1. Impact of voltage supraharmonics on power supply units in low-voltage gridsPrimož Sukič, Danilo Dmitrašinović, Gorazd Štumberger, 2025, izvirni znanstveni članek Opis: Voltage supraharmonics present in the electrical grid can trigger chain reactions in grid-connected household and industrial power supplies equipped with Power Factor Correction (PFC). A single source of voltage supraharmonics may significantly increase the current in switching devices with PFC, leading to higher-amplitude disturbances throughout the electrical network. When addressing issues in a real low-voltage (LV) grid, it was observed that activation of a single device emitting supraharmonics caused oscillating currents across all feeders connected to the transformer’s busbars, matching the frequency of the supraharmonic source. To investigate this phenomenon further, the grid voltage containing supraharmonics was replicated in a controlled laboratory environment and used to supply various power electronic devices. The laboratory results closely mirrored those observed in the field. Supraharmonics present in the supply voltage caused current oscillations in the power electronic devices at the same frequency. Moreover, the amplitude of the observed current oscillations increased with the amplitude of the injected supply voltage supraharmonics. In some cases, the root mean square (RMS) value of the current drawn by the power electronic devices doubled, indicating a substantial impact on device behaviour and potential implications for grid stability and energy efficiency.
Ključne besede: supraharmonics, PFC, solar inverters, PV inverters, hybrid converter
Objavljeno v DKUM: 29.10.2025; Ogledov: 0; Prenosov: 5
 Celotno besedilo (11,31 MB) |
2. Optimal ensemble-based framework for ground-fault protection in radial MV distribution networks with resonant grounding☆Boštjan Polajžer, Younes Mohammadi, Thomas Olofsson, Gorazd Štumberger, 2025, izvirni znanstveni članek Opis: Ground fault relays (GFRs) in resonant-grounded medium voltage distribution networks shall not operate during phase-to-ground (Ph-G) fault inception, allowing the Petersen coil to suppress self-extinguishing faults, but the designated GFR must operate during permanent faults. In order to enhance the performance of GFRs, particularly during high-impedance faults, the scope of this paper is to propose a straightforward, machine-learning-based protection framework. The enhanced GFR is modeled as a classification task. Depending on the GFR’s position and the Ph-G fault location in the network, fault samples are labeled as “no operation,” “primary,” “backup,” or “backup of backup,” forming two-class, three-class, and four-class GFR setups, respectively. This assures selective operation across three protection zones and improves the reliability of all GFRs. The proposed protection scheme employs backward optimal feature selection to identify the most relevant discrete features obtained from measured zero-sequence current and voltage waveforms. An ensemble of k-nearest neighbor classifiers is utilized for accurate classification, simulating the GFR operating conditions, with measurement errors and sensitivity incorporated in the preprocessing. A 20 kV case study network validates the proposed framework, achieving F1-scores exceeding 96 %. The maximum operation delay of the protection scheme for an enhanced GFR is 225 ms, accommodating the required time window (200 ms), prediction time (5 ms), and change detection time (20 ms), thus assuring safe operation. Compared to other machine-learning-based methods used for Ph-G fault protection in resonant-grounded radial networks, this framework is high-performing, fast, and easy to implement, utilizing a simpler structure than neural networks.
Ključne besede: resonant grounded networks, ground-fault relay, high-impedance faults, ensemble-based learning, optimal feature selection
Objavljeno v DKUM: 25.07.2025; Ogledov: 0; Prenosov: 4
Celotno besedilo (4,86 MB) |
3. Detection and optimization of photovoltaic arrays’ tilt angles using remote sensing dataNiko Lukač, Sebastijan Seme, Klemen Sredenšek, Gorazd Štumberger, Domen Mongus, Borut Žalik, Marko Bizjak, 2025, izvirni znanstveni članek 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%.
Ključne besede: solar energy, photovoltaics, semantic segmentation, optimization, LiDAR, VHR imagery
Objavljeno v DKUM: 22.07.2025; Ogledov: 0; Prenosov: 9
Celotno besedilo (11,60 MB)
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4. Multiplicative method for assessing the technical condition of switching bay devices in a substation using maintenance prioritiesJanez Ribič, Gorazd Štumberger, Marko Vodenik, Uroš Kerin, Miha Bečan, Anja Šketa, Drago Bokal, Peter Kitak, 2025, izvirni znanstveni članek Opis: The results of the presented research are directly applicable to enhancing the maintenance strategies of transmission system operator (TSO) assets, particularly high-voltage switchyard equipment, and are extendable to other TSO systems. Furthermore, the proposed methodology lays the groundwork for the implementation of predictive maintenance. This paper introduces a novel methodology for assessing the technical condition of high-voltage switchyard devices—specifically, circuit breakers, disconnectors, and instrument transformers—within a high-voltage switching bay. The proposed model integrates multiplicative criteria, which reflect maintenance actions, and additive criteria, which capture the operational and maintenance history of individual devices. Supported by a newly developed data model, the methodology enables an automated assessment process that generates a c-curve representing the condition trajectory of each device or device type. Leveraging real-time data from the maintenance information system, this automated approach allows for the timely evaluation of a device’s technical state prior to scheduled maintenance. The resulting c-curve analysis supports strategic maintenance planning and prioritization. The proposed solutions have been implemented experimentally by TSO ELES.
