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Preemptive mode-change triggering for inverters in response to unintentional islanding situations in high solar PV penetration distribution networks

机译:在高太阳能光伏渗透率分配网络中,针对意外孤岛情况的逆变器抢占式模式触发

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Unintentional islanding is one of the major concerns associated with integration of large solar photovoltaic generation with the power distribution network. However the issue of islanding needs to be comprehensively understood and managed given a challenging scenario ahead. This demands transition towards predictive approaches rather than the prevalent reactive ones for island detection and system management. The present work describes a machine learning based preemptive islanding detection module designed on a Raspberry Pi microcomputer for issuing advance alert to grid-interfaced solar photovoltaic inverters in the event of an imminent islanding situation and triggering the subsequent action. The module can activate a timely change in the inverter's operating mode by detecting precursors to accidental islanding, before the utility relay can trip a circuit breaker. Thus an intentional island can be maintained with acceptable power quality after the modechanging operation. The module can also issue a shut-down command to the inverter's control in order to completely avoid an unintentional island formation. Preliminary tests on an islanding precursor, discovered in simulation and on real laboratory-based network, have been presented. The precursor is simulated on a modified IEEE feeder and the online classification accuracy and speed indicate promising potential as a field-level prototype.
机译:无意孤岛是与大型太阳能光伏发电与配电网络集成相关的主要问题之一。但是,鉴于未来的挑战性局面,需要全面理解和管理孤岛问题。这就要求过渡到预测性方法,而不是用于岛检测和系统管理的普遍反应性方法。本工作描述了一种在Raspberry Pi微型计算机上设计的基于机器学习的抢占式孤岛检测模块,该模块可在出现孤岛情况并触发后续动作时向电网接口的太阳能光伏逆变器发出预警。在公用继电器可以使断路器跳闸之前,该模块可以通过检测意外孤岛的前兆来激活逆变器的运行模式的及时更改。因此,在模式改变操作之后,可以以可接受的电能质量来维持有意的孤岛。该模块还可以向逆变器的控制发出关闭命令,以完全避免意外的孤岛形成。已经提出了对在模拟和基于实验室的真实网络中发现的孤岛前体的初步测试。该前体在改进的IEEE馈线上进行了仿真,在线分类的准确性和速度表明它有望成为现场级原型。

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