Solar System Research Articles

Impact of thermal energy efficiency based on kerosene oil movement through hybrid nano-particles across contracting/stretching needle

This manuscript reveals the mathematical analysis of dual simulations in tangent hyperbolic rheology with heat transfer and mass diffusion mechanisms on the needle (expanding and shrinking). Further, Darcy's Forchhiermer law is employed with the occurrence of the magnetic field. The models of hybrid nanofluid utilized are Xue- and YO-hybrid nano-fluid models. Such models apply to optical fibers, solar systems, surgical implants, electronics and biological applications. Transfer of thermal energy and diffusion related to mass species occurs employing a non-Fourier approach. The transformed system of non-linear Odes is numerically tackled with the finite element method. Furthermore, because fluid and needle movement have opposite directions, the current model has dual solutions. It visualizes that such a complicated model is not solved numerically by FEM. The applications of Xue- and YO-hybrid nano-fluid model with non-Fourier's law on a needle are implemented for the first time. It concludes that adding YO-hybrid nanofluid with base fluid increases the entropy profile, temperature profile and Bejan profile rather than the Xue hybrid nanofluid model. Fields of concentration, velocity and heat energy for the case of upper solutions are higher than concentration, velocity and heat energy profiles for lower solutions.

Modelling and performance evaluation of a parabolic trough solar water heating system in various weather conditions in South Africa

In recent years, various energy sources and methods have been used to heat water in domestic and commercial buildings. Water heating methods for large households or commercial buildings include electrical heating elements, gas heaters, and solar energy (solar concentrators, flat plate collectors, evacuated tube collectors, etc.). In recent decades, the focus of water heating has shifted to solar energy, which is abundantly available in most African countries. The weather condition of a region has a huge impact on the system's performance. South Africa is characterised by four different weather seasons (winter, spring, summer, and autumn), unlike most African countries. Therefore, this study focuses on the impact of weather seasons on the system's performance for water heating through the combined use of solar energy and solar concentrator techniques. The system performance was modelled by using Matlab Simulink®, where historical weather data for Pretoria, South Africa, was fed into the model. Based on the weather data input, the system behaviour varied per season due to the change in solar intensity. The average outlet temperatures of the absorber, in the order of magnitude, were 333, 332, 328, and 325 K during the autumn, summer, spring, and winter seasons, respectively. Similarly, the average storage tank temperatures, in the order of magnitude, were 366, 364, 363, and 360 K in spring, summer, autumn, and winter, respectively. From this study, it is concluded that the different weather seasons in South Africa, have a direct impact on the performance of the system. Irrespective of the season, the system produced the required volume of hot water required throughout the year.

Study on the Use of Floating Photovoltaics on Kourna Lake, Western Crete, Greece

Installation of floating solar photovoltaic systems on the surface of water bodies has been developed rapidly in recent years worldwide. However, installation of floating photovoltaics in water reservoirs in Greece has not been reported so far. Kourna lake is the only natural lake in Crete located in the western part of the island in an idyllic and environmentally protected site while several touristic activities have been developed locally. The characteristics of the lake are mentioned and various parameters of a floating photovoltaic system which can be installed have been evaluated. A floating photovoltaic system with nominal power at 2.42 MWp can be installed on its surface with coverage ratio 5% generating 3.6 GWh annually. If the coverage ratio of the surface is at 10% the nominal power of the installed floating photovoltaic system will be at 4.83 MWp while the annually generated electricity will be at 7.24 GWh corresponding at 0.24% of the power demand in the island in 2018. The advantages and the drawbacks of the novel floating energy system have been stated. The acceptance of the abovementioned solar energy system from the local community is a prerequisite for its successful installation avoiding local conflicts and protests related with the co-existence of the current touristic activities with solar power generation in the lake.

