Purpose

Purpose of this paper are Real power loss reduction, voltage stability enhancement and minimization of Voltage deviation.

Design/methodology/approach

In HLG approach as per Henry gas law sum of gas dissolved in the liquid is directly proportional to the partial pressure on above the liquid. Gas dissolving in the liquid which based on Henry gas law is main concept to formulate the proposed algorithm. Populations are divided into groups and all the groups possess the similar Henry constant value. Exploration and exploitation has been balanced effectively. Ranking and position of the worst agents is done in order to avoid the local optima. Then in this work Mobula alfredi optimization (MAO) algorithm is projected to solve optimal reactive power problem. Foraging actions of Mobula alfredi has been imitated to design the algorithm. String foraging, twister foraging and backward roll foraging are mathematically formulated to solve the problem. In the entire exploration space the Mobula alfredi has been forced to discover new regions by assigning capricious position. Through this approach, exploration competence of the algorithm has been improved. In all iterations, the position of the Mobula alfredi has been updated and replaced with the most excellent solution found so far. Exploration and exploitation capabilities have been maintained sequentially. Then in this work balanced condition algorithm (BCA) is projected to solve optimal reactive power problem. Proposed BCA approach based on the conception in physics- on the subject of the mass; incoming, exit and producing in the control volume. Preliminary population has been created based on the dimensions and number of particles and it initialized capriciously in the exploration space with minimum and maximum concentration. Production control parameter and Production probability utilized to control the exploration and exploitation.

Findings

Proposed Henry's Law based -soluble gas optimization (HLG) algorithm, Mobula alfredi optimization (MAO) algorithm and BCA are evaluated in IEEE 30 bus system with L-index (Voltage stability) and also tested in standard IEEE 14, 30, 57, 118, 300 bus test systems without L- index. Real power loss minimization, voltage deviation minimization, and voltage stability index enhancement has been attained.

Originality/value

For the first time Henry's Law based -soluble gas optimization (HLG) algorithm, Mobula alfredi optimization (MAO) algorithm and BCA is projected to solve the power loss reduction problem.

中文翻译：

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通过基于亨利定律的可溶性气体、mobula alfredi 和平衡条件优化算法减少功率损耗

目的

本文的目的是降低实际功率损耗、增强电压稳定性和最小化电压偏差。

设计/方法/方法

在 HLG 方法中，根据亨利气体定律，溶解在液体中的气体总和与液体上方的分压成正比。基于亨利气体定律的气体溶解在液体中是制定所提出算法的主要概念。人口被分成几组，所有组都具有相似的亨利常数值。勘探开发有效平衡。对最差代理进行排名和位置是为了避免局部最优。然后在这项工作中，Mobula alfredi 优化 (MAO) 算法被设计为解决最优无功功率问题。算法设计模仿了 Mobula alfredi 的觅食行为。串觅食、捻线觅食和向后滚动觅食都用数学公式来解决这个问题。在整个探索空间中，Mobula alfredi 被迫通过分配反复无常的位置来发现新的区域。通过这种方法，算法的探索能力得到了提高。在所有迭代中，Mobula alfredi 的位置都已更新并替换为迄今为止发现的最优秀的解决方案。勘探开发能力保持有序。然后在这项工作中，平衡条件算法（BCA）被用来解决最优无功功率问题。基于物理学概念提出的 BCA 方法——关于质量的主题；控制量中的输入、输出和生产。根据粒子的尺寸和数量创建了初步种群，并在探索空间中以最小和最大浓度反复初始化。

发现

提议的基于亨利定律的可溶气体优化 (HLG) 算法、Mobula alfredi 优化 (MAO) 算法和 BCA 在具有 L 指数（电压稳定性）的 IEEE 30 总线系统中进行了评估，并在标准 IEEE 14、30、57、118 中进行了测试, 300 个没有 L- 指数的总线测试系统。实现了实际功率损耗最小化、电压偏差最小化、电压稳定指标提升。

原创性/价值

首次提出基于亨利定律的可溶气体优化（HLG）算法、Mobula alfredi 优化（MAO）算法和BCA 来解决功率损耗降低问题。