Performance Of Module Research Articles

Thermal Regulation Methods Aimed to Elevate Photovoltaic Panel Performance: A Review

Commercially used solar modules convert about 14 to 24% of sunlight into electrical energy. The remaining energy is kept in the panels which is converted into heat energy and increases the panel temperature. However, the increase in temperature caused by this input reduces the power output of the solar panel, i.e. in crystalline silicon cells it is about 0.40%/°C. And the resulting thermal stress also reduces the panel life. Therefore, it would be a smart solution to dissipate the heat generated on the photovoltaic system by cooling the panels with various methods in order to reduce the solar panel temperature and increase the module performance. This paper presents a summary study to review the significant researches on improving performance of photovoltaic systems. Among these researches, there are studies aiming to reduce the high operating temperature seen on the solar cell surface and to balance the inhomogeneous heat distribution such as cooling of a PV panel with natural and forced liquid and air, heat pipe, phase change material and thermoelectric module. Besides these studies, researches aiming to make optimum use of sunlight by reducing reflection, pollution and photo-angular effects, which are parameters that have weakening effects on the electrical performance of solar cells, are reviewed as well.

A Study on the Performance of Soiled Solar Photovoltaic Panels at Different Tilt Angles in Al Seeb, Oman

Climate and weather conditions greatly affect photovoltaic (PV) module performance and efficiency, particularly in desert environments. Dust accumulation, which significantly reduces power generation efficiency, is currently the main issue facing photovoltaic modules since it affects the return on investment of PV systems. It is believed that the tilt angle of solar PV panels can be helpful in reducing the effect of soiling using the gravitational force experienced by the dust particles, mainly in dry environments. In this work, experimental studies were conducted to investigate the effects of the tilt angle and dust deposition on the electrical power generation performance of photovoltaic modules under weather conditions in Al Seeb, Oman. The study was conducted by exposing solar PV panels to outdoor sunlight for two weeks. Two of the PV panels with fixed and different tilt angles were cleaned on a daily basis, while another panel was left uncleaned. A comparison was made with the panel that was not cleaned for an extended time. Measurements included solar irradiance, solar panel temperature, voltage, and current. The output power and efficiency reached 93.5 W and 24.5%, respectively, for the panel cleaned daily. Furthermore, soiling resulted in an 18.8% power loss. The results showed that the highest output power of 79.75 W was observed at an angle of 25°, with an efficiency of up to 20.5%. Moreover, the power generated was up to 9.8% higher than that at different tilt angles.

Numerical simulation for a suitable electron transport layer of a lead-free CuIn2Se3 based perovskite solar cell and PV module

The high expense of solar cell manufacture and experimentation has led researchers to use numerical simulation. The advantages of simulation-based optimization include the simplicity of use, low cost, and the ability to forecast the ideal parameters that go into producing a cell with the optimum performance. The efficiency of perovskite materials used in solar systems has increased significantly, and they are virtually ready for commercialization. Academics and the scientific community are now interested in lead-free perovskite materials because of the toxic problem and hazardous nature of lead (Pb)-based perovskite materials. In this research, Pb is replaced by copper indium diselinide (CuInSe2). This study simulated, examined, and analyzed the performance of photovoltaic (PV) CuInSe2-based TFSCs with three different electron transport layers: indium sulfide (In2S3), titanium dioxide (TiO2), and stannic oxide (SnO2). SCAPS-1D software was used to model (FTO/TiO2/CuInSe2/Spiro-OMeTAD/Ni), (FTO/SnO2/CuInSe2/Spiro-OMeTAD/Ni), and (FTO/In2S3/CuInSe2/Spiro-OMeTAD/Ni) configurations to determine which one has the highest conversion efficiency. All three electron transport layer (ETL) thicknesses, with absorber and hole-transport (HTL) layer thicknesses, were optimized. Results indicate that, the absorber layer for SnO2 and In2S3 layers must be 3.00µm thick, and for the TiO2 layer it must be 4.00µm thick. Efficiency of 26.17% is revealed with SnO2, whereas Jsc, Voc, and FF, are observed as 43.15mA/cm2, 0.723V, and 83.80%, respectively. While with In2S3, efficiency is revealed as 26.15%, with Jsc, Voc, and FF are observed as 43.17mA/cm2, 0.723V, and 83.68% respectively. Efficiency of 26.65% is revealed by TiO2 with current density (Jsc), open circuit voltage (Voc), and fill factor (FF), which are shown as 43.53mA/cm2, 0.728V, and 83.68%, respectively which was carefully calculated. The device shows highest performance with TiO2 ETL. The maximum extent for Jsc, Voc, FF%, and PCE% during optimal investigation is shown by the generation of supplemental electron-hole pairs under standard conditions by altering the thicknesses of the absorber, hole, and electron transport layers. Parasitic resistances effect on the cell performance indicate that solar cells work effectively with low Rs and high Rsh values. The temperature effect on solar cells shows that as temperature rises, cell performance declines due to increased reverse saturation current and reduced bandgap. Quantum efficiency analysis of three ETL layers found that TiO2 and SnO2 efficiency increased rapidly between 300–400nm, while In2S3 peaked at 300nm and then declined. Simulation results from SCAPS-1D were used to configure PVsyst software for a solar module with 72 cells (2.2 ×1.1m). Module performance and output power were evaluated based on temperature and sun irradiation variations using input from the solar capacitance simulator. The potential of CuIn2S3 as a perovskite material to produce toxicity-free renewable energy is demonstrated by this study.

