Search Results (13,116)

The column photobioreactor has become the predominant approach for carbon sequestration by microalgae in power plant settings, owing to its capacity for high-density cultivation and efficient light energy utilization. Due to the dense arrangement of the columnar photobioreactor and its height, insufficient light became one of the main factors limiting the carbon sequestration rate of microalgae growth. In this paper, a light resource optimization method of reflective baffle and top diffusing glass was proposed. When the angle of reflective baffle on the north and east walls was 35°, and the angle of reflective baffle on the west and south floors was 0°, the overall light radiation intensity of the reactor array became the largest, reaching up to 916.81 W/m², which was 14.39% higher than that before the optimization. The replacement of the top glass with diffusing material converted the direct radiation of solar radiation into scattered radiation. When the transmittance was 95% and the haze was 95%, the overall average light radiation intensity of the algal solution reached 830.93 W/m², which was an increase of 3.7%. Four new exhaust air distribution methods were proposed, in which the three-entrance staggered-arrangement type glasshouse had the lowest algal liquid temperature. Full article

Tropical regions experience intense and highly variable solar radiation, often resulting in excessive indoor illuminance, uneven daylight distribution, and visual discomfort in high-rise residential buildings. This study investigates the daylighting performance of various external horizontal slat configurations as a shading strategy for east- and south-facing rooms in a typical high-rise apartment under both intermediate sky with sun and overcast sky conditions. Using IESVE simulations, ten shading device (SD) configurations (SD 1–SD 10) were evaluated for their impact on daylight illuminance and distribution uniformity. Results show that high-rise apartment room with a commonly used overhang provided poor daylighting quality, with excessive illuminance and low distribution uniformity. SD 10 and SD 9 achieved the best performance at 09:00 and 12:00, respectively, for east-facing rooms across design days, while SD 10 was optimal for south-facing rooms on both 21 March and 22 December. Under overcast sky conditions, SD 9 demonstrated superior performance. This study proposes a novel adaptive external shading device featuring adjustable horizontal slats that can be reconfigured throughout the day to respond to changing solar positions and sky conditions. This approach overcomes the limitations of fixed shading systems by adapting to dynamic tropical sky conditions, offering a practical solution for enhancing daylight quality in tropical high-rise apartments. The findings provide design guidance for the development of energy-efficient shading, climate-responsive shading systems tailored to tropical environments. Full article

This paper explores the potential of the airbrushing method as a novel and cost-effective method for producing uniform titanium dioxide (TiO₂) films, crucial for enhancing the efficiency of dye-sensitized solar cells. The techniques performed were SEM and EDS images, OCP curves, photochronoamperometry, j-V curves, and impedance spectroscopy. Comparative analysis with the doctor blade methodology has noted a higher uniformity compared to the AB method, with the ability to improve the charge transportation and PCE (1.987%) and reduce the recombination process in the TiO₂/electrolyte interface (ԏe = 0.012 s). Insights from EIS spectroscopy and intensity-modulated spectroscopy offer mechanistic elucidations of the enhanced performance. Overall, this study highlights airbrushing as a promising approach for advancing the development of high-performance solar energy systems. Full article

The number of electric vehicles is constantly increasing in Europe and around the world. Providing a reliable charging infrastructure for the se vehicles is a major challenge for distribution grid operators. Off-grid microgrids have become a promising solution to this challenge, using renewable energy sources such as solar power to meet the demand in a sustainable way. This paper presents a practical study of a solar-powered microgrid operating at a university campus in Ilmenau, Germany, aimed at supporting electric vehicle (EV) charging at public workplaces. The system includes eight charging stations and utilizes renewable energy to reduce grid dependency. Statistical methods, including distribution functions, medians, and mean values, were applied to classify and evaluate the dataset to analyze energy generation and variable load patterns, as well as system performance. The results show that the Ilmenau microgrid can meet EV charging demand during the warm season but underperform during the cold season. An economic analysis determined costs of EUR 0.58/kWh based on pre-2020 component prices and EUR 0.46/kWh based on 2025 market prices. The calculated annual cost per employee is EUR 308.29 over a 20-year period. Increasing energy storage was found to be neither cost-effective nor operationally beneficial. The scalability of the microgrid to larger workplaces is investigated, and recommendations for system improvements are provided. Full article

