基于离群点分析的分布式光伏发电量异常检测算法

针对分布式光伏有带病运行以及骗取国家补贴的现象,本文基于离群点分析中的格拉布斯准则和分布式光伏的自身特点,提出了一种分布式光伏发电量异常检测算法。该算法可以筛选出单位容量日发电量过高与过低的分布式光伏用户,进而可以避免分布式光伏长期带病运行,以及遏制骗取国家补贴的行为。最后以某县的分布式光伏数据进行了算例分析,验证了该算法的有效性。

Anomaly Detection Algorithm for Distributed Photovoltaic Generation Based on Outlier Analysis

According to distributed photovoltaic system sick running and defraud state subsidies behavior, an anomaly detection algorithm for distributed photovoltaic generation is proposed, based on the outlier analysis based on Grubbs criterion and the characteristics of the distributed photovoltaic system. The algorithm can filter out the users, whose power generation of the unit capacity per day is too high or too low, so that distributed photovoltaic system long-term sick run can be avoided and defraud state subsidies behavior can be curbed. Finally based on the data of the distributed photovoltaic systems in a county, an example is analyzed. And the results show that the algorithm is effective.