Bifacial photovoltaic module performance in correlation to cloud conditions, sun spectrum and irradiance enhancement

This study presents the performance behavior of 10° tilted, east and west oriented bifacial photovoltaic (PV) modules during irradiance enhancement (IE). The impact of meteorological parameters on the performance of different bifacial photovoltaic module types was determined. The analysis was done time resolved for irradiance enhancement events as well as for the total annual yield in the period 04/2020–06/2021. A cloud classification was performed for clouds that trigger irradiance enhancements. Irradiance enhancements exceeding 1000 Wm−2 were found to occur only on days with clouds in Vienna (Austria). For 179 irradiance enhancement situations analyzed, 81% of all enhancements happened for cloudiness greater than 0.4 and still 30% for a cloudiness greater than 0.7, the latter resulting also in single enhancement events greater than 1150 Wm−2. Cloud genera preferentially causing irradiance enhancements were identified as Altocumulus and Cumulus clouds. The evaluation of cloud pictures during IE events was done by hand and not automated. By this the position of the sun towards the clouds could be also taken into account. The mechanism of irradiance enhancement compatible to the position of the sun towards the clouds were in accordance with the cloud types Mie-scattering and edge reflections, respectively, or a mix of both. The overall photovoltaic long term performance results showed that the average weighted absolute efficiencies of the bifacial photovoltaic modules were 2%–4% higher than the ones of monofacial standard reference modules. The power output of the bifacial modules was between 17%–24% higher throughout the 15 month period of the investigation compared to monofacial reference modules. This results held independent of orientation while there was a visible seasonal variation, namely 19%–28% more power output in winter, 18%–24% in spring, 16%–25% in summer and 17%–27% in autumn, respectively.

Feasibility of Average Photon Energy (APE) in performance evaluation of PV modules equipped with IR reflecting filter

In this work, we investigate the feasibility of the APE (Average Photon Energy) parameter as a qualitative representation of solar spectra in modeling the performance of PV modules equipped with a filter capable of reflecting parasitic IR irradiance. We evaluate APEs' relation with parasitical absorption of solar irradiance in the structure of PV modules (glass, lamination foil, back sheet), as well as its relation to the calculated temperature of PV modules operating in standard conditions. In our analysis, we employ real-world data of spectral irradiance. Full Text: PDF References B.S. Richards, A. Ivaturi, S.K.W. MacDougall, J. Marques-Hueso, "Up- and down-conversion materials for photovoltaic devices", Proc. SPIE 8438, 843802 (2012), CrossRef A. Ibrahim, M.Y. Othman, M.H. Ruslan, S. Mat, K. Sopian, "Recent advances in flat plate photovoltaic/thermal (PV/T) solar collectors", Renew. Sustain. Ener. Rev. 15, 352 (2011), CrossRef N. Khorrami, M.R. Zargarabadi, M. Dehghan, "A novel spectrally selective radiation shield for cooling a photovoltaic module", Sustain. Ener. Technol. Assess. 46, 101269 (2021), CrossRef G. Nofuentes, C.A. Gueymard, J. Aguilera, M.D. Pérez-Godoy, F. Charte, "Is the average photon energy a unique characteristic of the spectral distribution of global irradiance?", Solar Energy 149, 32(2017), CrossRef A. Andreas, T. Stoffel, NREL Solar Radiation Research Laboratory (SRRL): Baseline Measurement System (BMS), Golden, Colorado (Data), NREL Report No. DA-5500-56488 (1981). CrossRef