The widespread deployment of electric vehicles (EVs) has introduced substantial challenges to electricity pricing, grid stability, and renewable energy integration. This paper proposes a real-time pricing optimization framework for large-scale EV charging networks incorporating renewable intermittency, demand elasticity, and infrastructure constraints within a high-dimensional optimization model. The core objective is to dynamically determine spatiotemporal electricity prices that simultaneously reduce system peak load, improve renewable energy utilization, and minimize user charging costs. A rigorous mathematical formulation is developed integrating over 40 system-level constraints, including power balance, transmission capacity, renewable curtailment, carbon targets, voltage regulation, demand-side flexibility, social participation, and cyber resilience. Real-time electricity prices are treated as dynamic decision variables influenced by charging station utilization, elasticity response curves, and the marginal cost of renewable and grid-supplied electricity. The problem is solved over 96 time intervals using a hybrid solution approach, with benchmark comparisons against mixed-integer programming (MILP) and deep reinforcement learning (DRL)-based baselines. A comprehensive case study is conducted on a 500-station EV charging network serving 10,000 vehicles integrated with a modified IEEE 118-bus grid model and 800 MW of variable renewable energy. Historical charging data with ±12% stochastic demand variation and real-world solar and wind profiles are used to simulate realistic operational conditions. Results demonstrate that the proposed framework achieves a 23.4% average peak load reduction per station, a 17.9% improvement in renewable energy utilization, and user cost savings of up to 30% compared to baseline flat-rate pricing. Utilization imbalances across the network are reduced, with congestion mitigation observed at over 90% of high-traffic stations. The real-time pricing model successfully aligns low-price windows with high-renewable periods and off-peak hours, achieving time-synchronized load shifting and system-wide flexibility. Visual analytics including high-resolution 3D surface plots and disaggregated bar charts reveal structured patterns in demand–price interactions, confirming the model’s ability to generate smooth, non-disruptive pricing trajectories. The results underscore the viability of advanced optimization-based pricing strategies for scalable, clean, and responsive EV charging infrastructure management in renewable-rich grid environments. Full article

Photovoltaic (PV) modules undergo comprehensive testing to validate their electrical and thermal properties prior to market entry. These evaluations consist of durability and efficiency tests performed under realistic outdoor conditions with natural climatic influences, as well as in controlled laboratory settings. The overall performance of PV cells is affected by several factors, including solar irradiance, operating temperature, installation site parameters, prevailing weather, and shading effects. In the presented study, three distinct PV modules were analyzed using a sophisticated large-scale steady-state solar simulator. The current–voltage (I-V) characteristics of each module were precisely measured and subsequently scrutinized. To augment the analysis, a three-layer artificial neural network, specifically the multilayer perceptron (MLP), was developed. The experimental measurements, along with the outputs derived from the MLP model, served as the foundation for a comprehensive global sensitivity analysis (GSA). The experimental results revealed variances between the manufacturer’s declared values and those recorded during testing. The first module achieved a maximum power point that exceeded the manufacturer’s specification. Conversely, the second and third modules delivered power values corresponding to only 85–87% and 95–98% of their stated capacities, respectively. The global sensitivity analysis further indicated that while certain parameters, such as efficiency and the ratio of V_oc/V, played a dominant role in influencing the power-voltage relationship, another parameter, U, exhibited a comparatively minor effect. These results highlight the significant potential of integrating machine learning techniques into the performance evaluation and predictive analysis of photovoltaic modules. Full article

Extreme operating conditions in solar receivers of concentrated solar thermal power plants, such as high temperatures, intense irradiance, and thermal cycling, pose significant challenges for conventional sensors. Optical fibers offer a promising alternative for flux measurement in such environments, but their long-term performance and degradation mechanisms require detailed investigation and characterization. This work presents a proof of concept for high solar flux measurement by using optical fibers as photon-capturing elements and showcases the behavior and damage that these optical fibers undergo when exposed to relevant conditions, including temperatures over 600 °C and flux levels exceeding 400 kW/m². Three fiber configurations, including polyimide and gold-coated fibers, were tested at a high-flux solar simulator and analyzed via scanning electron microscopy to assess structural integrity and material degradation. Results reveal significant coating deterioration, fiber retraction, and thermal-induced stress effects, which impact measurement reliability. These findings provide essential insights for improving the durability and accuracy of optical fiber-based sensing technologies in concentrating solar energy. Full article

Photovoltaic (PV) module enhancers, such as coolers and reflectors, are advanced technologies aimed at improving PV performance. The conventional approach for selecting the optimal PV enhancer relies on the observation of the highest power. While effective in comparing different enhancer designs, this method does not determine the maximum performance that the PV enhancer can achieve. To address this limitation, a new methodology is introduced that overcomes this drawback. It relies on three essential parameters: the net power gain with an enhancer, the power output of a PV module without an enhancer, and the maximum power of a PV module under standard test conditions. The impact of each parameter on the proposed method is analyzed, and enhancers are classified based on the method’s output. Maximum or minimum performance is observed when the method’s value is either in unity with or matches the ratio of a PV module’s power output (without an enhancer) to its maximum power under standard conditions. To validate this approach in practical applications, experimental data from previous studies are examined. The results confirm that this technique can be applied for real-world cases and can effectively categorize PV enhancers, offering valuable insights for researchers, designers, and manufacturers. Full article

