基于随机矩阵理论的大型光伏电站设备状态评估研究

Equipment Condition Assessment of Large Photovoltaic Electric Plant Based on Random Matrix Theory

状态评估是企业硬件管理的核心问题,特别是针对设备繁多的大型光伏电站,尽早发现能效低或者有故障隐患的设备意味着提升人力资源利用效率和企业盈利,进而提升企业的竞争力。考虑光伏电站高维数据的时空相关性,基于随机矩阵理论对数据进行建模,进而设计算法提炼高维指标,形成设备状态评估判据。算例验证了随机矩阵理论算法的有效性。

Condition assessment is the core issue of enterprise management,especially for large-scale photovoltaic electric plant with a large number of equipment.Early detection of low efficiency or potential failure equipment means to enhance the efficiency of human resources utilization and corporate profits,and even then enhance the competitiveness of enterprises.Based on random matrix theory,this paper modelled the high-dimensional data for the sake of the spatial-temporal correlation.Furthermore,the algorithm was designed to extract the high-dimensional indicators to form the criteria for condition assessment.The effectiveness of the proposed method was verified by an example.