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Optimal allocation of distributed generations using hybrid technique with fuzzy logic controller radial distribution system

机译:采用模糊逻辑控制器径向分布系统的混合技术优化分布代分布

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摘要

In this concept, an enhanced idea is proposed for solving the optimal load flow issues with uncertainties. In this articlethe Fuzzy Logic Controller (FLC) technique and Ant-Lion Optimization Algorithm’s (ALOA) with Particle Swarm Optimization(PSO) based combination is proposed. The ALO imitates the hunting mechanism of ant lions in nature and thePSO improves the ALO performance by updating elitism phase of ALO. The FLC is trained based on training dataset andtesting time which produces the optimal allocation parameters are based on the variation of radial distribution networkparameters. In this projected hybrid algorithm, Photo-Voltaic and Wind Turbine generations (PV and WT) are consideringas Distributed Generators (DGs). Initially, after defining the multi objective function, then about voltage deviation,minimization of power loss and improvement of voltage stability index is discussed. The minimization of cost of operationand deviation of voltage indexes are considered as multi objective functions and the projected technique is evaluateon IEEE 33 standard radial distribution systems. With new hybrid technique, allocation of multi-DGs like wind and PV atdifferent sites, and the optimal load flow at various cases is analyzed.
机译:在这一概念中,提出了一种增强的想法,用于解决不确定性的最佳负载流问题。在本文中模糊逻辑控制器(FLC)技术和抗狮子优化算法(ALOA),具有粒子群优化(PSO)提出了基于组合。 Alo模仿自然界的蚂蚁狮子的狩猎机制PSO通过更新ALO的豁免阶段来提高ALO性能。 FLC根据培训数据集进行培训产生最佳分配参数的测试时间基于径向分配网络的变化参数。在该预测的混合算法中,考虑光伏和风力涡轮机代(PV和WT)作为分布式发电机(DGS)。最初,在定义多目标函数之后,然后关于电压偏差,讨论了最小化功率损耗和电压稳定性指数的提高。最小化操作成本电压索引的偏差被认为是多目标函数,并且预计技术是评估在IEEE 33标准径向分配系统上。采用新的混合技​​术,像风和光伏等多DG的分配分析了不同的网站,以及各种情况下的最佳负载流。

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