Effect of bird dropping deposition on photovoltaic (PV) module performance at different sites

Bird dropping deposition on the front glass plate of a Photovoltaic (PV) module is a critical challenge for output power generation. This research article is proposed to investigate the impact of bird dropping accumulation on PV surface at different sites. The current study includes the effect of bird dropping deposition in terms of physical parameters like gravimetric, electrical and transmittance analysis. The obtained results show how bird dropping settlement at the different sites affect the PV performance through output power generation. Gravimetric analysis depicts the maximum amount (51gm) of bird dropping deposition that occurs on the rooftop and the minimum (21gm) along the roadside, which is a replica of the bird's behavior. As a result, the average maximum power loss (22.1%) on the rooftop while the minimum (12.1%) along the roadside.

Quantifying Measurement Uncertainty in Photovoltaic Module Performance at Standard Test Conditions: A Machine-Based Approach

This paper presents an in-depth analysis of measurement uncertainty in the output parameters of photovoltaic (PV) devices, focusing specifically on measurements conducted under standard test conditions (STC). Accurate characterization of module I-V performance is crucial for PV manufacturers, researchers, and investors alike. The study provides a comprehensive overview of the measurement procedures for both performance and temperature coefficient of PV modules, with a strong emphasis on the detailed calculation of associated uncertainties. Notably, the research was conducted under real-world sunlight conditions, with special attention given to reference devices such as reference cells, modules, or pyranometers, which play a pivotal role in determining overall uncertainty components. By utilizing a diverse array of machines from various sources, the results obtained are applicable across a wide range of measurement configurations. Furthermore, adherence to the ISO/IEC 17025 series of standards ensures a standardized and reliable approach. The novelty of this research lies in its comprehensive approach to uncertainty analysis, encompassing both performance and temperature coefficient measurements under real-world conditions. By providing valuable guidelines for PV module characterization and reliability assessment, particularly in uncertainty estimation, this study contributes significantly to the advancement of photovoltaic technology.

Exploring the performance of a DOI-capable TOF-PET module using different SiPMs, customized and commercial readout electronics.

Time resolution is crucial in positron emission tomography (PET) to enhance the signal-to-noise ratio and image quality. Moreover, high sensitivity requires long scintillators, which can cause distortions in the reconstructed images due to parallax effects. This study evaluates the performance of a time-of-flight (TOF)-PET module that makes use of a single-side readout of a 4x4 3.1x3.1x15 mm3LYSO:Ce matrix with an array of 4x4 SiPMs and a light guide to extract high-resolution TOF and depth of interaction (DOI) information. 
Approach: This study assesses the performance of the detector prototype using the commercially available TOFPET2 ASIC and SiPMs from various producers. DOI and TOF performance are compared to results using custom-made NINO 32-chip based electronics.
Main Results: Using a Broadcom NUV-MT array, the detector module read out by the TOFPET2 ASIC demonstrates a DOI resolution of 2.6 ± 0.2 mm full width at half maximum (FWHM) and a coincidence time resolution (CTR) of 216 ± 6 ps FWHM. When read out using the NINO 32-chip based electronics, the same module achieves a DOI resolution of 2.5 ± 0.2 mm and a CTR of 170 ± 5 ps.
Significance: The prototype module, read out by commercial electronics and using state-of-the-art SiPMs, achieves a DOI performance comparable to that obtained with custom-made electronics and a CTR of around 200 ps. This approach is scalable to thousands of channels, with only a deterioration in timing resolution compared to the custom-made electronics, which achieve a CTR of 140 ps using a standard non-DOI module.

