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@ARTICLE{Wittmann:1042381,
author = {Wittmann, Ernst and Buerhop-Lutz, Claudia and Bennett,
Savannah and Christlein, Vincent and Hauch, Jens and Brabec,
Christoph and Peters, Ian Marius},
title = {{PV} {P}olaris – {A}utomated {PV} system {O}rientation
{P}rediction},
journal = {IEEE photonics journal},
volume = {},
issn = {1943-0655},
address = {New York, NY},
publisher = {IEEE},
reportid = {FZJ-2025-02552},
pages = {1 - 8},
year = {2025},
abstract = {The orientation of a photovoltaic system is an important
parameter for power generation and yield predictions. Yet
often, the real orientation is unknown. Measuring the
orientation manually is time-consuming. This study
introduces an automated Monte Carlo Search based algorithm
called PV Polaris which is capable of predicting the systems
orientation within 18s, with uncertainties of less than 2°
in tilt and 4° in azimuth. In terms of accuracy, PV Polaris
outperforms other methods such as measurements with a tilt
compensated compass or predictions from satellite images.
Applicable at module, string and inverter levels, the
algorithm only requires power monitoring data as well as an
approximate coordinate as input. Additionally, the algorithm
can operate inversely to estimate the system's coordinates
based on a given orientation. By using this orientation
prediction, it was possible to calculate the yearly yield
loss due to non-ideal orientation. For photovoltaic systems
we investigated, we found that yearly yield increases
between $2.3\%$ to $10.3\%$ could be achieved if the PV
systems orientation would be optimized.},
cin = {IET-2},
ddc = {620},
cid = {I:(DE-Juel1)IET-2-20140314},
pnm = {1214 - Modules, stability, performance and specific
applications (POF4-121)},
pid = {G:(DE-HGF)POF4-1214},
typ = {PUB:(DE-HGF)16},
UT = {WOS:001506590100005},
doi = {10.1109/JPHOT.2025.3568887},
url = {https://juser.fz-juelich.de/record/1042381},
}