A combination approach for optimization operation of multi-objective cascade reservoir systems (Case study: Karun reservoirs)

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS

ACS Applied Bio Materials Pub Date : 2024-05-23 DOI:10.2166/hydro.2024.264

Zahra Khoramipoor, Saeed Farzin

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引用次数: 0

Abstract

Multi-reservoir systems that have diverse and conflicting objectives are challenging to design due to their uncertainties, non-linearities, dimensions and conflicts. The operation of multi-reservoir systems is crucial to increasing hydropower production. In this study, we have investigated the application and effectiveness of the new optimization algorithm MOAHA in multi-objective cascade reservoirs with conflicting objectives, and it has been investigated on a case-by-case basis on Karun cascade reservoirs (Karun 3, Karun 1, Masjed Soleyman and Gotvand). The suggested method (MOAHA) output with other optimization algorithms, MOALO, MOGWO and NSGA-II, were compared and evaluation criteria were used to select the best performance. Additionally, we employed the powerful TOPSIS method to determine the most suitable algorithm. The considered restrictions have also been observed. The results indicate that MOAHA's proposed method is better than the compared algorithms in solving optimal reservoir utilization problems in multi-reservoir water resource systems. The reduction of evaporation (losses) from the tank surface by 9% is accompanied by a 15% increase in hydropower energy production. MOAHA, scoring 0.90, is deemed the best algorithm in this study, whereas MOGWO, with a score of 0.10, is regarded as the least effective algorithm.

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多目标级联水库系统优化运行的组合方法（案例研究：卡伦水库）

多水库系统的目标多种多样且相互冲突，由于其不确定性、非线性、复杂性和冲突性，其设计极具挑战性。多水库系统的运行对提高水电产量至关重要。在本研究中，我们研究了新优化算法 MOAHA 在具有冲突目标的多目标梯级水库中的应用和有效性，并对卡伦梯级水库（卡伦 3 号、卡伦 1 号、Masjed Soleyman 和 Gotvand）进行了个案研究。我们将建议的方法（MOAHA）输出与其他优化算法（MOALO、MOGWO 和 NSGA-II）进行了比较，并使用评估标准来选择最佳性能。此外，我们还采用了强大的 TOPSIS 方法来确定最合适的算法。我们还观察了所考虑的限制条件。结果表明，在解决多水库水资源系统中的水库优化利用问题时，MOAHA 提出的方法优于比较过的算法。水库表面蒸发（损失）减少 9%的同时，水力发电量增加 15%。在这项研究中，得分 0.90 的 MOAHA 被认为是最佳算法，而得分 0.10 的 MOGWO 被认为是最无效的算法。

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来源期刊

ACS Applied Bio Materials Chemistry-Chemistry (all)

CiteScore

9.40

自引率

2.10%

发文量

464

期刊介绍： ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.