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基于混合正弦余弦算法的经济负荷调度

Economic load dispatch using memetic sine cosine algorithm.

作者信息

Al-Betar Mohammed Azmi, Awadallah Mohammed A, Zitar Raed Abu, Assaleh Khaled

机构信息

Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates.

Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, Irbid, Jordan.

出版信息

J Ambient Intell Humaniz Comput. 2022 Feb 7:1-29. doi: 10.1007/s12652-022-03731-1.

Abstract

In this paper, the economic load dispatch (ELD) problem which is an important problem in electrical engineering is tackled using a hybrid sine cosine algorithm (SCA) in a form of memetic technique. ELD is tackled by assigning a set of generation units with a minimum fuel costs to generate predefined load demand with accordance to a set of equality and inequality constraints. SCA is a recent population based optimizer turned towards the optimal solution using a mathematical-based model based on sine and cosine trigonometric functions. As other optimization methods, SCA has main shortcoming in exploitation process when a non-linear constraints problem like ELD is tackled. Therefore, -hill climbing optimizer, a recent local search algorithm, is hybridized as a new operator in SCA to empower its exploitation capability to tackle ELD. The proposed hybrid algorithm is abbreviated as SCA- HC which is evaluated using two sets of real-world generation cases: (i) 3-units, two versions of 13-units, and 40-units, with neglected Ramp Rate Limits and Prohibited Operating Zones constraints. (ii) 6-units and 15-units with Ramp Rate Limits and Prohibited Operating Zones constraints. The sensitivity analysis of the control parameters for SCA- HC is initially studied. The results show that the performance of the SCA- HC algorithm is increased by tuning its parameters in proper value. The comparative evaluation against several state-of-the-art methods show that the proposed method is able to produce new best results for some tested cases as well as the second-best for others. In a nutshell, hybridizing HC optimizer as a new operator for SCA is very powerful algorithm for tackling ELD problems.

摘要

在本文中,采用一种基于文化算法的混合正弦余弦算法(SCA)来解决电气工程中的一个重要问题——经济负荷调度(ELD)问题。通过为一组发电单元分配最小燃料成本,以根据一组等式和不等式约束来生成预定义的负荷需求,从而解决ELD问题。SCA是一种基于种群的优化器,它使用基于正弦和余弦三角函数的数学模型来寻求最优解。与其他优化方法一样,在解决像ELD这样的非线性约束问题时,SCA在开发过程中存在主要缺点。因此,将一种最近提出的局部搜索算法——爬山优化器,作为一种新的算子与SCA进行混合,以增强其解决ELD问题的开发能力。所提出的混合算法简称为SCA-HC,使用两组实际发电案例进行评估:(i)3机组、两个版本的13机组和40机组,忽略了爬坡速率限制和禁止运行区域约束。(ii)6机组和15机组,考虑了爬坡速率限制和禁止运行区域约束。首先研究了SCA-HC控制参数的敏感性分析。结果表明,通过将其参数调整到合适的值,可以提高SCA-HC算法的性能。与几种先进方法的对比评估表明,所提出的方法能够在一些测试案例中产生新的最佳结果,在其他案例中产生次优结果。简而言之,将爬山优化器作为SCA的新算子进行混合,是解决ELD问题的一种非常强大的算法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/690c/8821871/db305faee14d/12652_2022_3731_Fig1_HTML.jpg

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