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DKUM
EPF - Faculty of Business and Economics
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Title:
Razvoj modela za napoved proizvodnje električne energije v sončnih elektrarnah : magistrsko delo
Authors:
ID
Repnik, Sara
(
Author
)
ID
Ravnik, Jure
(
Mentor
)
More about this mentor...
ID
Tručl, Primož
(
Comentor
)
Files:
MAG_Repnik_Sara_2025.pdf
(54,88 MB)
MD5: AE3EECCDE7B3EBA290971F11AFA5FEDD
Language:
Slovenian
Work type:
Master's thesis/paper
Typology:
2.09 - Master's Thesis
Organization:
FS - Faculty of Mechanical Engineering
Abstract:
Magistrska naloga obravnava razvoj modela za napoved proizvodnje električne energije v sončnih elektrarnah na območju Štajerske z uporabo umetnih nevronskih mrež. Za modeliranje so bili zbrani meteorološki podatki in zgodovinski podatki o proizvodnji za 100 elektrarn na območju vzhodne Slovenije. Model je bil razvit v programskem jeziku Pythonu z uporabo knjižnice PyTorch ter testiran z različnimi arhitekturami in aktivacijskimi funkcijami. Najboljše rezultate je dosegel model z dvema skritima slojema po 128 nevronov in kombinacijo ReLU ter Sigmoid funkcij. Dosežena povprečna napaka MAPE je znašala 8–14 %, pri čemer je natančnost močno odvisna od kakovosti vhodnih podatkov.
Keywords:
sončne elektrarne
,
umetna nevronska mreža
,
napoved proizvodnje električne energije
Place of publishing:
Maribor
Place of performance:
Maribor
Publisher:
[S. Repnik]
Year of publishing:
2025
Number of pages:
1 spletni vir (1 datoteka PDF (XII, 62 f., [198] f. pril.))
PID:
20.500.12556/DKUM-95884
UDC:
621.311.243-047.72:004.8.032.26(043.2)
COBISS.SI-ID:
268598787
Publication date in DKUM:
02.12.2025
Views:
180
Downloads:
48
Metadata:
Categories:
KTFMB - FS
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Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:
04.11.2025
Secondary language
Language:
English
Title:
Development of a model for predicting electricity production in solar power plants
Abstract:
The master’s thesis focuses on developing a model for predicting electricity generation in solar power plants in the Štajerska region using artificial neural networks. Meteorological and historical production data from 100 plants in eastern Slovenia were used. The model was built in Python with PyTorch and tested with different architectures and activation functions. The best performance was achieved with two hidden layers of 128 neurons each and a combination of ReLU and Sigmoid functions. The mean absolute percentage error (MAPE) ranged from 8% to 14%, depending strongly on input data quality.
Keywords:
solar power plants
,
artificial neural network
,
Electricity production forecasting
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