Ključne besede: condition-based maintenance, health index, circuit breaker, disconnector, instrument transformer, substation, failure mode analysis
Objavljeno v DKUM: 23.06.2025; Ogledov: 0; Prenosov: 15
Celotno besedilo (1,52 MB)
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6. Energy flexibility in aluminium smelting : a long-term feasibility study based on the prospects of electricity load and photovoltaic productionMarko Bizjak, Niko Uremović, Domen Mongus, Primož Sukič, Gorazd Štumberger, Haris Salihagić Hrenko, Dragan Mikša, Stanislav Kores, Niko Lukač, 2024, izvirni znanstveni članek Ključne besede: energy flexibility, aluminium smelting, renewable energy, virtual battery, solar production
Objavljeno v DKUM: 17.12.2024; Ogledov: 0; Prenosov: 22
Celotno besedilo (1,91 MB) |
7. Novel GPU-accelerated high-resolution solar potential estimation in urban areas by using a modified diffuse irradiance modelNiko Lukač, Domen Mongus, Borut Žalik, Gorazd Štumberger, Marko Bizjak, 2024, izvirni znanstveni članek Opis: In the past years various methods have been developed to estimate high-resolution solar potential in urban areas, by simulating solar irradiance over surface models that originate from remote sensing data. In general, this requires discretisation of solar irradiance models that estimate direct, reflective, and diffuse irradiances. The latter is most accurately estimated by an anisotropic model, where the hemispherical sky dome from arbitrary surface’s viewpoint consists of the horizon, the circumsolar and sky regions. Such model can be modified to incorporate the effects of shadowing from obstruction with a view factor for each sky region. However, state-of-the-art using such models for estimating solar potential in urban areas, only considers the sky view factor, and not circumsolar view factor, due to high computational load. In this paper, a novel parallelisation of solar potential estimation is proposed by using General Purpose computing on Graphics Processing Units (GPGPU). Modified anisotropic Perez model is used by considering diffuse shadowing with all three sky view factors. Moreover, we provide validation based on sensitivity analysis of the method’s accuracy with independent meteorological measurements, by changing circumsolar sky region’s half-angle and resolution of the hemispherical sky dome. Finally, the presented method using GPPGU was compared to multithreaded Central Processing Unit (CPU) approach, where on average a 70x computational speedup was achieved. Finally, the proposed method was applied over a urban area, obtained from Light Detection And Ranging (LiDAR) data, where the computation of solar potential was performed in a reasonable time.
Ključne besede: solar energy, solar potential, anisotropic diffuse irradiance, LiDAR, GPGPU
Objavljeno v DKUM: 17.12.2024; Ogledov: 0; Prenosov: 10
Celotno besedilo (8,06 MB) |
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9. Izbira primernega hranilnika energije za sončno elektrarno : diplomsko deloŽan Hrnčić, 2024, diplomsko delo Opis: Diplomsko delo obravnava izbiro hranilnikov energije za proizvodnjo električne energije s sončno elektrarno, naključnost katere je zmanjšana ravno z uporabo primernega hranilnika energije. Pri izbiri ustreznih hranilnikov energije moramo poiskati tehnologijo, ki bo primerna za aktivno sodelovanje v storitvah na trgu električne energije in bo za proizvedeno energijo sončne elektrarne omogočala največji finančni izplen in povrnitev investicije. Ker je eden od okoljskih ciljev družbe tudi zmanjšanje ogljičnega odtisa, smo analizirali tehnologije hranilnikov energije, ki imajo majhen ogljični odtis in so hkrati dovolj učinkovite in primerne za sodelovanje v storitvah na trgu električne energije.
Ključne besede: sončne elektrarne, hranilniki energije, storitve na trgu električne energije, izbira hranilnika energije
Objavljeno v DKUM: 08.10.2024; Ogledov: 0; Prenosov: 26
Celotno besedilo (2,03 MB) |
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