Solar System Research Articles

The Experimental Investigation of the Transient Regime of Solar Electric-Vapor Compression Refrigeration Systems under Desert Weather Conditions

The Experimental Investigation of the Transient Regime of Solar Electric-Vapor Compression Refrigeration Systems under Desert Weather Conditions

Novel Insights on the Dust Distribution in the Zodiacal Dust Cloud from PSP/WISPR Observations at Large Elongations

The Wide-Field Imager for Solar Probe (WISPR) on the Parker Solar Probe (PSP) mission maps the brightness produced by the zodiacal dust cloud (ZDC) from an historically unprecedented viewpoint. The brightness results from the scattering of photospheric light by dust particles in the ZDC, and is called zodiacal light (ZL). We exploit the PSP nominal science encounters in orbits 10 through 16 for an in-depth study of the location and brightness evolution of the symmetry axis of the ZL in images taken with the WISPR outer telescope (WISPR-O). During these 11 day encounters, PSP covered heliocentric distances between 0.25 and 0.0617 au (∼53.78−13.28 R ☉) and ∼255° in helioecliptic longitude from within the orbital plane of Venus. The unique WISPR-O viewpoint, which comprises line-of-sight elongations of 80° ± 27°, has led to further insights about the ZDC. Namely, we find that the gravitational pull of the planets warps the ZDC symmetry plane and shifts the ZDC towards the solar system barycenter, creating an east–west asymmetry in the ZL brightness. Additionally, our analysis provides the first consistent observational evidence of a circumsolar dust enhancement resulting from the sublimation of dust grains at ∼25 R ☉. Overall, the WISPR observations from the PSP platform are opening a new window in the remote sensing of the ZDC.

A Three-Step Weather Data Approach in Solar Energy Prediction Using Machine Learning

Solar energy plays a critical part in lowering CO2 emissions and other greenhouse gases when integrated into the grid. Higher solar energy penetration is hindered by its intermittency leading to reliability issues. To forecast solar energy production, this study suggests a three-step forecasting method that selects weather variables with a moderate to strong positive correlation to solar radiation using Pearson correlation coefficient analysis. Low-level data fusion is used to combine weather inputs from a reliable local weather station and an on-site weather station, significantly improving the forecasting model’s accuracy regardless of the machine learning method used. Weather data was obtained from the Kisanhub Weather Station located in Cranfield University, UK and the meteorological station in Bedford, UK. In addition, PV power supply data was obtained from four solar plants. Using the Regression Learner app in MATLAB, the proposed architecture is tested on a utility scale solar plant (1 MW), showing a 6% and 13% prediction accuracy improvement when compared to solely using data from the on-site and local weather station respectively. It is further validated using data from three residential rooftop solar systems (8 kW, 10.5 kW and 15 kW), achieving root-mean square values of 0.0984, 0.0885, and 0.1425 respectively. The data was pre-processed using both rescaling and list-wise deletion methods. Training and testing data from the 1 MW solar plant was divided into 75% and 25% respectively, while 100% of the residential rooftop solar plants was used for validation.

Heat transfer analysis of solar distillation system by incorporating nano‐enhanced PCM as thermal energy‐storage system

Heat transfer analysis of solar distillation system by incorporating nano‐enhanced PCM as thermal energy‐storage system

Design and assessment of a concentrating solar thermal system for industrial process heat with a copper slag packed-bed thermal energy storage

Decarbonising the industrial sector is a key part of climate change mitigation targets, and Solar Heat for Industrial Process (SHIP) is a promising technology to achieve this. However, one of the drawbacks of SHIP systems is that they rely on an intermittent energy source. Therefore, sensible energy storage has emerged as a potential solution. In addition, solid byproducts have been proposed as a low-cost but effective material for thermal energy storage (TES). This work presents a SHIP system model coupled with a copper slag-packed-bed TES (PBTES) model using air as heat transfer fluid. The TES has been implemented to preheat the makeup water of the tank where steam is generated. A system design was carried out using a parametric analysis to find a solar field size and a corresponding TES volume. The resulting system was simulated, and the operating variables were analysed in detail. The results show that it is possible to generate 20% more energy due to the storage system. Additionally, a techno-economic analysis indicates that the SHIP with PBTES system results in a payback period of 14 years and a savings of CO2 emissions of 30tCO2.

