1. 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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2. Public support of solar electricity and its impact on households - prosumersJarmila Zimmermannová, Adam Pawliczek, Petr Čermák, 2018, original scientific article Abstract: Background and Purpose: Currently, the idea of households - prosumers is broadly discussed in public governments, mainly in connection with both the energy security issues and the environmental issues. Therefore, the main goal of this paper is to present new agent model of household - prosumer and to compare two scenarios – “off grid household” and “on grid household”. The additional goal is to evaluate the impact of public support of solar electricity on the economic efficiency of household – prosumer projects (systems).
Design/Methodology/Approach: The model is structured as a micro-level agent model, representing one household – prosumer. The model has the following general characteristics: one household with own electricity generation (photovoltaic panels), battery and in case of “on grid household” also connection to the grid. The main goal of the agent is to cover electricity consumption in household with minimal costs. The agent model of prosumer is tested and validated, using the empirical data.
Results: The highest level of subsidy has significant impact on the economic indicators of selected scenarios. It causes lower investment costs at the beginning of the project and consequently shorter payback period (3-4 years earlier), positive cumulative cash flow, net present value and IRR in earlier period (approximately 5-10 years earlier, depending on the scenario).
Conclusion: We can recommend to the government to continue with current system of subsidies, since it contributes to better economic indicators of particular solar electricity projects. On the other hand, the level of subsidy should be at least the same as in current year 2017, for the purposes of representing the significant part of the investment costs. Low level of subsidy has negligible impact on the economic indicators of households – prosumers projects. The developed agent model is suitable for the evaluation of economic impact of public support on households – prosumers.
Keywords: renewable electricity, photovoltaics, prosumers, households, public support, agent model, energy model
Published in DKUM: 07.05.2018; Views: 1384; Downloads: 432
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3. The value of "vehicle to grid" integration into warehouse logistics management : case of Slovenian retailerMatjaž Knez, Péter Bajor, 2011, original scientific article Abstract: Wide-scale application photovoltaic energy sources for electricity production purposes is quite a challenge in Slovenia. The nature of sun is unpredictable, and the Slovenian National Grid has no significant storage opportunities today - if the V2G (vehicle-to-grid) solutions could be competitive in the near future we could prepare for the special circumstances: the batteries of electrically driven forklifts could provide attractive storage functions for renewable electricity storage. The following paper presents an overview of some "environmental background approaches" to show the complexity of this innovative system and to show the value of V2G technology and its application in warehouse logistics.
Keywords: renewable electricity, photovoltaics, warehouse logistics management, v2G
Published in DKUM: 10.07.2015; Views: 1635; Downloads: 223
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