Analysis of dust deposition law at the micro level and its impact on the annual performance of photovoltaic modules

Solar photovoltaic (PV) power generation is a promising clean energy technology, but dust affects its performance. This study, conducted in nine Chinese cities with varying climates and geographies, analyzed the physicochemical properties of dust and its deposition patterns at different inclination angles using microanalysis. Inclination angles were classified into three categories, and a dust density prediction (DDP) model was developed for each. The study also quantified the effect of different dust densities on PV module temperature in a controlled environment and created a PV module output power prediction (POPP) model to assess dust accumulation impacts on PV efficiency. It was found that dust insulation could increase PV module output power by 1.64% - 1.79% at dust densities of 5 - 10 g/m2 and radiation levels of 400 - 800 W/m2. Combining the DDP and POPP models, a PV efficiency loss rate model was proposed to evaluate annual average PV efficiency and power generation losses at different tilting angles. Results showed an annual average PV efficiency loss of over 7% at a 15° inclination angle and about 4.5% at a 90° inclination angle. This study provides a framework for evaluating PV module mounting angles and cleaning intervals, optimizing solar energy systems for improved efficiency and returns.

Performance of tube heat pipe solar collector with phase change material for seawater desalination system

Abstract Unlimited seawater resources resulted for utilization of desalination systems using seawater treatment process emerges as a promising technology for addressing the continually escalating need for freshwater. At present, the most notable desalination processes that are reverse osmosis, membrane distillation, multistage desalination, multiple-effect distillation, and electrodialysis, require energy generated by fossil fuels to obtain fresh water. Among the noteworthy sources of renewable energy, solar energy stands out with its manifold applications. The use of solar energy has strong advantages, such as a low maintenance and operation costs. In this study, a novel solar desalination system is introduced, which integrates tube heat pipe solar collector (THP-SC) equipped with phase change material (PCM). The aim of this research is to evaluate the performance of THP-SC equipped with PCM and without PCM. The feedwater sample used is water. Parameters measured for 24 hours were temperature, solar radiation, ambient air temperature, relative humidity, and wind speed. The greatest recorded solar radiation at noon (11.52 a.m.) is 900 W/m2 while the maximum recorded ambient temperature at 12.45 p.m. is 35.2°C. The experimental study showed that from morning to afternoon (06.00-15.00), the temperature of the evaporator section of the heat pipe on the THP-SC without PCM (46.70-56.21°C) was higher than the temperature of the evaporator section of the heat pipe on the THP-SC with PCM (33.18-44.43°C). This is because solar radiation will heat the PCM first before heating the heat pipe. PCM can store heat energy and release it at night. This can be seen from the water temperature in THP-SC with PCM (28.39-36.03) which is higher than the water temperature in THP-SC without PCM (27.17-34.01) at night, but the temperature difference is not significant. This can be caused by the large amount of heat lost to the environment in THP-SC with PCM, it is best to coat the heat pipe tube with insulation and create a vacuum to reduce heat loss.

Transforming waste polystyrene foam to carbon on zeolite for efficient solar water desalination

Solar-driven water evaporation was well-proven to be a sustainable technique for seawater desalination by using renewable energy. In this technology, carbon material is preferably chosen as a photothermal conversion material due to its excellent stability and corrosion resistance. However, the applicability of carbon-based materials was constrained by their poor mechanical strength and the high cost. In this paper, carbon coated sands and zeolites were prepared by using waste polystyrene foam (white pollution) as carbon source and this waste utilization method greatly reduces material costs. The solar-driven water evaporation device was fabricated by confining these carbon-coated composites in the PVA hydrogel. Owing to the superior light absorption (over 96 %) and good hydrophilicity for water transfer, the carbon-coated sand and zeolite exhibited maximum evaporation rate of 1.51 and 1.24 kg m−2h−1 under 1 sun illumination, respectively. In outdoor test, the maximum water collection rate was 0.92 kg m−2 h−1. It is possible to create an effective and environmentally beneficial solar interfacial water evaporation system with this approach.