Performance Analysis of a 50 MW Solar PV Installation at BUI Power Authority: A Comparative Study between Sunny and Overcast Days

Ghana, being blessed with abundant solar resources, has strategically invested in solar photovoltaic (PV) technologies to diversify its energy mix and reduce the environmental impacts of traditional energy technologies. The 50 MW solar PV installation by the Bui Power Authority (BPA) exemplifies the nation’s dedication to utilizing clean energy for sustainable growth. This study seeks to close the knowledge gap by providing a detailed analysis of the system’s performance under different weather conditions, particularly on days with abundant sunshine and those with cloudy skies. The research consists of one year’s worth of monitoring data for the climatic conditions at the facility and AC energy output fed into the grid. These data were used to analyze PV performance on each month’s sunniest and cloudiest days. The goal is to aid in predicting the system’s output over the next 365 days based on the system design and weather forecast and identify opportunities for system optimization to improve grid dependability. The results show that the total amount of AC energy output fed into the grid each month on the sunniest day varies between 229.3 MWh in December and 278.0 MWh in November, while the total amount of AC energy output fed into the grid each month on the cloudiest day varies between 16.1 MWh in August and 192.8 MWh in February. Also, the percentage variation in energy produced between the sunniest and cloudiest days within a month ranges from 16.9% (December) to 94.1% (August). The reference and system yield analyses showed that the PV plant has a high conversion efficiency of 91.3%; however, only the sunniest and overcast days had an efficiency of 38% and 92%, respectively. The BPA plant’s performance can be enhanced by using this analysis to identify erratic power generation on sunny days and schedule timely maintenance to keep the plant’s performance from deteriorating. Optimizing a solar PV system’s design, installation, and operation can significantly improve its AC energy output, performance ratio, and capacity factor on sunny and cloudy days. The study reveals the necessity of hydropower backup during cloudy days, enabling BPA to calculate the required hydropower for a consistent grid supply. Being able to predict the daily output of the system allows BPA to optimize dispatch strategies and determine the most efficient mix of solar and hydropower. It also assists BPA in identifying areas of the solar facility that require optimization to improve grid reliability.

Influence of different flow models on numerical simulation of solar updraft tower

Solar updraft tower is a new kind of solar heat utilization technology. In the numerical simulation of solar updraft towers, selecting different flow models will affect the accuracy of prediction results. To improve the reliability of the numerical simulation results of the solar updraft tower, this paper uses the solar load model is used to simulate the local conditions of Hohhot, Inner Mongolia Autonomous Region, China at different times, and adds the ambient crosswind air domain to simulate the operation of the device under the actual environmental conditions. Laminar flow, Re-Normalisation Group (RNG), transition, and k-omega shear stress transport (SST) models were selected according to the Reynolds number corresponding to the characteristic length of the system at different positions to simulate and predict the flow field in the solar updraft tower heat collection system, and the results were compared with the test data. The results show that in the simulation of Hohhot at 13:00 and 17:00 on July 19, compared with the RNG model, the relative errors of the calculated data and experimental data of the transition model are reduced by 1.04% and 0.1%, respectively. The surface temperature distribution of the absorber is more consistent with the actual physical law. The superiority of the transition model in the numerical simulation of solar updraft tower is verified.

Comparative assessment of various MPPT algorithms for solar photovoltaic systems under dynamic shading conditions

Comparative assessment of various MPPT algorithms for solar photovoltaic systems under dynamic shading conditions

A novel distributed solar refrigeration system based on evacuated U-tube solar collector and elastocaloric refrigerator

A novel distributed solar refrigeration system based on evacuated U-tube solar collector and elastocaloric refrigerator

Research and application of a novel graph convolutional RVFL and evolutionary equilibrium optimizer algorithm considering spatial factors in ultra-short-term solar power prediction

