Remote supervision and fault detection on OPC monitored PV systems
Remote supervision and fault detection on OPC monitored PV systems
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DOI：
10.1016/j.solener.2016.08.030
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发表时间：
2016-11
期刊：
影响因子：
6.7
通讯作者：
S. Silvestre
中科院分区：
文献类型：
--
作者：
S. Silvestre
提出了一种基于OPC技术的光伏并网发电系统自动监控和远程故障检测的新方法。通过使用标准的OPC进行监控，可以从一组使用不同通信协议的设备获取数据，例如光伏系统中的逆变器或其他电子设备，从而实现通用连接和互操作性。使用OPC标准可以促进分布式-异质环境中软件对象的互操作，还允许在系统中结合远程监控和诊断，以评估并网的光伏设施。监控系统分析监测数据，并评估光伏阵列主要参数的预期行为：输出电压、电流和功率。故障检测程序使用监测数据和评估的参数，以识别光伏系统中可能存在的故障。提出的方法已经在西班牙的一个并网光伏系统的监督中得到了实验验证。结果表明，OPC监测与监测和故障检测程序相结合是一种稳健的工具，在光伏并网发电系统的远程监测和诊断领域非常有用。即使在阴天，实际监测数据与光伏阵列建模结果之间的RMSE对于所有参数也在3.6%以下。
This paper presents a new approach for automatic supervision and remote fault detection of grid connected photovoltaic (PV) systems by means of OPC technology-based monitoring. The use of standard OPC for monitoring enables data acquisition from a set of devices that use different communication protocols as inverters or other electronic devices present in PV systems enabling universal connectivity and interoperability. Using the OPC standard allows promoting interoperation of software objects in distributed-heterogeneous environments and also allows incorporating in the system remote supervision and diagnosis for the evaluation of grid connected PV facilities. The supervision system analyses the monitored data and evaluates the expected behaviour of main parameters of the PV array: Output voltage, current and power. The monitored data and evaluated parameters are used by the fault detection procedure in order to identify possible faults present in the PV system. The methodology presented has been experimentally validated in the supervision of a grid connected PV system located in Spain. Results obtained show that the combination of OPC monitoring along with the supervision and fault detection procedure is a robust tool that can be very useful in the field of remote supervision and diagnosis of grid connected PV systems. The RMSE between real monitored data and results obtained from the modelling of the PV array were below 3.6% for all parameters even in cloudy days.