An 18 kW solar array research facility for fault detection experiments
An 18 kW solar array research facility for fault detection experiments
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用于故障检测实验的 18 kW 太阳能电池阵列研究设施
DOI：
10.1109/melcon.2016.7495369
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
A. Spanias
中科院分区：
文献类型：
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作者：
Sunil Rao;David Ramirez;Henry Braun;Jongmin Lee;C. Tepedelenlioğlu;E. Kyriakides;Devarajan Srinivasan;Jeffrey Frye;Shinji Koizumi;Y. Morimoto;A. Spanias
监测公用事业规模的太阳能电池阵列被证明可以最大限度地减少维护成本，并有助于优化阵列在各种条件下的性能。在本文中，我们描述了一个18千瓦的实验设施，由104面板与智能监控设备的设计。这些设备中的每一个都嵌入了传感器、无线收发器和继电器，可以实现连续监控、故障检测和实时连接拓扑变化。该设施通过使用与服务器、融合和控制中心以及移动的设备的无线数据共享来实现联网数据交换。该阶段计划的研究包括开发用于故障检测的机器学习方法。本文给出了利用机器学习进行故障检测的初步仿真结果。
Monitoring utility-scale solar arrays was shown to minimize cost of maintenance and help optimize the performance of the array under various conditions. In this paper, we describe the design of an 18 kW experimental facility that consists of 104 panels fitted with smart monitoring devices. Each of these devices embeds sensors, wireless transceivers, and relays that enable continuous monitoring, fault detection, and real-time connection topology changes. The facility enables networked data exchanges via the use of wireless data sharing with servers, fusion and control centers, and mobile devices. Research planned at this stage includes developing machine learning methods for fault detection. Preliminary simulation results on fault detection using machine learning are given in this paper.