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Multi-objective Grasshopper Optimization Algorithm based Reconfiguration of Distribution Networks | ||
| Journal of Operation and Automation in Power Engineering | ||
| مقاله 2، دوره 7، شماره 2، دی 2019، صفحه 148-156 اصل مقاله (1.3 M) | ||
| نوع مقاله: Research paper | ||
| شناسه دیجیتال (DOI): 10.22098/joape.2019.5841.1437 | ||
| نویسندگان | ||
| M.A. Tavakoli Ghazi Jahani1؛ P. Nazarian1؛ A. Safari* 2؛ M.R. Haghifam3 | ||
| 1Department of Electrical Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran. | ||
| 2Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran | ||
| 3Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran. | ||
| چکیده | ||
| Network reconfiguration is a nonlinear optimization procedure which calculates a radial structure to optimize the power losses and improve the network reliability index while meeting practical constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with the objective functions of minimization of power losses and improvement of reliability index. The optimization problem is solved by multi-objective grasshopper optimization algorithm (MOGOA) which is one of the most modern heuristic optimization tools. To solve an optimization problem, the suggested algorithm mathematically mimics and formulates the behavior of grasshopper swarms. The modifying comfort zone coefficient needs grasshoppers to balance exploration and exploitation, which helps the MOGOA to find an exact approximation of global optimization and not trapped in local optima. The efficiency of the suggested technique is approved regarding the 33-bus and 69-bus test systems. Optimization results expressed that the suggested technique not only presents the intensified exploration ability but also has a better solution compared with previous algorithms. | ||
| کلیدواژه‌ها | ||
| Reconfiguration؛ Powe loss؛ Reliability؛ Multi-objective grasshopper optimization algorithm؛ Multi-objective optimization | ||
| مراجع | ||
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