Study on the Optical Coupling Effect of Building-Integrated Photovoltaic Modules Applied with a Shingled Technology

Building-integrated photovoltaics (BIPV) comprise the integration of a solar power generation system into the exterior design and architectural elements of a building to produce electricity, which allows the building itself to generate electricity. By integrating shingled technology into the photovoltaic module with optimization of the optical effect, the output performance of the module can be increased while securing an aesthetic appeal as an architectural exterior material for the building simultaneously. In this research, we studied enhancing the performance of BIPV modules through an analysis of the optical coupling effect for shingled technology using PSpice simulation. Compared to the efficiency of 0.2 cm string spacing, the optical coupling effect was increased by 33.33%, 46.98%, 67.01%, and 193.49% according to the string spacing of 0.5 cm, 1 cm, 2 cm and 4 cm, respectively. To analyze this increase, we focused on studying the increase in current due to the reflection and re-absorption of light in the back layer of the solar cell as the cause of this output enhancement. Additionally, the coupling effect in accord with different layers showed that using white EVA to reflect the incident light from the top layer resulted in 117.14% and 521.90% enhancements in maximum output power (Pm) loss % compared to the conventional and black backsheet applied PV modules, respectively.

Optimization of MPPT perturb and observe algorithm for a standalone solar PV system

Optimization of MPPT perturb and observe algorithm for a standalone solar PV system

Interplay between the heat treatment and structural and optical properties of Nb2O5 thin films

Thin films of Nb2O5 were synthesized by RF sputtering. The effect of annealing, at different temperatures (100, 150, 200, 250, 300, 350, and 400 °C), on the structural and optical properties was studied. The crystallinity and structural characteristics of the Nb2O5 thin films were examined employing the X-ray diffraction (XRD) and scanning electron microscopy (SEM). XRD and SEM analyses showed an amorphous nature for the as-deposited and annealed samples from 100 to 350 °C and crystalline structure for the annealed sample at 400 °C. The high values of the transmittance and low reflection make these films used as a window layer in solar cell systems. Upon increasing annealing temperature, the energy band gap Eg increased from 4.039 to 4.175 eV. Eg high values again make these films suitable to be used as a window layer in solar cell system. Urbach tail, EU, decreased with increasing annealing temperature. The refractive index showed the normal dispersion. The dispersion energies were found to have the same behavior with respect to annealing temperature, besides, the single oscillator energy Eₒ had a lower value compared to the dispersion energy Ed. The plasma frequency ωp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\omega }_{p}$$\\end{document} was found to increase with annealing temperature. The first and third optical moments had peak values depending on the incident photon energy.

Adaptive extreme learning machine using soft computing fuzzy propositions—Validating operating state of solar energy system

In this paper soft computing fuzzy proposition/rule based adaptive extreme learning is proposed. This article illustrates the impact of agricultural solar panel (AgSP) and its operating condition/state during the farming seasons and hence safety of energy system sustained. Extreme learning machine (ExLM) used as learning machine (LM) for artificial intelligence (AI) training to predict the operating state of applied AgSP green energy unit. soft computing Fuzzy rules are framed for every instant of leaning machine to identifying the lower mismatch conditions and avoid the false prediction. Higher and lower limits of adaptive resonance theory (ART) support LM (ART-LM) is properly used by providing unusual dust formation (UnDFR) data and usual/normal dust formation (UsDFR) data for AI training. Outcome of AI neural net is determined by resonant neuron net (RSNN). Predicted variable from ART-LM is calculated with higher and lower limits of dataset captured from applied energy common node (CN). Many test conditions of dust formation on solar photovoltaic (PV) has been validated to predict the state of applied energy system. For any UnDFR confirmation, entire AgSP based distributed generator (DG) unit will isolate from common node/utility grid. Proposed ART-LM based AI algorithm has been validated even for charging state events of electrical vehicle (EV) during the abnormal conditions.

