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Open-source quality control routine and multi-year power generation data of 175 PV systems

Authors: Visser, Lennard; Elsinga, Boudewijn; AlSkaif, Tarek; van Sark, Wilfried;

Open-source quality control routine and multi-year power generation data of 175 PV systems

Abstract

Description The repository contains an extensive dataset of PV power measurements and a python package (qcpv) for quality controlling PV power measurements. The dataset features four years (2014-2017) of power measurements of 175 rooftop mounted residential PV systems located in Utrecht, the Netherlands. The power measurements have a 1-min resolution. PV power measurements Three different versions of the power measurements are included in three data-subsets in the repository. Unfiltered power measurements are enclosed in unfiltered_pv_power_measurements.csv. Filtered power measurements are included as filtered_pv_power_measurements_sc.csv and filtered_pv_power_measurements_ac.csv. The former dataset contains the quality controlled power measurements after running single system filters only, the latter dataset considers the output after running both single and across system filters. The metadata of the PV systems is added in metadata.csv. This file holds for each PV system a unique ID, start and end time of registered power measurements, estimated DC and AC capacity, tilt and azimuth angle, annual yield and mapped grids of the system location (north, south, west and east boundary). Quality control routine An open-source quality control routine that can be applied to filter erroneous PV power measurements is added to the repository in the form of the Python package qcpv (qcpv.py). Sample code to call and run the functions in the qcpv package is available as example.py. Objective By publishing the dataset we provide access to high quality PV power measurements that can be used for research experiments on several topics related to PV power and the integration of PV in the electricity grid. By publishing the qcpv package we strive to set a next step into developing a standardized routine for quality control of PV power measurements. We hope to stimulate others to adopt and improve the routine of quality control and work towards a widely adopted standardized routine. Data usage If you use the data and/or python package in a published work please cite: Visser, L., Elsinga, B., AlSkaif, T., van Sark, W., 2022. Open-source quality control routine and multi-year power generation data of 175 PV systems. Journal of Renewable and Sustainable Energy. Units Timestamps are in UTC (YYYY-MM-DD HH:MM:SS+00:00). Power measurements are in Watt. Installed capacities (DC and AC) are in Watt-peak. Additional information A detailed discussion of the data and qcpv package is presented in: Visser, L., Elsinga, B., AlSkaif, T., van Sark, W., 2022. Open-source quality control routine and multi-year power generation data of 175 PV systems. Journal of Renewable and Sustainable Energy. Corrections are discussed in: Visser, L., Elsinga, B., AlSkaif, T., van Sark, W., 2024. Erratum: Open-source quality control routine and multiyear power generation data of 175 PV systems. Journal of Renewable and Sustainable Energy. Acknowledgements This work is part of the Energy Intranets (NEAT: ESI-BiDa 647.003.002) project, which is funded by the Dutch Research Council NWO in the framework of the Energy Systems Integration & Big Data programme. The authors would especially like to thank the PV owners who volunteered to take part in the measurement campaign. 

Country
Netherlands
Related Organizations
Keywords

PV power measurements, quality control routine, open-source code, Open-source dataset, Quality control routine, Open-source code, open-source dataset

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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