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Optimal Planning of SNOP Considering Natural Disaster

机译:考虑自然灾害时障碍的最佳规划

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Although Soft Normally Open Point (SNOP) shows its strong capability to control load transfer and regulate network voltage profile in a distribution network, considerations of the high investment costs of these special electric devices are quite limited. This paper proposes an optimal sizing and siting method for an SNOP that considers the costs and benefits of an SNOP in a distribution network. Firstly, the operation scenario of the distribution network is generated under time-series multiple scenarios during the entire period of the life cycle of an SNOP. Based on the restrictions of SNOP and system operation states that have been generated, the influence of different installation positions and SNOP capacities on the power loss is quantitatively analyzed. Secondly, the relationship between the cost of an SNOP and the capacity is analyzed. Furthermore, to make SNOP more profitable, a practical algorithm is designed for the scanning of the possible formations of islands that can be restored by an SNOP when disasters happen. In the end of the paper, the capacity and the location of an SNOP are optimized considering the balance between the benefit of energy-loss reduction in daily operations and the investment costs of the SNOP. From case study, it is validated that implementing only one SNOP in the distribution network is both optimal and practical in most simulation cases due to the restrictions of the extremely high costs, and this may greatly simplify the complexity of the optimal planning problem for the SNOP in a distribution network.
机译:虽然软常开点(SNOP)显示了其在配送网络中控制负载传递和调节网络电压简档的强能力,但这些特殊电气设备的高投资成本的考虑非常有限。本文提出了一种障碍的最佳尺寸和选址方法,用于在分销网络中考虑SNOP的成本和益处。首先,在速度的生命周期的整个周期期间在时间序列多种场景下生成分发网络的操作场景。基于所产生的SNOP和系统操作状态的限制,定量分析了不同安装位置和速度容量对电源损耗的影响。其次,分析了SNOP成本与容量之间的关系。此外,为了使SNOP更有利可图,设计了一种实用的算法,用于扫描可能在灾害发生时可以通过速度恢复的岛屿的可能构造。在纸张结束时,考虑到日常运营减少的损失与速度的投资成本之间的平衡,优化了斯诺普的能力和位置。从案例研究,它被验证,由于极高成本的限制,在大多数仿真情况下,仅在分发网络中仅实现一个速度在大多数仿真情况下都是最佳实用的,这可能极大地简化了SNOP的最佳规划问题的复杂性在分销网络中。

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