Development of a novel hybrid hydrogen generator incorporated into a combined system for buildings in sustainable communities

The development of a new hybrid (Photoelectrochemical (PEC)-Conventional) hydrogen generator integrated into a combination system for buildings is a major step forward in the quest for sustainable energy solutions in cities. This study introduces a novel hybrid hydrogen generation system that is specifically designed, implemented, and evaluated for incorporation into sustainable community systems. A significant advantage of the generator is the ability to produce hydrogen constantly, regardless of the absence of solar irradiation. Furthermore, both electrolyzers contribute to a rise in the amount of hydrogen produced. Furthermore, the utilization of PEC electrolysis for hydrogen generation results in a significant reduction in the overall power requirements of the system. This new study investigates an integrated power system that produces electricity from solar energy and tackles issues related to freshwater supply, hydrogen production, and heating/cooling demands. The purpose of this research is to integrate advanced system components, including a solar power tower system, a combined Brayton-Rankine cycle, a multi-effect desalination (MED) unit, a new hybridized hydrogen generator system, an absorption cooling cycle (ACS), and a hydrogen storage and refuelling station. The overall energy efficiency is determined to be 49%, while the exergy efficiency becomes 46.2%.

Comparative analysis of solar module configuration and tracking systems for enhanced energy generation in South Sakucia Union, Bhola, Bangladesh: A software based analysis

Bangladesh is blessed with an extensive range of solar energy generation possibilities; however, the primary impediment to attaining its full potential in the solar energy industry is the inadequate budget in the energy sector. As a result, determining the most economical and efficient solar module configuration for each specific scenario has become a critical necessity. This study offers a comprehensive techno-economic analysis and environmental impact assessment of four distinct solar modules: monofacial, bifacial, dual-axis solar tracker, and seasonal tilt solar module, in an open area of South Sakucia Union, Bhola district, in the southwest part of Bangladesh. By integrating energy-generation capabilities, financial metrics, and environmental benefits, this research provides a holistic evaluation framework to ensure optimal economic performance and minimal adverse environmental effects for sustainable solar solutions in Bangladesh. Utilizing PV*SOL, PVsyst, and System Advisor Model (SAM) software, this study assesses energy-generation capabilities and economic viability. Despite the dual-axis solar tracker exhibiting the highest average energy generation (149,070.3 kWh/year), its higher initial cost renders it less financially viable compared to other configurations. Financial metrics reveal that the seasonal tilt configuration is the most cost-efficient, with the lowest Levelized Cost of Electricity (LCOE) at $0.0452/kWh and the highest Net Present Value (NPV) of $52,887.70. Additionally, it has the shortest Discounted Payback Period (DPBP) at 12.69 years, a favorable Internal Rate of Return (IRR) of 9.460 %, and a Profitability Index (PI) of 1.459, indicating robust returns on investment. These findings emphasize the importance of considering both energy-generation capabilities and financial metrics when evaluating solar module configurations in the southern part of Bangladesh, serving as a valuable reference for policymakers. Moreover, meticulous environmental impact assessments assist in choosing configurations with minimal adverse effects on the environment.

Unlocking the power of LiOH: Key to next-generation ultra-compact thermal energy storage systems

This study explores the potential of untapped lithium hydroxide (LiOH) as a phase change material for thermal energy storage. By overcoming the challenges associated with the liquid LiOH leakage, we successfully thermal-cycled LiOH in a laboratory scale experimentation, and observed its stability (>500 thermal cycles), without chemical decomposition. This step has never been performed to date. Its solid-to-liquid reversible transitions temperatures and related solidification/melting enthalpies values have been verified. Then, the first experimental characterization of LiOH's thermal properties shows unexpected values for its heat capacity, thermal conductivity and diffusivity, in contradiction with the few ones available in literature. This opens avenues for LiOH's applications for the storage of sensible and latent heat, as shown through the increased cycle efficiency potential of a thermal energy storage system if based on its energy storage capacity; up to six times more volumetric energy density compared to traditional Solar Salt-based systems used in the solar tower plant (4.5 GJ/m3 vs. 0.76 GJ/m3 over 1000 thermal cycles). Additionally, we observed a softening phenomenon that occurs inconsistently during heating, but which may account for its excellent melting properties and the interplay with other raw chemicals. This new insight contributes certainly to the underlying mechanisms in the synthesis of another promising heat storage material in development: the peritectic compound Li4Br(OH)3. This pioneering work suggests LiOH as a promising ultra-compact thermal energy storage material for filling the intermediary gap from current to next-generation solar power plants, although its large-scale application requires further investigation to achieve economic viability.