To improve the optical concentrator ratio of space solar power stations (SSPSs), this paper proposes a deployable segmented solar concentrator (DSSC) based on an afocal reflective system. First, a novel concept of an afocal reflective concentrator composed of segmented primary and secondary mirrors is introduced, and the deployable mechanism for the segmented primary mirror is described in detail. Subsequently, a model for the comprehensive error of the deployable mechanism with 3D revolute joint clearances and link length errors is established based on the “massless link” equivalent model of the clearance in revolute joints and the homogeneous transfer matrix. Sensitivity analysis evaluates the impact of various geometric errors of the deployable mechanism on the comprehensive error. Finally, a prototype experimental system is built to verify the concentration ratio of the concentrator and the pose error of the deployable mechanism. The experimental results show that the DSSC geometric concentration ratio reaches 5.36 to 6, and the optical concentration ratio reaches 24.7 to 32.2. The repeatability of the deployable mechanism is ±50 µm and ±1.2′, meeting the tolerance requirements of the optical system. The proposed afocal reflective DSSC can be used for solar energy concentration, improving the utilization of solar energy. Full article

In this work, a sol–gel spin coating method was applied to obtain ZnO and ZnO:Ga thin films on a glass and ITO-coated glass substrate. Their structural, optical, and electrical properties were investigated with respect to their dependence on the different substrates, the number of layers (two and four), and the annealing temperature (300 and 400 °C). X-ray diffraction (XRD) patterns showed a hexagonal structure corresponding to the wurtzite phase for ZnO and ZnO:Ga films. ZnO films, deposited on a glass substrate, reveal greater crystallite sizes compared with ZnO films obtained from an ITO substrate. A Ga dopant worsened film crystallization. X-Ray photoelectron spectroscopy (XPS) proves the presence of Ga in a ZnO structure. ZnO films show lower transparency and haze values up to 44.12 (glass substrate) and 33.73 (ITO substrate) at a wavelength of 550 nm. The significant enhancement of ZnO film transparency is observed with Ga doping (with average transmittance in the visible spectral range above 85%, independent of the substrate used). Sheet resistance values are lower for ZnO:Ga films, and the figure of merit values are better compared with those of undoped ZnO films. Work function is studied for ZnO and ZnO:Ga films, deposited on Si, ITO, and glass substrates. Full article

Surface solar radiation (SSR) is a critical component of the Earth’s energy balance and plays a pivotal role in climate modelling, hydrological processes, and solar energy planning. In data-scarce regions like India, where dense ground-based radiation networks are limited, reanalysis and satellite-derived SSR datasets are often utilized to fill observational gaps. However, these datasets are subject to systematic biases, particularly under diverse sky and seasonal conditions. This study presents a comprehensive evaluation of four widely used SSR datasets: ERA5, IMDAA, MERRA2, and CERES, against high-quality in situ observations from 27 India Meteorological Department (IMD) stations, for the period 1985–2020. The assessment incorporates multi-scale temporal analysis (daily/monthly), spatial validation, and sky-condition stratification via the clearness index (K_t). The results indicate that CERES exhibits the best overall performance with the lowest RMSE (16.30 W/m²), minimal bias (–2.5%), and strong correlation (r = 0.97; p = 0.01), particularly under partly cloudy conditions. ERA5, with a finer spatial resolution, also performs robustly (RMSE = 20.80 W/m²; MBE = –0.8%; r = 0.94; p = 0.01), showing consistent agreement with observed seasonal cycles, though slightly underestimating SSR during monsoonal cloud cover. MERRA2 shows moderate overestimation (+4.4%) with region-specific bias variability, while IMDAA demonstrates persistent overestimation (+10.2%) across all conditions, highlighting limited sensitivity to atmospheric transparency. Importantly, this study reconciles apparent contradictions between monthly and sky condition-based bias analyses, attributing them to aggregation differences. While reanalysis datasets overestimate SSR during the monsoon on average, they tend to underestimate it under heavily overcast conditions. These insights are critical for guiding the selection and application of SSR datasets in solar energy modelling, SPV system design, and climate diagnostics across India’s heterogeneous atmospheric regimes. Full article

