Roadmap to Prepare Distribution Grid-Tied Photovoltaic Site Data for Performance Monitoring

被引:0
|
作者
Sundararajan, Aditya [1 ]
Sarwat, Arif I. [1 ]
机构
[1] Florida Int Univ, Dept Elect & Comp Engn, Miami, FL 33199 USA
来源
2017 INTERNATIONAL CONFERENCE ON BIG DATA, IOT AND DATA SCIENCE (BID) | 2017年
基金
美国国家科学基金会;
关键词
smart grid; PV big data; performance monitoring; data processing;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
One of the key analytics conducted on a gridtied Photovoltaic (PV) system is the periodic monitoring of its performance. It is expected that with increased PV penetration into the distribution smart grid in the future, quality and integrity of the data required to conduct such analytics will be crucial. While data processing and management tools for smart grid in the literature use cloud, distributed file management and parallel processing, the latency and computation requirements specific to performance monitoring need more lightweight, descriptive methods. This paper provides a systematic roadmap to analyze data collected from a real distribution grid-tied 1.4MW PV power plant for completeness, consistency and integrity, with the objective of using it for performance monitoring. To ensure the data's integrity is not compromised, the distribution of processed data is compared with that of the raw data. This paper makes one of the first few attempts to provide a comprehensive approach for data scientists to clean and prepare grid-tied PV data for site-level performance monitoring.
引用
收藏
页码:110 / 115
页数:6
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