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首页> 外文期刊>Smart Grid, IEEE Transactions on >HPC-Based Intelligent Volt/VAr Control of Unbalanced Distribution Smart Grid in the Presence of Noise
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HPC-Based Intelligent Volt/VAr Control of Unbalanced Distribution Smart Grid in the Presence of Noise

机译：存在噪声的基于HPC的不平衡配电智能电网智能Volt / VAr控制

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摘要

The performance of Volt/VAr optimization has been significantly improved due to the integration of measurement data obtained from the advanced metering infrastructure of a smart grid. However, most of the existing works lack: 1) realistic unbalanced multi-phase distribution system modeling; 2) scalability of the Volt/VAr algorithm for larger test system; and 3) ability to handle gross errors and noise in data processing. In this paper, we consider realistic distribution system models that include unbalanced loadings and multi-phased feeders and the presence of gross errors such as communication errors and device malfunction, as well as random noise. At the core of the optimization process is an intelligent particle swarm optimization-based technique that is parallelized using high performance computing technique to solve Volt/VAr-based power loss minimization problem. Extensive experiments covering the different aspects of the proposed framework show significant improvement over existing Volt/VAr approaches in terms of both the accuracy and scalability on IEEE 123 node and a larger IEEE 8500 node benchmark test systems.
机译：由于集成了从智能电网的先进计量基础设施获得的测量数据，Volt / VAr优化的性能得到了显着改善。但是，大多数现有工作缺乏：1）现实的不平衡多相配电系统建模； 2）Volt / VAr算法在较大测试系统中的可扩展性； 3）处理数据处理中的严重错误和噪声的能力。在本文中，我们考虑了现实的配电系统模型，其中包括不平衡负载和多相馈线，以及诸如通信错误和设备故障以及随机噪声之类的重大错误的存在。优化过程的核心是基于智能粒子群优化的技术，该技术使用高性能计算技术进行并行化处理，以解决基于Volt / VAr的功率损耗最小化问题。涵盖拟议框架不同方面的大量实验表明，与现有的Volt / VAr方法相比，IEEE 123节点和更大的IEEE 8500节点基准测试系统在准确性和可扩展性方面均取得了显着改进。

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