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Optimal placement of data concentrators for expansion of the smart grid communications network

机译：用于扩展智能电网通信网络数据集中器的最佳位置

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Evolving power systems with increasing renewables penetration, along with the development of the smart grid, calls for improved communication networks to support these distributed generation sources. Automatic and optimal placement of communication resources within the advanced metering infrastructure is critical to provide a high-performing, reliable, and resilient power system. Three network design formulations based on mixed-integer linear and non-linear programming approaches are proposed to minimise network congestion by optimising residual buffer capacity through the placement of data concentrators and network routeing. Results on a case study show that the proposed models improve network connectivity and robustness, and increase average residual buffer capacity. Maximising average residual capacity alone, however, results in both oversaturated and underutilised nodes, while maximising either minimum residual capacity or total reciprocal residual capacity can yield much-improved network load allocation. Consideration of connection redundancy improves network reliability further by ensuring quality-of-service in the event of an outage. Analysis of multi-period network expansion shows that the models do not deviate significantly from optimal when used progressively (within 5% deviation), and are effective for utility planners to use for smart grid expansion.
机译：随着可再生能源的渗透，随着智能电网的开发而不断发展的电力系统，呼叫改进的通信网络以支持这些分布式生成源。高级计量基础设施内的通信资源的自动和最佳放置对于提供高性能，可靠和弹性的电力系统至关重要。提出了一种基于混合整数线性和非线性编程方法的网络设计配方，通过放置数据集中器和网络路由来最小化网络拥塞。结果研究表明，该模型提高了网络连接和鲁棒性，并提高了平均剩余缓冲容量。然而，单独的平均剩余容量最大化，导致过饱和和未充分的节点，同时最大化最小剩余容量或总互易剩余容量可以产生大量改善的网络负荷分配。考虑到连接冗余的考虑通过确保停电时的服务质量进一步提高了网络可靠性。多时期网络扩展的分析表明，当逐步使用时，模型不会显着偏离最佳（在5％偏差范围内），并且对于智能电网扩展来说是有效的。

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