1. IoT-based off-grid solar power supply : design, implementation, and case study of energy consumption control using forecasted solar irradiationMarijan Španer, Mitja Truntič, Darko Hercog, 2025, original scientific article Abstract: This article presents the development and implementation of an IoT-enabled, off-grid solar power supply prototype designed to power a range of electrical devices. The developed system comprises a Photovoltaic panel, a Maximum Power Point Tracking (MPPT) charger, a 2.5 kWh/24 V high-performance LiFePO4 battery bank with a Battery Management System, an embedded controller with IoT connectivity, and DC/DC and DC/AC converters. The PV panel serves as the primary energy source, with the MPPT controller optimizing battery charging, while the DC/DC and DC/AC converters supply power to the connected electrical devices. The article includes a case study of a developed platform for powering an information and advertising system. The system features a predictive energy management algorithm, which optimizes the appliance operation based on daily solar irradiance forecasts and real-time battery State-of-Charge monitoring. The IoT-enabled controller obtains solar irradiance forecasts from an online meteorological service via API calls and uses these data to estimate energy availability for the next day. Using this prediction, the system schedules and prioritizes the operations of connected electrical devices dynamically to optimize the performance and prevent critical battery discharge. The IoT-based controller is equipped with both Wi-Fi and an LTE modem, enabling communication with online services via wireless or cellular networks.
Keywords: energy consumption control, forecasted solar irradiation, power management, off-grid power supply, photovoltaic, solar, IoT, LTE, Wi-Fi, ESP32
Published in DKUM: 14.11.2025; Views: 0; Downloads: 6
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2. 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, original scientific article Abstract: 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%.
Keywords: solar energy, photovoltaics, semantic segmentation, optimization, LiDAR, VHR imagery
Published in DKUM: 22.07.2025; Views: 0; Downloads: 9
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3. 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, original scientific article Keywords: energy flexibility, aluminium smelting, renewable energy, virtual battery, solar production
Published in DKUM: 17.12.2024; Views: 0; Downloads: 22
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4. 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, original scientific article Abstract: 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.
Keywords: solar energy, solar potential, anisotropic diffuse irradiance, LiDAR, GPGPU
Published in DKUM: 17.12.2024; Views: 0; Downloads: 10
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5. The impact of financial support mechanisms and geopolitical factors on the profitability of investments in solar power plants in SloveniaIztok Gornjak, Filip Kokalj, Niko Samec, 2024, original scientific article Abstract: This article examines the impact of financial support mechanisms and geopolitical factors on the profitability of investments in solar power plants within Slovenia. The European Union’s energy policy prioritizes increases in renewable energy sources, aiming to reduce dependency on unstable and volatile fossil fuel markets. Solar power plants play a vital role in this transition. The energy policy framework also includes mechanisms and support systems to operate such facilities. This article analyzes electricity price trends over the past decade and addresses which support type—guaranteed purchase or operational support—has proven more profitable for investments in solar power plants up to 50 kW in Slovenia, considering economic and geopolitical influences on the electricity market. Although the global energy market has been affected by various significant events in recent years, it was found that the COVID-19 pandemic had minimal impact on the electricity market. In contrast, the onset of the conflict in Ukraine has contributed to rising electricity prices and has influenced the support dynamics essential for the development and sustainability of renewable energy systems. Analyses from the past decade indicate a higher return on investment in solar power plants when operational support mechanisms are chosen over guaranteed purchase support.
Keywords: renewable energy sources, solar power plants, support system, investment profitability factors, electricity price
Published in DKUM: 16.12.2024; Views: 0; Downloads: 13
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6. Solar irradiance stability factorsBorut Jereb, 2024, original scientific article Abstract: In the field of renewable energies, the logistical intricacies of production, as well as the use and storage of photovoltaic energy, have become critical issues. In addition to sheer quantity, the stability of this type of energy is a crucial factor in ensuring the reliability and consistency of power generation. This paper defines Solar Irradiance Stability Factors (SISFs) as indicators complementing electricity production. When planning solar energy production in each geographical area, both the quantity and stability of solar irradiance are necessary for exploitation and determining the quality of solar irradiance. While the average production of solar energy per unit area in each time interval is a widely used parameter in daily practice, the observation of the amplitude of solar irradiance and its influence on energy production in the observed time interval is currently still rare. The SISFs defined in this article are new metrics that mainly depend on the meteorological variability in an area, and the observed time intervals should be in the range of seconds, minutes, or even hours. Larger time
intervals are not helpful for the stability of solar irradiance in energy production and logistics from the source to the destination. They provide a complementary and more accurate measure of how suitable a particular geographical area is for producing solar energy.