With the increasing proportion of photovoltaic power generation, solar power prediction systems have become more important. Accurate photovoltaic power prediction can assist the grid dispatch department in formulating effective power scheduling plans, improving grid stability and the capacity to accommodate solar energy. To address the challenges in solar power generation forecasting, the paper proposes a new neural network model called Graph Convolutional Random Vector Functional Link (GCRVFL). The output layer of this model includes both nonlinear transformed features from the hidden layer and the original input features, while also considering the spatial characteristics among photovoltaic sites. Furthermore, Singular Spectrum Analysis (SSA) is utilized to decompose the original solar power time series, extracting different component sequences from the photovoltaic power time series. Opposite based learning and cross-mutation are employed to improve the original Equilibrium Optimizer (EO) algorithm, resulting in an Evolutionary Equilibrium Optimizer (EEO) algorithm. The EEO algorithm is employed to optimize the weight threshold of GCRVFL, leading to a novel photovoltaic power prediction model called SSA-EEO-GCRVFL. Through four datasets and eight control experiments, it can be observed that the proposed model achieves the best predictive performance and is capable of fulfilling the task of photovoltaic power prediction.

Unexpected mineral impact on organic evolution during simulated aqueous alteration in asteroids

The presence of organic matter in carbonaceous chondrites provides valuable information about the early composition of the Solar System. Although they are considered primitive, the majority of these chondrites have undergone secondary processes subsequent to their formation. These processes, such as aqueous alteration, have altered their composition. The effect of aqueous alteration on minerals is well known, but the effect on organic matter and/or on an organo-mineral system have been little studied. Here, we report experimental results devoted to investigate the chemical evolution of a hypothetical initial chondritic material subjected to hydrothermal alteration under reducing conditions at low-temperature. The mixtures consist of different anhydrous minerals (peridot, feldspar, troilite) together with hexamethylenetetramine (HMT) chosen as a model molecule inherited from the interstellar grains. After different times at 80 °C, the large molecular diversity formed is highly influenced by the presence and the nature of the minerals, as highlighted in particular by the evolution of the amide produced. The presence of minerals in the mixture appears to influence the reactivity of the system more through the formation of salts and chelates than through surface adsorption mechanisms. The most pronounced effect is observed in the presence of troilite, both in the degradation of HMT and in the abundance of amides formed. The study of the mutual influence of minerals and organic matter, and their intrinsic transformations in the media during the processes, could help to understand about the origin of organic molecules observed in carbonaceous chondrites.

A Comprehensive analysis of energy, exergy, economic and environment on integrated solarcombined cycle with various HTFs and thermal storage

Energy and exergy analysis are considered as important tools for the thermodynamic assessment of any power plant. The utilization of solar energy in electricity generation is progressively increasing day by day due to various issues associated with conventional power plants. In recent times, solar systems in integration with conventional power plants have emerged as popular and optimal solution. The current integrated solar combined cycle (ISCC) involves integrating a 15 MW linear Fresnel reflector with the existing 328.10 MW combined cycle power plant situated in North India. The proposed study examined the thermodynamic performance (energy and exergy) of ISCC and cascade thermal storage. The exergy loss in solar system, combined cycle, and thermal storage is quantified, followed by a comparative analysis of the impact of integrating the solar system and thermal storage on the exergy loss within the combined cycle plant. The results indicate that the collector-receiver experience the highest exergy loss at 69.41%, which is further reduced by 1.82% and 3.39% by employing therminol oil and molten salt, respectively, in thermal storage within the solar system. Additionally, integration of solar system & thermal storage with conventional system showed improvement in second law efficiency. The overall exegetic efficiency of the power system is improved by 1.38% and 3.12% utilizing molten salt as HTF with two-tank system and cascade TES respectively. CO2 emissions are reduced by 97,020 tons per annum with molten salt, which serves as a superior HTF compared to water. Cascade TES systems reduce a greater amount of CO2 emissions compared to two-tank TES systems, amounting to 172,260 tons per annum.

Microstructures of iron meteorites

Abstract Meteorites originate from the early phase of our solar system and are wonderfully undefined and inhomogeneous. In terms of its composition and microstructure, one single meteorite has quite a few surprises in store. The iron meteorite microstructure depends essentially on the initial solidification of the melt in a larger asteroid or minor planet. The solidification process itself is a function of local element concentrations and the very slow cooling rate. Various collisions in space resulted in the fragmentation of the asteroids and the deformation of the microstructure. However, whether visible microstructural changes occur or not depends on the microstructure itself. And finally, corrosion may also occur in the Earth’s atmosphere. An attempt is made to explain the different microstructures on the example of three iron meteorites, namely those found in Canyon Diablo, Gebel Kamil, and Dronino.

