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Outdoor PV system monitoring—input data quality, data imputation and filtering approaches
ID
Lindig, Sascha
(
Avtor
),
ID
Louwen, Atse
(
Avtor
),
ID
Moser, David
(
Avtor
),
ID
Topič, Marko
(
Avtor
)
PDF - Predstavitvena datoteka,
prenos
(23,77 MB)
MD5: EC7F59F6D17DCF8BCBBB0EDE3F0D4F3C
URL - Izvorni URL, za dostop obiščite
https://www.mdpi.com/1996-1073/13/19/5099
Galerija slik
Izvleček
Photovoltaic monitoring data are the primary source for studying photovoltaic plant behavior. In particular, performance loss and remaining-useful-lifetime calculations rely on trustful input data. Furthermore, a regular stream of high quality is the basis for pro-active operation and management activities which ensure a smooth operation of PV plants. The raw data under investigation are electrical measurements and usually meteorological data such as in-plane irradiance and temperature. Usually, performance analyses follow a strict pattern of checking input data quality followed by the application of appropriate filter, choosing a key performance indicator and the application of certain methodologies to receive a final result. In this context, this paper focuses on four main objectives. We present common photovoltaics monitoring data quality issues, provide visual guidelines on how to detect and evaluate these, provide new data imputation approaches, and discuss common filtering approaches. Data imputation techniques for module temperature and irradiance data are discussed and compared to classical approaches. This work is intended to be a soft introduction into PV monitoring data analysis discussing best practices and issues an analyst might face. It was seen that if a sufficient amount of training data is available, multivariate adaptive regression splines yields good results for module temperature imputation while histogram-based gradient boosting regression outperforms classical approaches for in-plane irradiance transposition. Based on tested filtering procedures, it is believed that standards should be developed including relatively low irradiance thresholds together with strict power-irradiance pair filters.
Jezik:
Angleški jezik
Ključne besede:
photovoltaics
,
solar cells
,
photovoltaic system performance
,
photovoltaic system data
,
data quality
,
data imputation
,
data filtering
Vrsta gradiva:
Članek v reviji
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FE - Fakulteta za elektrotehniko
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Leto izida:
2020
Št. strani:
18 str.
Številčenje:
Vol. 13, iss. 19, art. 5099
PID:
20.500.12556/RUL-134484
UDK:
621.383.51
ISSN pri članku:
1996-1073
DOI:
10.3390/en13195099
COBISS.SI-ID:
32452611
Datum objave v RUL:
18.01.2022
Število ogledov:
1191
Število prenosov:
168
Metapodatki:
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Objavi na:
Gradivo je del revije
Naslov:
Energies
Skrajšan naslov:
Energies
Založnik:
Molecular Diversity Preservation International
ISSN:
1996-1073
COBISS.SI-ID:
518046745
Licence
Licenca:
CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:
http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:
To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:
01.10.2020
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
fotovoltaika
,
sončne celice
Projekti
Financer:
EC - European Commission
Program financ.:
H2020
Številka projekta:
721452
Naslov:
Photovoltaic module life time forecast and evaluation
Akronim:
SOLAR-TRAIN
Financer:
EC - European Commission
Program financ.:
European Regional Development Fund
Financer:
Drugi - Drug financer ali več financerjev
Program financ.:
Autonomous Province Bolzano—South Tyrol
Številka projekta:
FESR1128-Project PV4.0
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