Application of Adaptive Artificial Bee Colony Algorithm in Reservoir Information Optimal Operation

被引：0
作者：
Cui L. [1 ,2 ]
机构：
[1] Liaoning Open University, School of Public Administration, Shenyang
[2] Liaoning Equipment Manufacturing Vocational and Technical College, School of Public Administration, Shenyang
来源：
Informatica (Slovenia) | 2023年 / 47卷 / 02期
关键词：
artificial bee colony algorithm; cascade hydropower stations; comprehensive learning; multi strategy; optimal scheduling;
D O I：
10.31449/inf.v47i2.4031
中图分类号：
学科分类号：
摘要：
The hydrothermal scheduling is complex issue of nonlinear optimization consisting of several constraints that plays a critical role in the operations of power system. In order to meet the safe operation of hydropower stations, how to reasonably dispatch them to achieve the best comprehensive benefits is one of the main problems in the hydropower industry. Artificial bee colony algorithm has the advantages of simple structure and strong robustness. It is widely used in many engineering fields. However, the algorithm itself still has many shortcomings. Based on the current research, an improved artificial colony algorithm based on standard artificial bee colony algorithm is proposed, and the performance of the algorithm is verified in three benchmark functions and three cec213 test functions. Compared with many well-known improved algorithms, it is proved that the improved procedure has greatly enhances the final solution accuracy and convergence outcome. The experimental outcomes observed by improved artificial algorithm are compared with adaptable artificial bee colony procedure and chaotic artificial bee colony procedure and with other existing works in the literature. It is observed from the experimentation that the proposed algorithm performs better in comparison with established optimization algorithms. © 2023 Slovene Society Informatika. All rights reserved.
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页码：193 / 200
页数：7
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