Marcin Walczak

The operating temperature of a photovoltaic module strongly affects its electrical performance, while direct temperature measurements may be influenced by sensor placement, thermal resistance, and measurement delay. This paper investigates the use of open-circuit voltage for estimating the temperature of a photovoltaic module under varying irradiance conditions. Two standard-based approaches, derived from IEC 60904-5 and EN 50530, are compared with a proposed empirical model in which the temperature sensitivity of the open-circuit voltage is allowed to vary with irradiance. The experimental study was carried out using a water-cooled 10 W polycrystalline PV module. A total of 135 I–V characteristics were measured at 15 irradiance levels between 72 and 834 W/m² and at nine module temperatures between 30 and 70 °C. The parameters of all investigated models were identified from the experimental data, and their temperature estimation performance was evaluated over the complete measurement range. The standard-based methods provided satisfactory results mainly at medium and high irradiance levels, whereas their accuracy decreased at low irradiance. The proposed model accounted for the irradiance dependence of the open-circuit voltage temperature sensitivity and reduced the estimation error over the investigated operating range. The obtained RMSE was 0.26 °C, with a mean absolute error of 0.21 °C and a maximum absolute error of 0.82 °C. These results indicate that the proposed approach can provide a simple method for indirect PV module temperature estimation in monitoring and control applications.

The gyroid minimal surface is one type of triply periodic minimal surface (TPMS). TPMS is a minimal surface replicated in the three main directions of the Cartesian coordinate system. The minimal surface is a surface stretched between two objects, known as the smallest possible area (e.g., a soap bubble with a saddle shape stretched between two parallel circles). The complicated shape of the TPMS makes its production possible only by additive methods (3D printing). This article presents the results of experimental studies on heat transfer and flow resistance in a heat exchanger made of stainless steel. The heat exchange surface, a TPMS gyroid, separates two working media: hot and cold water. The water flow rate was varied in the range from 8 kg/h to 25 kg/h (Re = 246–1171). The water temperature at the inlet to the exchanger was maintained at a constant level of 8.8 ± 0.3 °C and 49.5 ± 0.5 °C for cold and hot water, respectively. The effect of water flow rate on the change in its temperature, the heat output of the exchanger, the average heat transfer coefficient, pressure drop, and overall resistance factor was presented.

This paper presents information on ionic liquids (ILs) and explores their potential applications in heat exchange systems. Basic information on ionic liquids and their selected thermophysical properties is presented in a manner that facilitates their use in future research. The physical properties of IL that are important in the area of heat exchange are described in detail, with particular emphasis on heat exchange in flow. Issues related to the melting point, specific heat, thermal conductivity coefficient, and viscosity of selected ionic liquids, as well as the effect of temperature on their changes, are discussed. The physical properties of IL are compared with the physical properties of water treated in heat exchange as a reference substance. The issues of creating aqueous solutions of ionic liquids and the effect of the amount of water on the physical properties of the resulting solution are discussed. It is demonstrated that selected ionic liquids can be considered an alternative to traditional working liquids commonly used in heat exchange systems.

Small-signal models of a buck converter working in the discontinuous conduction.mode that are available in the literature usually can be divided into those which contain.a single pole and refer to non-ideal converters and those that describe ideal converters and.contain two poles. Even though the models are noticeably different they have been validated.through simulations and measurements, which suggests both of them are correct. The.purpose of this paper is to provide a comprehensive comparison of the existing models with.transient simulations done in OrCAD software and through measurements, to show that both.of the mentioned models are true for a specific set of converter parameters, and to propose.a two-pole, control-to-output and input-to-output transfer functions of a non-ideal buck.converter, that can be used in any buck converter working in discontinuous conduction mode.