Design and implementation of a low-cost datalogger for solar irradiance and PV module temperature

Photovoltaic module temperature and solar irradiance are two essential parameters that greatly affect the performance of solar plants. The measured information concerning these parameters is needed to size as well as predict future energy production of the plant. These data are often available at hourly intervals or more from meteorological stations and are expensive to acquire depending on the number of data points needed or from websites linked to satellites. Consequently, a method that can provide data at smaller time intervals is required to capture changes in irradiance and temperature. This paper presents a simple and cost-effective datalogger that measures the irradiance, relative humidity, module, and environmental temperatures. It used a 50 W photovoltaic module as an irradiance sensor. LM35 and DHT22 sensors were used for PV module and ambient temperature measurements, respectively. An interrupt service routine function implemented with the Arduino Mega microcontroller ensured a repetitive switching sequence of parallel resistance networks and the storage of desired current and voltage coordinates every 4s from 6 a.m. to 6 p.m. The irradiance computed was based on power at the maximum point with a load-switching network and in a short-circuit condition. The entire cost of the datalogger system was 153.12 euros, and major results show that the power at maximum power point method and ambient temperature give the best estimate of the photovoltaic module temperature. Consequently, the irradiance determined by the maximum power point method with ambient temperature can be used to evaluate the performance of photovoltaic modules using the single-diode model.

Design of Comprehensive Monitoring on Hybrid Photovoltaic and Thermoelectric Generator Using IoT

The study aims to design and develop a more efficient measurement monitoring system based on influential parameters for the performance of hybrid PV and TEG modules using IoT with the Thingspeak application. The parameters measured include the PV top and bottom surface temperatures and output current and voltage, the surface temperatures of the TEG's hot and cold sides, their respective current and voltage outputs, air humidity, and solar intensity. This IoT-based monitoring system experimental method utilizes two types of PV, polycrystalline and monocrystalline, each rated at 50 Wp, in a hybrid configuration with 5 TEG modules attached to the back of the solar panel. The monitoring design results indicate that sensor measurements were accurate and data readings were reliable. The temperature difference between the two sides of the TEG was measured up to 21.7°C, and the hybrid efficiency of the monocrystalline PV with TEG showed better results compared to the polycrystalline setup, achieving optimum efficiency above 6%, with the PV surface temperature maintained at an average of 50°C. Additionally, IoT monitoring revealed the effect of air humidity on TEG performance: lower air humidity resulted in a larger ?T, peaking at 21.7°C with humidity at 39.1%. Therefore, this study recommends using IoT technology for observational data collection on system performance, particularly for PV and TEG, with sensor component modifications tailored to the characteristics of the targeted sensor object.

Novel Indoor Educational I-V Tracer for Photovoltaic Modules

The renewable energy market, particularly the photovoltaic sector, has experienced significant growth over the past decade. Higher education institutions must play a vital role in the training of professionals, which the sector is currently demanding and will continue to require in the future. A pivotal resource for understanding the performance of PV modules is the experimental extraction of the characteristic I-V curve in laboratory practices. This paper presents an innovative and low-cost I-V curve tracer which can be used in indoor laboratories for teaching purposes. The described measurement system presents the novelty of helping form an energy-harvesting IC to force a sweep of the voltage from values close to zero to the open voltage circuit (Voc). An Arduino Micro board interfaces the implemented electronics and a LabVIEW-based monitoring and control program. The system proved its reliability and accuracy when it was compared to a calibrated commercial I-V tracer. The experimental results show that for a low-power PV module illuminated by a lamp, the proposed I-V tracer only deviated 1.3% from the commercial one in measurements of the maximum power.

Students’ use of virtual learning environment resources and their impact on student performance in an econometrics module

Abstract We examine the relationship between students’ engagement with a range of virtual learning environment resources and their module performance, focusing on a relatively large second year undergraduate econometrics module. The analysis offers a useful contribution to the literature on the relationship between virtual learning environment engagement and student performance through consideration of a broader range of virtual learning environment resources than is typically considered in analyses to date, also through using a wider range of control variables. The setting for the analysis is also of interest as data relate to the 2020/2021 academic year in which there was a greater onus on the provision of online learning resources. Further, while much literature considers student performance on economics principles modules, there is much less literature focusing on econometrics module performance. Results suggest that there are different relationships between virtual learning environment engagement and student performance, depending on the virtual learning environment resources under consideration. Generally, engagement with virtual learning environment resources that encourage more active learning is associated with better student module performance. Similarly, engagement with online formative assessments with immediate feedback is associated with student module success.

