Roadmap to prepare distribution grid-tied photovoltaic site data for performance monitoring

Aditya Sundararajan; Arif I. Sarwat

doi:10.1109/BID.2017.8336582

Roadmap to prepare distribution grid-tied photovoltaic site data for performance monitoring

Aditya Sundararajan, Arif I. Sarwat

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

21 Scopus citations

Abstract

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.

Original language	English
Title of host publication	2017 International Conference on Big Data, IoT and Data Science, BID 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	110-115
Number of pages	6
ISBN (Electronic)	9781509065936
DOIs	https://doi.org/10.1109/BID.2017.8336582
State	Published - Jul 2 2017
Externally published	Yes
Event	2017 International Conference on Big Data, IoT and Data Science, BID 2017 - Pune, India Duration: Dec 20 2017 → Dec 22 2017

Publication series

Name	2017 International Conference on Big Data, IoT and Data Science, BID 2017
Volume	2018-January

Conference

Conference	2017 International Conference on Big Data, IoT and Data Science, BID 2017
Country/Territory	India
City	Pune
Period	12/20/17 → 12/22/17

Funding

The work for this paper has been sponsored by the National Science Foundation (NSF) Grant No. CNS-1553494.

Keywords

PV big data
data processing
performance monitoring
smart grid

Access to Document

10.1109/BID.2017.8336582

Cite this

Sundararajan, A., & Sarwat, A. I. (2017). Roadmap to prepare distribution grid-tied photovoltaic site data for performance monitoring. In 2017 International Conference on Big Data, IoT and Data Science, BID 2017 (pp. 110-115). (2017 International Conference on Big Data, IoT and Data Science, BID 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BID.2017.8336582

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title = "Roadmap to prepare distribution grid-tied photovoltaic site data for performance monitoring",

abstract = "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.",

keywords = "PV big data, data processing, performance monitoring, smart grid",

author = "Aditya Sundararajan and Sarwat, \{Arif I.\}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Conference on Big Data, IoT and Data Science, BID 2017 ; Conference date: 20-12-2017 Through 22-12-2017",

year = "2017",

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Sundararajan, A & Sarwat, AI 2017, Roadmap to prepare distribution grid-tied photovoltaic site data for performance monitoring. in 2017 International Conference on Big Data, IoT and Data Science, BID 2017. 2017 International Conference on Big Data, IoT and Data Science, BID 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 110-115, 2017 International Conference on Big Data, IoT and Data Science, BID 2017, Pune, India, 12/20/17. https://doi.org/10.1109/BID.2017.8336582

Roadmap to prepare distribution grid-tied photovoltaic site data for performance monitoring. / Sundararajan, Aditya; Sarwat, Arif I.
2017 International Conference on Big Data, IoT and Data Science, BID 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 110-115 (2017 International Conference on Big Data, IoT and Data Science, BID 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

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Sundararajan A, Sarwat AI. Roadmap to prepare distribution grid-tied photovoltaic site data for performance monitoring. In 2017 International Conference on Big Data, IoT and Data Science, BID 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 110-115. (2017 International Conference on Big Data, IoT and Data Science, BID 2017). doi: 10.1109/BID.2017.8336582

Roadmap to prepare distribution grid-tied photovoltaic site data for performance monitoring

Abstract

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