][17][18][19], particle swarm optimization algorithm [18,[20][21][22], immune algorithm [23], firefly algorithm [24], and their improved algorithms are also used in reservoir flood control operation. The intelligent optimization algorithm has solved the "dimension disaster" problem of reservoir flood control operation, but the randomness is too strong, and it is easy to fall into the local optimal solution, and the solution result is not stable.…”
Section: Introductionmentioning
confidence: 99%