Sensorless fault detection method for photovoltaic systems through mapping the inherent characteristics of PV plant site: Simple and practical

摘要

Research on monitoring and fault detection systems for photovoltaic plants is significantly increasing with the continual development in technologies and the availability of qualified data. Nevertheless, many gaps still exist that need to be addressed. The electrical output of PV plants in various weather conditions is very close to those obtained under fault conditions. For a large scale PV plant, it is very crucial to utilize the data in the decision-making process without using external sensors or performing simulation studies that require detailed parameters of the plant. The main challenge here is to automatically rationalize the collected data in order to make a decision on distinguishing between faulty and natural outputs. This paper proposes a method for distinguishing faults and inherent changes in the PV plant's output to help O&M crews identify and fix system issues. The proposed method has the ability to map the inherent characteristics of the PV plant by using only the data received from inverters without using additional equipment or detailed models. It has been developed by analyzing the working mechanisms of several large scale PV plants installed in Turkey. The proposed method can easily be implemented in a newly installed or existing PV plant. The novelty of this study is detecting abnormal operations in a PV plant even under low irradiance and cloudy-sky conditions without using any irradiance and temperature sensors. The effectiveness of the proposed method is shown in rooftop and ground-mounted PV plants.