Python 3.6 (Spyder) program file_Detection of corrupt data in a PV plant database
- Citation Author(s):
-
Manjunath Matam
- Submitted by:
- MANJUNATH MATAM
- Last updated:
- DOI:
- 10.21227/bk6y-6j88
- Data Format:
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Abstract
This folder contains two csv files and one .py file. One csv file contains NIST canopy PV plant data imported from https://pvdata.nist.gov/. This csv file has 1041 days raw data consisting PV plant POA irradiance, ambient temperature, Inverter DC current, DC voltage, AC current and AC voltage. Second csv file contains user created data. The Python file imports two csv files. The Python program executes four proposed corrupt data detection methods to detect corrupt data in NIST canopy PV plant data. The program generates many PDF and JPG image plots to represent the findings of four methods. A PV plant user can use this Python program by replacing the NIST canopy PV plant data with their plant data to detect corrupt days.
Instructions:
This folder contains two csv files and one .py file. One csv file contains NIST canopy PV plant data imported from https://pvdata.nist.gov/. This csv file has 1041 days raw data consisting PV plant POA irradiance, ambient temperature, Inverter DC current, DC voltage, AC current and AC voltage. Second csv file contains user created data. The Python file imports two csv files. The Python program executes four proposed corrupt data detection methods to detect corrupt data in NIST canopy PV plant data. The program generates many PDF and JPG image plots to represent the findings of four methods. A PV plant user can use this Python program by replacing the NIST canopy PV plant data with their plant data to detect corrupt days.