Boosting the effectiveness of a cutting-edge Ca3NCl3 perovskite solar cell by fine-tuning the hole transport layer

Ca3NCl3 has unique electrical and optical properties and shows great potential as an absorber for solar cells, offering a promising solution for enhancing efficiency and reducing costs. To determine the best device layout, this study uses a device combination of Ag/FTO/ETL/Ca3NCl3/HTL/Ni, including seven HTLs and one ETL with the SCAPS-1D simulator. To improve device configuration, consider variables including thickness, temperature, doping density, defect density, and series and shunt resistance. After optimizing device parameters, the Ag/FTO/SnS2/Ca3NCl3/MoO3/Ni device outperformed the other 6-HTLs (Cu2O, CuI, CuSCN, NiO, CuSbS2, and P3HT) based devices with a power conversion efficiency (PCE) of 28.13 %, an open circuit current (VOC) of 1.36 V, a short circuit current density (JSC) of 22.892 mA/cm2, and a fill factor (FF) of 90.36 %. This proposed solar cell has exceptional performance compared to conventional thin-film solar cells, highlighting Ca3NCl3 as an appealing solution for solar energy systems while reducing toxicity issues.

Hardware in the loop testing of converter control in solar PV and BESS based islanded microgrid

Over the past decades, microgrids have garnered significant attention due to their ability to offer resilient power supply and efficiently integrate renewable energy sources (RESs). The test model includes an islanded microgrid having common voltage source converter for solar photovoltaic and battery energy storage system, characterized by low inertia. To minimize the effect of reduced inertia caused by lack of synchronous generators and also to cope up with the variation in power output from different renewable energy sources, an adaptive virtual inertia and damping based control, is incorporated through voltage source converter control, utilizing swing equation of the synchronous generator. However, it is imperative to verify the proposed control strategy before implementation in an actual plant. In that direction, this paper discusses the practicality of the proposed control in the real-time using Controller Hardware-in-the-Loop (CHIL) platform. So, the plant is built in real time simulator OP4512 and the proposed control is implemented using practical microcontroller TMS320F28379D. Subsequently, configuration and modelling of ADC and EPWM are explained. CHIL testing platform demonstrates flawless compatibility with the converter control, having a system model running in real time. Simulation results are compared with that of HIL results for various loading configurations, hence proving the efficacy of the proposed control strategy.

Simulation study on thermal performance of solar coupled air source heat pump system with phase change heat storage in cold regions

The development of efficient and clean heating technologies is profoundly significant for the reduction of carbon emissions in cold regions. This paper puts forth a novel solar-coupled air source heat pump system integrated with phase change heat storage technology, which is well-suited for regions with such climatic conditions. A numerical model of the components and coupled systems is established using the lumped parameter method, and an iterative method is employed for the computational solution in MATLAB software. A variety of system performance aspects are then simulated and analysed following the configuration of component structural parameters and initial operating conditions. The results of the simulations indicate that an increase in the phase change temperature interval of the phase change materials leads to a higher average heat release power. In particular, a 2 °C increase in the phase change temperature interval results in an increase in the heat release power of over 10 %. Furthermore, when the system is applied in typical cold regions, including Kunming, Hangzhou, Lhasa, and Harbin, the average coefficient of performance is 10.23, 8.87, 8.49, and 7.70, respectively. The proportion of solar energy input contributes to an increase in system efficiency across all regions. A case study of Hangzhou reveals that the incorporation of solar energy into the system results in an increase in efficiency of 70.91 %. This research provides valuable operational methods and site selection recommendations for engineering practices, laying a theoretical foundation for its widespread application in cold regions.

Improving Cleaning of Solar Systems through Machine Learning Algorithms

The study focuses on the importance of maintaining photovoltaic (PV) systems for optimal performance in sustainable energy generation. It highlights the impact of dust accumulation on reducing system efficiency and proposes a method to predict system performance, aiding in scheduling cleaning activities effectively. Two prediction models are developed: one using time-series prediction techniques (LSTM, ARIMA, SARIMAX) to forecast Performance Ratio (PR), and another employing ensemble voting classifiers (RF, Log, GBM) to predict the need for cleaning. The SARIMAX model performs best, achieving high accuracy in PR prediction (R2 = 92.12%), while the classification model accurately predicts cleaning needs (91%). The research provides valuable insights for improving maintenance strategies and enhancing the efficiency and sustainability of PV systems.

