Data on optimization of the Karun-4 hydropower reservoir operation using evolutionary algorithms

被引:17
|
作者
Akbarifard, Saeid [1 ]
Sharifi, Mohammad Reza [2 ]
Qaderi, Kourosh [3 ]
机构
[1] Shahid Chamran Univ Ahvaz, Fac Water Sci Engn, Dept Hydrol & Water Resources, Water Resources Engn, Ahvaz, Iran
[2] Shahid Chamran Univ Ahvaz, Fac Water Sci Engn, Dept Hydrol & Water Resources, Ahvaz, Iran
[3] Shahid Bahonar Univ Kerman, Dept Water Engn, Fac Agr, Kerman, Iran
来源
DATA IN BRIEF | 2020年 / 29卷
关键词
Optimization algorithms; Karun-4; reservoir; Hydropower operation; Moth swarm algorithm;
D O I
10.1016/j.dib.2019.105048
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This article describes the time series data for optimizing the hydropower operation of the Karun-4 reservoir located in Iran for a period of 106 months (from October 2010 to July 2019). The utilized time-series data included reservoir inflow, reservoir storage, evaporation from the reservoir, precipitation on the reservoir, and release of water through the power plant. In this data article, a model based on Moth Swarm Algorithm (MSA) was developed for the optimization of water resources. The analysis showed that the best solutions achieved by the MSA, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) were 0.147, 0.3026, and 0.1584, respectively. The analysis of these datasets revealed that the MSA algorithm was superior to GA and PSO algorithms in the optimal operation of the hydropower reservoir problem. (C) 2020 The Authors. Published by Elsevier Inc.
引用
收藏
页数:8
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