Designing a maximum power point tracking system (MPPT) can raise many questions when it comes to choosing the best converter and algorithm for the job. The number of possible solutions can be overwhelming, especially when it comes to MPPT algorithms. New algorithms are often tested in simulation environments only, where the accuracy and speed of a single measurement (i.e., in a single step) are usually assumed and sometimes unintentionally exaggerated. In practice, even if the algorithm is fast, its speed is limited by other factors. This article emphasizes the time limitations that are related to converter parameters and that naturally exist in all maximum power point tracking systems. Additionally, the article proposes a measurement method that enables voltage and current measurements with good accuracy for different transients that exist at the input and output of DC–DC converters.

Research related to photovoltaic panels comprises different topics starting with modelling solar cells, finding new maximum power point tracking (MPPT) algorithms, testing existing ones or designing of DC/DC converters for MPPT systems and microgrids that incorporate photovoltaic energy sources. In each of the examples above a deep knowledge of photovoltaic panels is required, as well as a reliable measurement system that can deliver continuous, stable light with enough power to meet standard test conditions (STC) and that can ensure repeatable results. Therefore this paper presents a low-cost solar simulator with a microcontroller-based measurement system, that can be used for various measurements of low-power photovoltaic panels.

The main goal of this study was to derive small-signal models of the input characteristics of buck, boost, and flyback converters working in continuous conduction mode (CCM) and discontinuous conduction mode (DCM). The models presented in the paper were derived using the separation of variables approach and included the parasitic resistances of all converter components. The paper features a discussion about the limitations of the model accuracy. The presented characteristics were obtained by calculation and verified by measurements. The input characteristics of converters are essential in the design of converters used in Power Factor Correction systems as well as in maximum power point tracking systems (MPPT).

DC/DC converters are widely used in photovoltaic (PV) systems to maximize the power drained from solar panels. As the power generated by a PV panel depends on the temperature and irradiance level, a converter needs to constantly modify its input resistance to remain at the maximum power point (MPP). The input resistance of a converter can be described by a simple equation that includes the converter load resistance and the duty cycle of the switching signal. The equation is sufficient for an ideal converter but can lead to incorrect results for a real converter, which naturally features some parasitic resistances. The goal of this study is to evaluate how the parasitic resistances of a converter influence its input resistance and if they are relevant in terms of MPPT system operation.

The article presents the problems of diagnostics of low-power solar power plants with the use of the three-valued (3VL) state assessment {2, 1, 0}. The 3VL diagnostics is developed on the basis of two-valued diagnostics (2VL), and it is elaborated on. In the (3VL) diagnostics, the range of changes in the values of the signals from the 2VL logic was accepted for the serviceability condition: state {1_2VL}. This range of signal value changes for logic (3VL) was divided into two signal value change sub-ranges, which were assigned two status values in the logic (3VL): {2_3VL}—serviceability condition and {1_3VL}—incomplete serviceability condition. The state of failure for both logics applied of the valence of states is interpreted equally for the same changes in the values of diagnostic signals, the possible changes of which exceed the ranges of their permissible changes. The DIAG 2 intelligent system based on an artificial neural network was used in diagnostic tests. For this purpose, the article presents the structure, algorithm and rules of inference used in the DIAG intelligent diagnostic system. The diagnostic method used in the DIAG 2 system utilizes the method known from the literature to compare diagnostic signal vectors with the reference signal vectors assigned. The result of this vector analysis is the metric developed of the difference vector. The problem of signal analysis and comparison is carried out in the input cells of the neural network. In the output cells of the neural network, in turn, the classification of the states of the object’s elements is realized. Depending on the condition of the individual elements that make up the object, the method is able to indicate whether the elements are in working order, out of order or require quick repair/replacement.

Large-signal input characteristics of three DC–DC converter types: buck, boost and flyback working in the discontinuous conduction mode (DCM), obtained by precise large signal PSpice simulations, calculations based on averaged models and measurements are presented. The parasitic resistances of the converter components are included in the simulations. The specific features of the input characteristics in theDCMand the differences between the continuous conduction mode (CCM) and DCM are discussed.