EXPERIMENTAL INVESTIGATION OF NATURAL CIRCULATING SOLAR ENERGY SYSTEM INCLUDING A PARABOLIC TROUGH SOLAR COLLECTOR

Abstract The most common natural flow water heating systems are in one-ended inclined pipes today. In this study, it is aimed to investigate the natural circulation solar energy system experimentally with parabolic trough solar collector. For this purpose, a natural circulation solar energy system including a parabolic trough solar collector that follows the sun in one dimension on the N-S axis in the outdoor environment has been established. Experiments were conducted on different dates. The radiation values coming into the opening of the moving collector were calculated. With the SolTrace program, it has been found that 56 % of this radiation can reach the vacuum tube glass pipe in the focus of the collector. In addition, the Rayleigh number was calculated for each experiment for the section of the glass tube close to the tank inlet, and it was monitored whether there was natural circulation throughout the experiment. As a result, the average Rayleigh number in the experiments conducted on 13 February, 31 March, 24 April, 23 May, 9 June, and 6 July was 1.4E+06, 7.6E+05, 7.8E+04, 2.2E+04, 3.1E+05, respectively. and calculated as 2.8E+05. In the experiments on May 23 and April 24, when the cooling system was open, it was observed that the Rayleigh number constantly dropped below the critical value. In other experiments, the situation is the opposite, and the natural flow is continuous.

Adaptive Fourth-Order GI-Based Controller for Three-Phase Grid-Tied Solar Photovoltaic System

A fourth-order generalized integrator (GI)-based frequency locked loop (AFOGI-FLL) controller is proposed to provide switching pulses for a three-phase IGBT-based voltage source converter. Accurate frequency synchronization, lower- and higher-order harmonic elimination, power quality refinement, and reactive power compensation are the features of the presented controller. As a renewable energy solution to meet energy demands, grid-interfaced photovoltaic systems are described in this paper. To stabilize DC link voltage, a novel ANFIS-based hybrid intelligent controller is proposed. In addition, a comparative analysis has been performed between the proposed controller and the third-order generalized integrator (TOGI). The comparative analysis results show that fourth-order generalized integrator has higher DC offset elimination capability and better dynamic performance as well and THD is less compared with the TOGI controllers. The THD of the proposed controller is 1.10% which is less than the IEEE standard. The proposed controller robustness is validated by an experimental prototype setup and test results exhibit the performance under non-linear loading. Additionally, the feasibility of the proposed control scheme is demonstrated by using MATLAB/SIMULINK software. The system is well executed under irradiance variations, load fluctuations, and frequency variations as well. The laboratory prototype is used to demonstrate the proposed system's simulated behavior and experimental test results.

Optimizing photovoltaic system configurations for domestic refrigerators in Miliana, Algeria: a simulation study

This study investigates the optimal configuration of a photovoltaic system to operate a home refrigerator with a power consumption of 130 watts. The research focuses on the city of Miliana, Algeria, analyzing the effects of local solar radiation and ambient temperature on battery charging dynamics throughout the year. Using MATLAB simulation techniques, we identified a 450 W solar panel coupled with a 150 Ah battery as the most efficient configuration to meet the power requirements of the refrigerator. Our findings highlight the fast charging capability of this PV system, achieving fast battery charging while maintaining a balance between energy production and consumption. However, we have also determined that increasing battery capacity beyond this limit results in longer charging times, shorter battery life cycles, and higher costs, which are counterproductive to the PV refrigerator-coupled system. The study emphasizes the importance of incorporating local climate conditions into the design of solar energy systems to ensure robust and sustainable energy solutions. The proposed configuration promises to reduce dependence on traditional energy sources, encourage the use of renewable energy in residential environments, and enhance environmental sustainability. Future research should evaluate these configurations in diverse geographic locations to validate and optimize the system for broader application, and explore advanced battery technologies to further improve efficiency and longevity.