论文标题
可扩展的数据存储用于光伏监控系统
Scalable data storage for PV monitoring systems
论文作者
论文摘要
有效的PV研究包括来自具有不同特征的多个实验的延长数据监视，需要一个可扩展的支持系统来处理所有收集的信息。本文介绍了一个关系数据库的开发，用于托管所有必要的信息，用于数据建模，比较分析和O \＆M系统。 Ramer-Douglas-Peucker算法和TimeScaledB压缩用于减少时间序列数据的大小并提高查询的性能。提出了一种决策算法，用于选择Ramer-Douglas-Peucker算法的最佳输入，以确保最大的磁盘空间节省，同时又不丢失任何必要的信息。此外，还提供了实现相同数据库的替代方法。
Efficient PV research which includes a prolonged data monitoring from multiple experiments with different characteristics, requires a scalable supporting system to handle all of the collected information. This paper presents the development of a relational database for hosting all the necessary information for data modeling, comparative analysis and O\&M systems. Ramer-Douglas-Peucker algorithm and Timescaledb compression are used to decrease the size of the time-series data and increase the performance of the queries. A decision-making algorithm is presented for selecting the optimal inputs to the Ramer-Douglas-Peucker algorithm to ensure the maximum disk space savings while not losing any of the necessary information. Furthermore, alternative ways of implementing the same database are provided.