Modeling a solar shading system that controls heat gain by using solar energy to change louver slat angles

In this study, we propose a model for a passive louver system that adjusts slat angles using solar heat energy. The model is structured in two stages: predicting the surface temperature of a solar collector plate and using this temperature to determine the slat angles. The system was installed and monitored in a building in Okinawa, Japan, to validate the model’s accuracy with field measurements. The validation showed that while the model accurately predicted the daily opening and closing times of the louvers, it faced limitations in minute-by-minute variations, making it less suitable for scenarios requiring instantaneous state evaluations, such as lighting environment assessments. Additionally, predicting the temperature for the double-skin façade was challenging and could affect overall model accuracy. Despite these issues, the model effectively achieved its primary goal of predicting annual energy consumption by accurately forecasting the daily opening and closing times of the louvers. The model’s fast computation speed and simplicity make it particularly suitable for annual energy simulations and easy to integrate with existing energy simulation programs. Further research is needed to enhance minute-by-minute reproducibility and integrate temperature predictions for double-skin façades, ensuring a comprehensive evaluation of both thermal and lighting environments.

Enhancing the estimation of direct normal irradiance for six climate zones through machine learning models

The evaluation of solar radiation is essential for large-scale solar energy systems, as assessing economic feasibility early on depends on accurate solar radiation data. Accurate sensors are needed to characterize the solar resource. Due to a scarcity of solar radiation data, numerical models are commonly used to estimate solar radiation components using meteorological variables that are simple or cheap to measure. In recent years, the use of machine learning (ML) algorithms has gained significant popularity in the estimation of solar radiation components. In this study it is proposed a post-processing approach using the separation model outcomes as input variables to estimate the diffuse fraction. Three ML models are employed (XGBoost, Random Forest, and Multilayer Perceptron) to boost the accuracy in terms of three statistical indicators: nRMSE, nMBE, and R2. The employed technique takes a distinctive approach by using reference stations to train the machine learning models and, afterward, make the assessment at the site under study. The results show an improvement in terms of precision of individual separation model outcomes. Thus, the proposed methodology may serve as a reliable approach for estimating solar radiation components in cases where historical data for a specific place of interest is not accessible.

Response surface methodology optimization of characteristics of biodiesel powered diesel engine and its effective integration to autonomous microgrid

An optimum diesel engine load condition with higher thermal efficiency and energy management has been the foremost challenge in the renewable energy research field. Modern trends involve nano additives for obtaining high performing biodiesel blends. Considering the above-mentioned factors, an experimental study along with statistical analysis has been performed with variation of compression ratio (16, 17.5 & 18), ZrO2 nano additive (50, 100 & 150 ppm) and load (50, 75 & 100 %). The optimization was accomplished by diminishing the BSFC, NOx, HC, CO, and increasing the BTE, CO2 using the approach of desirability. From the obtained results, the optimum operating conditions of the engine were found to be 75 % load, 18:1 compression ratio, and 150 ppm ZrO2 nano additive. The actual values at optimized conditions are obtained as BSFC (0.27 kg/kWh), BTE (33.37 %), CO (0.71 %), CO2 (8.69 %), NOx (1270 ppm), HC (62 %) and Smoke (25.20 %) with error less than 5 %. It has been observed that the BSFC of the proposed biodiesel-diesel blend is lower than that of pure diesel in all levels of power output. The biodiesel fuelled diesel engine is integrated as backup power in autonomous microgrid with main power as solar PV system operated at MPPT mode. A hybrid power system based on solar PV and biodiesel generator set up is the better alternative to emission-intensive fossil fuel and intermittent renewable.