To improve the mechanical stability and service durability of solar road structures, this study systematically investigates the mechanical response characteristics of photovoltaic panels with different geometric shapes—including triangles, rectangles, squares, regular pentagons, and regular hexagons—under consistent boundary and loading conditions using the discrete element method (DEM). All panels have a uniform thickness of 10 cm and equivalent surface areas to ensure shape comparability. Side lengths vary among the shapes: square panels with sides of 0.707 m, 1.0 m, and 1.5 m; triangle 1.155 m; rectangle (aspect ratio 1:2) 0.707 m; pentagon 1.175 m; and hexagon 0.577 m. Results show that panel geometry significantly influences stress distribution and deformation behavior. Although triangular panels exhibit higher ultimate bearing capacity and failure energy, they suffer from severe stress concentration and low stiffness. Regular hexagonal panels, due to their geometric symmetry, enable more uniform stress and displacement distributions, offering better stability and crack resistance. Size effect analysis reveals that larger panels improve load-bearing and energy dissipation capacity but exacerbate edge stress concentration and reduce overall stiffness, leading to more pronounced “thinning” deformation and premature failure. Failure mode analysis further indicates that shape governs crack initiation and path, while size determines crack propagation rate and failure extent—revealing a coupled shape–size mechanical mechanism. Regarding assembly, honeycomb arrangements demonstrate superior mechanical performance due to higher compactness and better load-sharing characteristics. The study ultimately recommends the use of small-sized regular hexagonal units and optimized splicing structures to balance strength, stiffness, and durability. These findings provide theoretical guidance and parameter references for the structural design of solar roads. Full article

The damage characteristics of monocrystalline silicon solar cells irradiated by a nanosecond pulsed laser were investigated in a vacuum environment. An 8 ns pulsed laser was used with a 1064 nm wavelength, a 2.0 J maximum pulse energy, and a millimeter-scale ablation spot diameter. The cells were irradiated by a laser with varying fluences, irradiation positions, and pulse numbers. The damage mechanism was discussed in combination with the degradation of electrical properties, the morphology of surface damage, and electroluminescence images. A single pulse mainly caused surface heating and deformation, while multi-pulse irradiation led to the formation of melting ablation craters. More severe performance degradation was caused by irradiation at the grid line site due to fracture of the grid line electrodes. Moreover, monocrystalline silicon cells showed excellent damage resistance to fixed-position irradiations at non-gridded line areas. This work reveals, for the first time in vacuum, that grid-line fracture dominates performance degradation—enabling targeted hardening for space solar cells. Full article

Accurate photovoltaic (PV) power forecasting is essential for grid integration, particularly in maritime climates with dynamic weather patterns. This study addresses high-dimensional meteorological data challenges by systematically evaluating 32 variables across four categories (solar irradiance, temperature, atmospheric, hydrometeorological) for day-ahead PV forecasting using long short-term memory (LSTM) networks. Using six years of data from a 350 kWp solar farm in Scotland, we compare satellite-derived data and local weather station measurements. Surprisingly, downward thermal infrared flux—capturing persistent atmospheric moisture and cloud properties in maritime climates—emerged as the most influential predictor despite low correlation (1.93%). When paired with precipitation data, this two-variable combination achieved 99.81% R², outperforming complex multi-variable models. Satellite data consistently surpassed ground measurements, with 9 of the top 10 predictors being satellite derived. Our approach reduces model complexity while improving forecasting accuracy, providing practical solutions for energy systems. Full article

The global scarcity of freshwater, driven by population growth and the unequal distribution of water resources, has intensified the need for alternative water supply technologies. Among the most promising solutions, adsorption-based atmospheric water harvesting (AWH) systems offer the ability to extract water vapor directly from ambient air, even under low-humidity conditions. This review presents a comprehensive overview of the thermodynamic principles and material characteristics governing these systems, with particular emphasis on adsorption isotherms and their role in predicting and optimizing system performance. A generalized theoretical framework is proposed to assess the energy efficiency of thermally driven AWH devices, based on key material parameters. Recent developments in sorbent materials, especially metal–organic frameworks (MOFs) and advanced zeolites, are examined for their high-water uptake, regeneration efficiency, and potential for operation under real climatic conditions. The Dubinin–Astakhov and modified Langmuir isotherm models are reviewed for their effectiveness in describing nonlinear sorption behaviors critical to performance modeling. In addition, component-level design strategies for adsorption-based AWH systems are discussed. The integration of solar energy is also discussed, highlighting recent prototypes and design strategies that have achieved water yields ranging from 0.1 to 2.5 L m⁻²/day and specific productivities up to 2.8 L kg⁻¹ using MOF-801 at 20% RH. Despite notable progress, challenges remain, including limited productivity in non-optimized setups, thermal losses, long-term material stability, and scalability. This review concludes by identifying future directions for material development, system integration, and modeling approaches to advance the practical deployment of efficient and scalable AWH technologies. Full article