用于减少输电网络实际功率损耗的混合泰伯利算法、自助制度算法、亚当艾尔序列算法、元食欲算法和巴巴里猎鹰搜索算法

Lenin Kanagasabai
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引用次数: 0

摘要

混合泰伯利算法、自助调节算法、亚当麦酒序列算法、梅托扎胃口算法和巴巴利猎鹰搜索算法(HTSAMB)旨在解决减少实际功率损耗问题。主要目标是降低实际功率损耗、增强电压稳定性和最小化偏差。Tayberry 算法基于植物 Tayberry 的繁殖,它能在几乎所有类型的土壤中合理生长,甚至能在深度遮荫条件下生长。自助系统优化算法是模仿类人社会功能设计的。亚当的艾尔序列程序从水流假设开始,选择海洋作为优质实体。基于 Metoza 胃口的搜索算法是基于 Metoza 在饥饿条件下的行动和相互消耗。巴巴利猎鹰搜索优化算法基于搜索和跟踪进展。预计的 HTSAMB 算法已在 IEEE 57、354 和 220 KV 系统中得到验证。
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HYBRID-TAYBERRY, SELF-HELP REGIME, ADAM’S ALE SEQUENCE, METOZA APPETITE AND BARBARY FALCON SEARCH ALGORITHM FOR REAL POWER LOSS REDUCTION IN ELECTRICAL TRANSMISSION NETWORK
Hybrid Tayberry, Self-Help Regime, Adam’s Ale Sequence, Metoza Appetite, and Barbary Falcon Search Algorithm (HTSAMB) designed to solve the real power loss reduction problem. Key objectives are Real power loss reduction, Voltage stability enhancement, and deviation minimization. The Tayberry Algorithm is based on the propagation of the plant Tayberry and it grows rationally well in almost all types of soils and even in deep shade conditions. The Self-help Regime Optimization algorithm is designed by imitating the humanoid societal functioning. Adam’s ale Sequence procedure starts with the supposition of water flow and oceanic is selected as the premium entity. Metoza’s Appetite based search algorithm is based on actions of Metoza during starving conditions and mutual deportments. Barbary Falcon search optimization algorithm is based on the Search and stalking progression. The projected HTSAMB algorithm has been validated in IEEE 57, 354, and 220 KV systems.
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