Marine Predators Algorithm with Deep Learning based Solar Photovoltaic System Modelling and Optimization of Green Hydrogen Production

Green hydrogen production depends on solar energy contains employing renewable solar power to purpose the electrolysis of water, causing the separation of hydrogen and oxygen molecules. This method contains a high potential to address the energy transition challenges caused by weather changes and vital carbon-neutral alternatives. Photovoltaic (PV) based combined energy systems performance as a potential new technological solution for clean and affordable green hydrogen production. Optimizing solar PV systems for the effectual generation of green hydrogen includes maximizing the energy output of solar panels and increasing the entire hydrogen production method. Several researchers and scientists are paid attention to the optimizer and modelling of many blocks developing the PV electrolysis method to acquire the optimum solution. With this motivation, the study presents a new Marine Predator Algorithm with Deep Learning-based Modelling and Optimization of the Green Hydrogen Production (MPADL-MOGHP) technique. The MPADL-MOGHP technique can be employed for determining the optimum operational variables of the water electrolysis procedure relevant to hydrogen (H2) production. Catalyst amount (μg), electrolysis time (min), and electric voltage (V) are the three controlling factors that should be properly detected to increase hydrogen production. The MPADL-MOGHP technique comprises two major stages of operations such as modelling and optimization. Primarily, the DBN model is applied for simulating the water electrolysis procedure designed based on electric voltage, quantity of catalyst, and electrolysis time. Next, the MPA is applied for determining the optimum parameters of the water electrolysis process to maximize the generation rate of the hydrogen. The quantity of catalyst, the electrolysis time, and the electric voltage are applied as decision parameters during the optimization process. The performances of the MPADL-MOGHP system are tested on different aspects. The experimental values highlighted the promising results of the MPADL-MOGHP method over other existing techniques.

Experimental investigation of inclined solar still through localized interfacial evaporation using nano enhanced Bio wick under disparate flow rate

Water treatment is essential for obtaining potable water, and passive solar desalination offers a renewable and sustainable approach. However, productivity remains a key challenge for commercialization. Scaling up solar desalination systems while maintaining efficiency and cost-effectiveness is a significant challenge. The current state of research in solar desalination is focused on developing scalable and sustainable solutions to address challenges faced in productivity. To address this issue, ongoing efforts focus on improving productivity under localized interfacial evaporation. The present study aims to enhance productivity, particularly at higher mass flow rates, through a series of experiments conducted in three sets. In the first set of experiments, a bare Integrated Solar Still (ISS) was utilized with various mass flow rates (0.29, 0.42, 0.75, and 1.3 kg/min). The highest hourly yield of potable water was observed during peak solar intensity, typically between 13:00 and 14:00 Hrs for all mass flow rates. However, as the mass flow rate increased, the hourly yield of potable water decreased. For instance, at 14:00 Hrs, the maximum yield was 0.235, 0.15, 0.12, and 0.06 kg/m2 for mass flow rates of 0.29, 0.42, 0.75, and 1.3 kg/min, respectively, in the ISS without wick material. The highest cumulative yield achieved was 1.6 kg/m2 during 0.29 kg/min mass flow rate, while the minimum clean water yield of 0.4 kg/m2 was obtained at 1.3 kg/min. In the second set of experiments, the goal was to improve productivity at higher mass flow rates. The use of Fe2O3-impregnated jute cloth in comparison to the bare ISS resulted in an average absorber temperature increase of 4∘C, 4.8∘C, 4.8∘C, and 4.9∘C for mass flow rates of 0.29, 0.42, 0.75, and 1.3 kg/min, respectively. Interestingly, the trend showed an increasing rate of reduction mitigation at higher mass flow rates. Simultaneously, the average water temperature increased by 4.2∘C, 4.5∘C, 6.4∘C, and 7.1∘C for the corresponding mass flow rates with Fe2O3-impregnated jute cloth. The introduction of jute cloth enhanced energy harvesting at all mass flow rates compared to the bare ISS. The maximum energy efficiency, at 48.02 %, was achieved with Fe2O3-impregnated jute cloth during the 0.29 kg/min mass flow rate, while the minimum energy efficiency, at 9.14 %, was recorded at the highest mass flow rate of 1.3 kg/min. Notably, the energy efficiency of the jute cloth-covered ISS surpassed that of the bare ISS by 12.44 %, 9.14 %, 7.15 %, and 3.14 % for mass flow rates of 0.29, 0.42, 0.75, and 1.3 kg/min, respectively. Furthermore, the addition of Fe2O3-impregnated jute cloth further improved energy efficiency, with enhancements of 8.19 %, 1.14 %, 6.36 %, and 9.57 % over the jute cloth-covered ISS for the respective mass flow rates. During the 0.75 kg/min mass flow rate, energy efficiency reached 26.12 %, closely matching the 27.3 % efficiency achieved at 0.29 kg/min in the bare ISS. The study also demonstrated a 2.29 % improvement in exergy with Fe2O3-impregnated jute cloth at a mass flow rate of 0.29 kg/min. In conclusion, the results suggest that the implementation of jute cloth over the ISS absorber basin can enhance overall efficiency and mitigate the negative impacts of increased mass flow rates via localized interfacial evaporation. The combination of a jute cloth wick and Fe2O3 nanoparticles holds promise for improving energy efficiency in solar still desalination.