Development of an Indoor Line Scanning System for Photovoltaic Modules Performance Characterization

Uganda’s interest in using solar energy for various applications began 20 years ago. However, there have been numerous reports by the public over the poor performance of the photovoltaic (PV) modules during their operations. This study determined the performance of selected PV modules openly sold in the Ugandan markets. The low-cost indoor line scanning system developed using locally available materials was used to assess the performance of each of the solar cells in the PV module by determining their photogenerated currents. In addition, the electrical characteristics of the PV modules were determined using the outdoor characterization method, which assumed the actual operation of the PV modules under direct sunlight. From the indoor line scans, the percentage of performing solar cells in the three PV modules of single-crystalline silicon (c-Si), multi-crystalline silicon (mc-Si), and amorphous silicon (a-Si) technologies were determined as 79%, 61%, and 95% respectively. The outdoor characterization results revealed that the c-Si, mc-Si, and a-Si PV modules had measured maximum power outputs of 18.5 W, 19.0 W, and 18.9 W, respectively and these were lower than the rated power values of 20 W. The line scan results had a direct relationship with the measured power output of the PV module, which implied that solar cells mismatch, affected the performance of the PV modules by lowering their performance. This developed testing system is affordable for developing countries with limited testing systems and would in the long run contribute to significant increase in the deployment of PV technology in Uganda since only performing PV modules would be allowed into the open market.

Study of Cooling Performance of Liquid-Cooled EV Battery Module According to the TIM Compression Ratio

AbstractThis study examines the coolant and heat flows in electric vehicle (EV) battery pack that employs a thermal interface material (TIM). The overall temperature distribution of the battery pack that consists of many battery modules is precomputed based on the cooling circuit design, and the battery module that is most strongly influenced by cooling circuit is selected. To investigate the detailed effects of the TIM’s performance, we measure its thermal conductivity based on its compression ratio and consider the detailed shape of the battery cell module for incorporating the TIM’s thermal conductivity in the battery assembly. The TIM, which functions as part of the cooling system within the confined space of the battery cell module, is included in the CFD analysis to assess the effect of thermal conductivity variation resulting from the compression ratio of the TIM on the cooling performance of the battery pack. Various cases of confined spaces in the battery module are compared to optimize the cooling efficiency of the EV battery pack.

Enhanced photovoltaic performance and longevity of perovskite modules via interface engineering of transport layer

Abstract This research presents interfacial engineering of large–area perovskite modules. The quality of the interface between the electron transport layer(ETL) and the perovskite layer are studied, because it significantly affects the optoelectronic performance of large–area module devices. In large–area fabrication, film uniformity and interfacial quality are critical, as the ETL/perovskite interface governs both electron extraction and transport efficiency, while also affecting the uniformity and crystallinity of the perovskite. To overcome these issues, using picosecond laser technique (P1,P2,P3) to fabricate large–area modules, integrating monolithic cells in series. Planar SnO2 and mesoporous TiO2 ETL are prepared. Results show that meso–type ETL structures are better suited for large–area modules. The modules with meso–type TiO2 exhibit fewer shunting issues and stronger emission in electroluminescence images. Photoluminescence mapping indicates improved structural uniformity of perovskite. The perovskite module with meso–type TiO2 achieve power conversion efficiency of 18.2% (4cm2) and maintain 80% of initial efficiency after 700 hours.

