Investigation of Data Mining Method in Optimal Operation of Eyvashan Earth Dam Reservoir Based on PSO Algorithm

Abstract

Today, Metaheuristic Algorithms are considered one of the most important and appropriate methods to achieve good solutions and optimization. In this research, a Particle swarm optimization (PSO) algorithm with a nonlinear objective function has been used to optimize the reservoir water allocation of the Eyvashan earth dam based on the reservoir water balance for irrigation periods (2014-2020). The results show that the highest agricultural demand downstream of the dam in June was 8.96 (MCM). The amount of reservoir release calculated by the model to meet the water requirement downstream of the dam (37.80MCM) is much more optimal than the total amount of downstream needs (41.03MCM). Also, the minimum amount of water shortage due to severe drought while controlling floods is easily possible due to the reservoir's useful volume and the reservoir's annual flow. According to the PSO model, in each period of operation of Eyvashan earth dam, about 7.9% can be saved in the reservoir release for the needs of downstream agriculture in the months of high water consumption in summer.