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An efficient modified dragonfly algorithm and whale optimization approach for optimal scheduling of microgrid with islanding constraints
Transactions of the Institute of Measurement and Control ( IF 1.7 ) Pub Date : 2020-10-07 , DOI: 10.1177/0142331220961657
K.S Kavitha Kumari 1 , R. Samuel Rajesh Babu 2
Affiliation  

This paper presented an effective technique for considering optimal scheduling of microgrid (MG) with islanding constraints. The proposed optimal scheduling approach is the combination of both the modified dragonfly algorithm (MDA) and whale optimization algorithm (WOA)-based approach named as (MDAWO). In this work, the searching conduct of the dragonflies is altered by the effective WOA approach. This WOA is used to the optimal scheduling of MG and also significantly reduces the computational burden. In this paper, the MDAWO is the appraisal technique used to set up the definite schedule of the MG coupling subject to the power assortment. The equality and inequality constraints are utilized to characterize the target capacity of a projected approach using the system information. Batteries act as an energy source to adjust the MG with continual running at an unfaltering and stable output control. Finally, the performance of the proposed technique is executed through the MATLAB/Simulink working platform with two different scenarios. With these two different scenarios, the proposed technique performance is compared with existing techniques such as dragonfly algorithm, firefly and gravitational search algorithm. Furthermore, the statistical analysis of the proposed technique based on cost and fitness are analyzed. Numerical simulations demonstrate the effectiveness of the proposed MG optimal scheduling model and explore its economic and reliability merits.

中文翻译:

具有孤岛约束的微电网优化调度的高效改进蜻蜓算法和鲸鱼优化方法

本文提出了一种考虑具有孤岛约束的微电网 (MG) 优化调度的有效技术。所提出的最优调度方法是改进的蜻蜓算法(MDA)和基于鲸鱼优化算法(WOA)的方法(MDAWO)的结合。在这项工作中,蜻蜓的搜索行为被有效的 WOA 方法改变了。该 WOA 用于 MG 的优化调度,也显着减少了计算负担。在本文中,MDAWO 是一种评估技术,用于建立受功率配置约束的 MG 联轴器的确定时间表。利用等式和不等式约束来表征使用系统信息的投影方法的目标容量。电池作为能源来调整 MG,并以坚定和稳定的输出控制持续运行。最后,通过具有两种不同场景的 MATLAB/Simulink 工作平台执行所提出技术的性能。在这两种不同的场景下,将所提出的技术性能与现有技术如蜻蜓算法、萤火虫和引力搜索算法进行了比较。此外,还分析了基于成本和适应度的所提出技术的统计分析。数值模拟证明了所提出的 MG 优化调度模型的有效性,并探讨了其经济性和可靠性优点。所提出技术的性能通过具有两种不同场景的 MATLAB/Simulink 工作平台执行。在这两种不同的场景下,将所提出的技术性能与现有技术如蜻蜓算法、萤火虫和引力搜索算法进行了比较。此外,还分析了基于成本和适应度的所提出技术的统计分析。数值模拟证明了所提出的 MG 优化调度模型的有效性,并探讨了其经济性和可靠性优点。所提出技术的性能通过具有两种不同场景的 MATLAB/Simulink 工作平台执行。在这两种不同的场景下,将所提出的技术性能与现有技术如蜻蜓算法、萤火虫和引力搜索算法进行了比较。此外,还分析了基于成本和适应度的所提出技术的统计分析。数值模拟证明了所提出的 MG 优化调度模型的有效性,并探讨了其经济性和可靠性优点。
更新日期:2020-10-07
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