With half-cut photovoltaic (PV) modules being the dominant technology on the market, there is an increasing necessity for accurate modeling of this module type. Circuit simulators such as Simulink are widely used to study different topics regarding photovoltaics, often employing a solar cell block available from the Simcape library. The purpose of this work is to validate this model against measurements for a partially shaded half-cut PV module. Diverse shading scenarios are created by varying the number of shaded substrings, the number of shaded solar cells in the substring, and the shading level. For every shading scenario, the PV module’s I-V curve is measured, along with in-plane irradiance, air temperature, and module temperature. A comprehensive evaluation of simulation accuracy is presented. The results confirm a high accuracy of the model with mean nRMSE values of 2.2% for I-V curves and 2.8% when P-V curves are considered. It is found that the simulation errors tend to increase when increasing the number of shaded substrings. At the same time, no obvious dependency of simulation accuracy on the shading level or the number of shaded solar cells in the substring is found.

Currently, monitoring systems in various fields rely on commercial technologies that can be costly and, more critically, lack integration with remote management solutions. These systems often present accessibility challenges for researchers and professionals who require data collection for in-depth analysis. In addition, the deployment of sensing devices within more complex networks can be difficult, hindering the scalability and effectiveness of these technologies. This work presents a flexible smart multitechnological datalogger based on an Internet of Things (IoT) structure that utilizes numerous Low Power Wide Area Network solutions, allowing remote analysis of the phenomenon and reducing the installation and management complexity. The designed system was developed at a lower cost than state-of-the-art dataloggers and tested in the hydric monitoring scenario. The results indicate that the system can sustain remote monitoring operations for a significant duration without frequent battery replacements, making it suitable for applications that require extended autonomous deployments.

We present a numerical study on resistance fluctuations in a series of nanowire‐based grids. Each grid is made of GaAs nanowires arranged in parallel with metallic contacts crossing all nanowires perpendicularly. Electrical properties of GaAs nanowires known from previous experimental research are used as input parameters in the simulation procedure. Due to the nonhomogeneous doping, the resistivity changes along nanowire. Allowing two possible nanowire orientations (“upwards” or “downwards”), the resulting grid is partially disordered in vertical direction which causes resistance fluctuations. The system is modeled using a two‐dimensional random resistor network. Transfer‐matrix computation algorithm is used to calculate the total network resistance. It is found that probability density function (PDF) of resistance fluctuations for a series of nanowire grids changes from Gaussian behavior towards the Bramwell‐Holdsworth‐Pinton distribution when both nanowire orientations are equally represented in the grid.

This paper presents a comprehensive analysis of the solar cell, covering its equivalent circuit, operating principles, and the effects of temperature and irradiance changes on its current-voltage characteristic. Additionally, the Maximum Power Point Tracking (MPPT) techniques used to determine the maximum current and voltage product under various irradiances are described, and the efficiency of different MPPT techniques is compared to demonstrate the operation of a solar cell. The study also investigates the impact of shading on solar modules by calculating the power loss on two parallel-connected solar panels with different orientations under the same irradiation conditions. The results demonstrate that the Incremental Conductance (IC) algorithm has the best efficiency, followed by Perturb and Observe (P&O) and Hill Climbing (HC) algorithms, under different irradiation conditions. Furthermore, the power loss of the two solar modules with different orientations is significantly affected by the difference in irradiance received by each module. The novelty of this research lies in the comparison of different MPPT techniques under different irradiation conditions and the demonstration of the impact of shading on solar modules with different orientations. This study provides valuable insights for designing and optimizing solar energy systems in real-world conditions, and offers a unique perspective on a well-researched area.