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

Autor: Saeid Akbarifard, Mohammad Reza Sharifi, Kourosh Qaderi
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Data in Brief, Vol 29, Iss , Pp - (2020)
Druh dokumentu: article
ISSN: 2352-3409
DOI: 10.1016/j.dib.2019.105048
Popis: 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. Keywords: Optimization algorithms, Karun-4 reservoir, Hydropower operation, Moth swarm algorithm
Databáze: Directory of Open Access Journals