This paper deals with developing a new technique based on artificial neural networks (ANN) for monitoring of the remote grid connected photovoltaic (PV) plant. An ANN utilizes the existing impedance relays’ measurements located at switchgear panel to monitor the PV power generated. Also, the proposed technique is able to monitor the power consumed by the load at the distribution side. The simple proposed technique can monitor and decide the reverse power flow in the distribution feeder. Furthermore, the proposed method identifies an index which diagnosis the PV plant performance. The estimated power from the ANN is compared with the PV generation from real time recorded weather data at the distribution site, and the performance index is obtained accordingly. This technique does not employ any communication infrastructure as usually used in the classical monitoring techniques available in the literature. This advantage makes the proposed scheme very highly attractive from the economical point of view.

本文致力于开发一种基于人工神经网络（ANN）的新技术，用于监测远程并网光伏（PV）厂。ANN利用位于开关柜面板上的现有阻抗继电器的测量值来监视所产生的PV功率。而且，所提出的技术能够监视配电侧的负载消耗的功率。所提出的简单技术可以监视并确定配电馈线中的反向功率流。此外，所提出的方法确定了诊断光伏电站性能的指标。将来自ANN的估算功率与配电现场实时记录的气象数据产生的PV进行比较，从而获得性能指标。该技术没有采用文献中通常使用的经典监视技术中通常使用的任何通信基础结构。从经济的角度来看，这一优点使所提出的方案具有很高的吸引力。