Influence of Leg Geometry on the Performance of Bi2Te3 Thermoelectric Generators

This study analyzed the significant performance using COMSOL Multiphysics software of thermoelectric modules (TEMs) fabricated from aluminium oxide (Al2O3), copper (Cu), and bismuth telluride (Bi2Te3) materials, with a particular focus on investigating various leg geometries. The TEM design had Al2O3 for insulation, Cu for conducting, and Bi2Te3 for TE legs among the Cu. Investigated the influence of square and rectangular TE legs with heights of 2.0, 2.75, and 3.5 mm on critical parameters such as the normalized current density, electric potential, temperature gradient, and total internal energy within the TEM. Furthermore, the impact of varying thicknesses in the insulator and conductor layers of the TEM was explored. The results consistently demonstrated that the square leg geometry, particularly when configured with a height of 2.75 mm, outperformed other leg geometries. Consequently, it is suggested to adopt a square-shaped Bi2Te3 TEM measuring 1 mm × 1 mm × 2.75 mm with a 0.50 mm Al2O3 thickness and 0.125 mm Cu thickness during the manufacturing process. Investigate how temperature differences in TE device leg design are influenced by parameters such as the Seebeck coefficient (S), thermal conductivity (k), and electrical conductivity (σ). At lower temperatures, modeling reveals lower electrical conductivity and enhanced thermal conductivity, highlighting the significance of S = ± 2.37×10⁻⁴ V/K. This illustrates the high potential of TEM for applications in thermoelectric generator (TEG) manufacturing.

Research on the thermal management performance of battery module with heat pipe in the full-scenarios and multiple dimensions

Research on the thermal management performance of battery module with heat pipe in the full-scenarios and multiple dimensions

An Automatic Optimization Method for Electrical and Thermal Performance of Stacked DBC Power Module

An Automatic Optimization Method for Electrical and Thermal Performance of Stacked DBC Power Module

Reliable Prediction of Solar Photovoltaic Power and Module Efficiency using Bayesian Surrogate Assisted Explainable Data-Driven Model

This study proposes a Bayesian surrogate-driven explainable deep neural network model to predict and interpret the module efficiency and maximum output power of three commercially available photovoltaic modules: monocrystalline silicon, polycrystalline silicon, and amorphous silicon during the winter season. In addition, the influence of the photovoltaic material and ambient conditions on the predicted power and module efficiency is investigated. The model inputs include solar irradiance, module material (monocrystalline, polycrystalline, and amorphous silicon), season of the year (months), and time of day (morning to evening). Experiments were conducted on these three modules during the winter using data from Rawalpindi, Pakistan. These data were then fed into the deep neural network model to train and yield predictions. Several preprocessing techniques such as logarithmic transformation, square root, cube root, reciprocal, and exponential transformations are employed to improve the linearity of distributed data. For hyper-parameters optimization, Gaussian process, gradient boost regression trees, and random forest are used. The results show that the optimal deep neural network using random forest surrogate model along with square root and exponential transformation is able to predict the maximum power output and module efficiency of the considered photovoltaic modules for the entire investigated period with a correlation coefficient, R2 = 0.998. The least accurate model (R2=0.991) is a Gaussian process using simple data distribution. These results hold valuable insights for predicting and optimizing the performance of other solar photovoltaic modules in various climates and different seasons of the year.

Assessing water resource vulnerability based on remote sensing data-enhanced SWAT+ and High-Resolution precipitation data

Climate change and human activities have significantly impacted the global water cycle, increasingly threatening water security across various sectors. By improving the performance of hydrological models in simulating the water balance, including precipitation and evapotranspiration, we can better support decision-making for regional water resource management and the deployment of climate change adaptation measures. This study aims to enhance the simulation performance of the vegetation growth module in the SWAT + model and reduce its uncertainty by dynamically updating the model’s data files with satellite-derived leaf area index and phenology data. Additionally, this study modified the weather station allocation mechanism in SWAT + to fully utilize the high-resolution meteorological data grids. The simulation results show that the enhanced SWAT + model achieved a Nash-Sutcliffe Efficiency (NSE) between 0.84 and 0.90 and a PBIAS of less than 6 % for daily streamflow simulations at four hydrological stations in the Weihe River Basin. The enhanced SWAT + model’s water balance simulation results for the Weihe River Basin were used to analyze the vulnerability of water resources within the basin. The results indicate that the Qinling region, benefiting from its well-developed forest ecosystems, has the lowest green water vulnerability. The overall blue water vulnerability of the basin reached 1.12, suggesting that during periods of insufficient precipitation or intense evaporation, blue water resources may not meet the demands of agriculture, industry, ecology, and residential use. Among these, agricultural water use exhibits the highest vulnerability. Efficient irrigation technologies can be employed to improve irrigation water use efficiency, and the use of treated reclaimed water for agricultural irrigation can be promoted to reduce the demand for fresh blue water resources.