Smart solar maintenance: IoT-enabled automated cleaning for enhanced photovoltaic efficiency

This innovative project aims to increase the effectiveness and user experience of solar panel systems by introducing a state-of-the-art dust and speck removal system. Leveraging cutting-edge technology, the system demonstrates a remarkable 32% increase in power output compared to dirty solar panels. The approach is characterized by its reliance on the universe as the system controller, reducing the need for manual intervention and minimizing the workforce required for panel cleaning. The proposed timed system utilizes water and wipers, facilitated by internet of things (IoT) technology, microcontrollers, and sensor modules for efficient and automated operation. An Android application provides user control and notifications about ongoing processes. The system’s adaptability for various settings is emphasized, offering a portable solution. The smart IoT based automatic solar panel cleaning ensures reliable performance, underscoring the project’s commitment to improve scalability, cost-efficiency, performance, integrity, and consistency.

Unlocking the power of LiOH: Key to next-generation ultra-compact thermal energy storage systems

This study explores the potential of untapped lithium hydroxide (LiOH) as a phase change material for thermal energy storage. By overcoming the challenges associated with the liquid LiOH leakage, we successfully thermal-cycled LiOH in a laboratory scale experimentation, and observed its stability (>500 thermal cycles), without chemical decomposition. This step has never been performed to date. Its solid-to-liquid reversible transitions temperatures and related solidification/melting enthalpies values have been verified. Then, the first experimental characterization of LiOH's thermal properties shows unexpected values for its heat capacity, thermal conductivity and diffusivity, in contradiction with the few ones available in literature. This opens avenues for LiOH's applications for the storage of sensible and latent heat, as shown through the increased cycle efficiency potential of a thermal energy storage system if based on its energy storage capacity; up to six times more volumetric energy density compared to traditional Solar Salt-based systems used in the solar tower plant (4.5 GJ/m3 vs. 0.76 GJ/m3 over 1000 thermal cycles). Additionally, we observed a softening phenomenon that occurs inconsistently during heating, but which may account for its excellent melting properties and the interplay with other raw chemicals. This new insight contributes certainly to the underlying mechanisms in the synthesis of another promising heat storage material in development: the peritectic compound Li4Br(OH)3. This pioneering work suggests LiOH as a promising ultra-compact thermal energy storage material for filling the intermediary gap from current to next-generation solar power plants, although its large-scale application requires further investigation to achieve economic viability.