Keywords: solar irradiance, stability metrics, photovoltaic energy, meteorological variability, geographical area
Published in DKUM: 23.09.2024; Views: 0; Downloads: 45
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7. Prices of conventional and renewable energy as determinants of sustainable and secure energy development : regression model analysisSandi Knez, Goran Šimić, Anica Milovanović, Sofia Starikova, Franc Željko Županič, 2022, original scientific article Abstract: Background
The prices of energy resources are important determinants of sustainable energy development, yet associated with significant unknowns. The estimates of the impact of prices of energy products in the domestic market (for domestic consumers) are rare—hence the importance and novelty of this research. Therefore, the main goal of the paper is to assess the impact of domestic prices of gasoline, gas, coal, and solar energy on sustainable and secure energy future.
Methods
The research includes 14 countries (of which 7 are developed and 7 are developing countries) and a period of 5 years (2014–2018). The model also includes discrete variables: level of development (developing or developed), and the fact as to whether the country is an energy exporter or not. For the purposes of analysis, the following elements were used: Panel Data Analysis, Linear regression (with random and fixed effects), Durbin–Wu–Hausman test, and Honda test, with the use of R-studio software for statistical computing.
Results
The research showed that the biggest negative impact on energy sustainability was recorded by an increase in the price of coal and the smallest one by an increase in the price of solar energy. An increase in the price of gasoline has a positive impact, while an increase in the price of gas has no impact. The basic methodological result showed that the fixed effects linear model is more accurate than the random effect model.
Conclusions
The results of the paper, important as a sustainable energy policy recommendation, showed that the impact of changes in energy product prices is significantly greater in developing countries, but that the status of the country as an energy exporter has no significance. In addition, the paper points to the need to intensify the research on the assessment of the impact of energy product prices for domestic consumers on their ability to pay that price, because with a certain (so far undefined) increase in energy product prices, a certain group of domestic consumers moves into a category that is not in line with sustainable energy development and is extremely undesirable in every respect—energy poverty.
Keywords: sustainable energy development, conventional energy prices, solar prices, developing countries, R-studio
Published in DKUM: 26.06.2024; Views: 133; Downloads: 15
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8. High-resolution spatiotemporal assessment of solar potential from remote sensing data using deep learningMitja Žalik, Domen Mongus, Niko Lukač, 2024, original scientific article Keywords: deep learning, fully convolutional neural network, LiDAR data, digital elevation model, solar energy, solar potential
Published in DKUM: 26.01.2024; Views: 244; Downloads: 118
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9. Solar photovoltaic tracking systems for electricity generation : a reviewSebastijan Seme, Bojan Štumberger, Miralem Hadžiselimović, Klemen Sredenšek, 2020, review article Abstract: This paper presents a thorough review of state-of-the-art research and literature in the field of photovoltaic tracking systems for the production of electrical energy. A review of the literature is performed mainly for the field of solar photovoltaic tracking systems, which gives this paper the necessary foundation. Solar systems can be roughly divided into three fields: the generation of thermal energy (solar collectors), the generation of electrical energy (photovoltaic systems), and the generation of electrical energy/thermal energy (hybrid systems). The development of photovoltaic systems began in the mid-19th century, followed shortly by research in the field of tracking systems. With the development of tracking systems, di%erent types of tracking systems, drives, designs, and tracking strategies were also defined. This paper presents a comprehensive overview of photovoltaic tracking systems, as well as the latest studies that have been done in recent years. The review will be supplemented with a factual presentation of the tracking systems used at the Institute of Energy Technology of the University of Maribor.
Keywords: solar energy, photovoltaic tracking system, tracking strategies, drive system, degree of freedom
Published in DKUM: 15.11.2023; Views: 436; Downloads: 45
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10. A sustainable transport solution for a Slovenia townMatjaž Knez, Ali Naci Celik, Tariq Muneer, 2014, original scientific article Abstract: Authorities in Slovenia and other EU member states are confronted with problems of city transportation. Fossil-fuel-based transport poses two chief problems—local and global pollution, and dwindling supplies and ever-increasing costs. An elegant solution is to gradually replace the present automobile fleet with electric vehicles (EVs). This article explores the economics and practical viability of the provision of solar electricity for the charging of EVs by installation of economical available Photovoltaic modules. A steep decline in the module, inverter and installation costs is reported herein. Present estimates indicate that for the prevailing solar climate of Celje—a medium-sized Slovenian town—the cost would be only 2 euros and 11 cents per kWh of generated solar electricity.
Keywords: electric vehicles, energy sustainability, Slovenia, solar photovoltaic, sustainable transport, urban transportation
Published in DKUM: 21.07.2017; Views: 1667; Downloads: 597
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