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首页> 外文期刊>International Journal of Intelligent Systems and Applications >Optimal Sitting and Sizing of Distributed Generation Units in an Indian Practical Distribution System using Bird Swarm Algorithm
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Optimal Sitting and Sizing of Distributed Generation Units in an Indian Practical Distribution System using Bird Swarm Algorithm

机译:使用鸟群算法的印度实用配电系统中分布式发电机组的最优选型和选型。

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Indian practical rural distribution systems are very long and spread over a wide range of area. The nodes far away from the distribution substation are suffering from low voltage. In India, total distribution system losses are around 20% to 25%. From the past few years, penetration of distributed generation (DG) in to the distribution network/system is increasing expeditiously. DG allocation with appropriate location and size can provide numerous benefits to the distribution companies as well as to the society. In this regard, a new technique called combined sensitivity index (CSI), to find the optimal DG unit location, based on voltage sensitivity and network load magnitude is proposed. To assess the effectiveness of the proposed technique, it is tested on Indian practical 52-bus rural distribution system. The results obtained with the proposed CSI technique is compared with the results obtained with the combined power loss sensitivity (CPLS) technique. Here, the optimal DG unit size is calculated using Bird Swarm Algorithm (BSA). The results show that the proposed CSI technique performs better in minimizing power losses and voltage profile augmentation when compared to existing CPLS technique.
机译:印度的实用农村分配系统非常长,分布在广泛的地区。远离配电变电站的节点电压低。在印度,配电系统的总损失约为20%至25%。在过去的几年中,分布式发电(DG)进入配电网络/系统的渗透正在迅速增加。具有适当位置和大小的DG分配可以为配电公司以及整个社会带来许多好处。在这方面,提出了一种新的技术,称为组合灵敏度指数(CSI),用于基于电压灵敏度和网络负载幅度来找到最佳DG单元位置。为了评估所提出技术的有效性,已在印度实际的52辆公共汽车的农村配电系统上对其进行了测试。将通过建议的CSI技术获得的结果与通过组合功率损耗敏感性(CPLS)技术获得的结果进行比较。此处,最佳DG单位大小是使用Bird Swarm算法(BSA)计算的。结果表明,与现有的CPLS技术相比,所提出的CSI技术在最小化功率损耗和电压分布增加方面表现更好。

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