Generating realistic Smart Grid communication topologies based on real-data
Generating realistic Smart Grid communication topologies based on real-data
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DOI：
10.1109/smartgridcomm.2014.7007684
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发表时间：
2014-11
期刊：
影响因子：
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通讯作者：
Thomas Hartmann;François Fouquet;Jacques Klein;Y. L. Traon;A. Pelov;L. Toutain;T. Ropitault
中科院分区：
文献类型：
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作者：
Thomas Hartmann;François Fouquet;Jacques Klein;Y. L. Traon;A. Pelov;L. Toutain;T. Ropitault
今天的电网必须经历重大变革，才能跟上不断增长的能源需求。智能电网的愿景旨在提高当今电网的效率和可靠性，例如通过整合可再生能源和分布式微型发电。这项工作的支柱是促进信息和通信技术，以实现双向通信和设备自动控制。底层通信拓扑结构对于智能电网至关重要，并且是使智能电网智能化的关键。分析、模拟、设计和比较智能电网基础设施，以及优化路由算法和预测故障的影响，所有这些都依赖于对智能电网通信拓扑结构的深入了解。然而，由于智能电网仍处于研究和测试阶段，因此很难获得真实世界的拓扑数据。在本文中，我们提供了一个全面的分析电力线通信拓扑结构的现实世界的智能电网，目前部署和测试在卢森堡。基于此分析的结果，我们实现了一个发电机自动创建随机但现实的智能电网通信拓扑结构。研究人员和工业专业人员可以使用这些工具来分析、模拟、设计、比较和改进智能电网基础设施。
Today's electricity grid must undergo substantial changes in order to keep pace with the rising demand for energy. The vision of the smart grid aims to increase the efficiency and reliability of today's electricity grid, e.g. by integrating renewable energies and distributed micro-generations. The backbone of this effort is the facilitation of information and communication technologies to allow two-way communication and an automated control of devices. The underlying communication topology is essential for the smart grid and is what enables the smart grid to be smart. Analyzing, simulating, designing, and comparing smart grid infrastructures but also optimizing routing algorithms, and predicating impacts of failures, all of this relies on deep knowledge of a smart grids communication topology. However, since smart grids are still in a research and test phase, it is very difficult to get access to real-world topology data. In this paper we provide a comprehensive analysis of the power-line communication topology of a real-world smart grid, the one currently deployed and tested in Luxembourg. Building on the results of this analysis we implement a generator to automatically create random but realistic smart grid communication topologies. These can be used by researchers and industrial professionals to analyze, simulate, design, compare, and improve smart grid infrastructures.