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:
Thu, 01/02/2020 - 09:35
DOI:
10.21227/bk6y-6j88
Data Format:
License:
0
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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.

Comments

Hello,
I am doing my master thesis on PQ noise analysis and this datasheet looks very related and useful. Since I do not have access to the dataset, would you please share it with me or send to ali12af@gmail.com?
Thanks in advance,
Jan

Submitted by Jan Ali on Sat, 03/20/2021 - 08:44

Hi

I am PhD student from FCUL, Lisbon. I am doing reserach on forecasting energy production for PV. I am interested to see your resreach and data. Can you share your dataset with me? If so, please inbox me a download link at my email adress: jcsimoes@fc.ul.pt

Thanks

Submitted by Joao Simoes on Mon, 10/25/2021 - 12:02