| Naslov: | Detection and optimization of photovoltaic arrays’ tilt angles using remote sensing data |
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| Avtorji: | ID Lukač, Niko (Avtor)
ID Seme, Sebastijan (Avtor)
ID Sredenšek, Klemen (Avtor)
ID Štumberger, Gorazd (Avtor)
ID Mongus, Domen (Avtor)
ID Žalik, Borut (Avtor)
ID Bizjak, Marko (Avtor) |
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| Datoteke: |  applsci-15-03598-v2.pdf (11,60 MB)
MD5: 1B717F49A769548CB79EE8AADC4025F5
 https://www.mdpi.com/2076-3417/15/7/3598
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| Jezik: | Angleški jezik |
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| Vrsta gradiva: | Članek v reviji |
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| Tipologija: | 1.01 - Izvirni znanstveni članek |
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| Organizacija: | FERI - Fakulteta za elektrotehniko, računalništvo in informatiko
FE - Fakulteta za energetiko
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| Opis: | Maximizing the energy output of photovoltaic (PV) systems is becoming increasingly important. Consequently, numerous approaches have been developed over the past few years that utilize remote sensing data to predict or map solar potential. However, they primarily address hypothetical scenarios, and few focus on improving existing installations. This paper presents a novel method for optimizing the tilt angles of existing PV arrays by integrating Very High Resolution (VHR) satellite imagery and airborne Light Detection and Ranging (LiDAR) data. At first, semantic segmentation of VHR imagery using a deep learning model is performed in order to detect PV modules. The segmentation is refined using a Fine Optimization Module (FOM). LiDAR data are used to construct a 2.5D grid to estimate the modules’ tilt (inclination) and aspect (orientation) angles. The modules are grouped into arrays, and tilt angles are optimized using a Simulated Annealing (SA) algorithm, which maximizes simulated solar irradiance while accounting for shadowing, direct, and anisotropic diffuse irradiances. The method was validated using PV systems in Maribor, Slovenia, achieving a 0.952 F1-score for module detection (using FT-UnetFormer with SwinTransformer backbone) and an estimated electricity production error of below 6.7%. Optimization results showed potential energy gains of up to 4.9%. |
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| Ključne besede: | solar energy, photovoltaics, semantic segmentation, optimization, LiDAR, VHR imagery |
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| Status publikacije: | Objavljeno |
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| Verzija publikacije: | Objavljena publikacija |
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| Poslano v recenzijo: | 12.02.2025 |
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| Datum sprejetja članka: | 24.03.2025 |
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| Datum objave: | 25.03.2025 |
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| Založnik: | MDPI AG |
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| Leto izida: | 2025 |
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| Št. strani: | 22 str. |
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| Številčenje: | let. 15, št. 7, št. članka 3598 |
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| PID: | 20.500.12556/DKUM-93491  |
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| UDK: | 621.383.51 |
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| COBISS.SI-ID: | 230279939 |
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| DOI: | 10.3390/app15073598 |
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| ISSN pri članku: | 2076-3417 |
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| Avtorske pravice: | © 2025 by the authors |
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| Datum objave v DKUM: | 22.07.2025 |
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| Število ogledov: | 153 |
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| Število prenosov: | 13 |
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| Metapodatki: |    |
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| Področja: | Ostalo
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