Search Results (9,144)

Water scarcity in semi-arid regions makes efficient irrigation scheduling a priority, yet farm-level adoption of soil-moisture monitoring remains limited by the cost, low portability and installation complexity of commercial sensing systems. This study presents the development and field validation of WaziSense, a low-cost, solar-powered Internet-of-Things (IoT) smart tensiometer, developed within the OSIRRIS platform for soil-water monitoring and irrigation scheduling. The device couples a Watermark granular-matrix sensor and a DS18B20 temperature probe to an ATmega328P microcontroller (Arduino Pro-Mini, 3.3 V, 8 MHz) with long-range LoRa communication and a maximum-power-point-tracking (MPPT) solar-charging stage, logging soil matric potential and soil temperature every 15 min. An open-source edge/cloud stack (WaziGate, WaziApp) retrieves weather forecasts from an open API and runs an automated machine learning (AutoML) regression pipeline that forecasts soil-water dynamics and the time to a user-defined threshold, from which irrigation is scheduled and its applied volume verified by a flow meter. The system was deployed at three bioclimatic sites in Tunisia (durum wheat at Cherfech, citrus at Nabeul, apple at Sbeitla), with tensiometers installed at 20 and 40 cm depths, and validated against commercial 10HS capacitive probes coupled to a ZL6 data logger, with which the co-located readings were significantly correlated (r = 0.81). Calibrated readings showed a strong relationship between soil–water content and soil–water potential (R² = 0.99), and the edge forecasting model reproduced soil–water dynamics on unseen data (Sbeitla apple site, 5-day horizon) with R² = 0.73, RMSE = 0.35, MAE = 0.23 and MPE = 12.52%. With a material cost under about 90 EUR per node and fully open-source hardware and software, WaziSense is one to two orders of magnitude cheaper than commercial monitoring stations, offering an affordable, reproducible and scalable tool for data-driven irrigation in water-limited agriculture. Full article

This research presents a straightforward and detailed method for calculating the cost of recycling solar panels and the associated economic benefits. The contribution of this research is to estimate the impact of the recycling process on the cost of energy and the payback period. The Full Recovery End-of-Life Photovoltaic (FRELP) method was utilized to assess the PV recycling process. Calculations were made for every 1000 kg of solar panels and converted to calculate the cost and revenue per square meter of panels. Calculations showed that the cost of recycling in Saudi Arabia reached 9.46 $/m² based on the geographical environment, fuel prices, and the various materials used in recycling processes, while the revenue was approximately 24.6 $/m² according to the current prices of materials resulting from the recycling process, especially the price of silver. The study results were applied to a 400 MW solar power plant to determine the feasibility of recycling the energy price and the payback period. The solar power plant was designed using variable-sized solar panels with capacities of 255, 330, and 580 watts. The recycling revenue for the plant with the smaller panels was the highest, being $2.6 M as an annual rate. Full article

In this work, Cu₂CoSnS₄ (CCTS) thin films were deposited on glass substrates by thermal evaporation and investigated for photovoltaic applications. The influence of substrate temperature, varied from 25 °C to 200 °C, on the structural, morphological, and optical properties of the films was experimentally studied using X-ray diffraction (XRD), scanning electron microscopy (SEM), and photoluminescence (PL) measurements. XRD analysis confirmed the formation of crystalline CCTS with a stannite structure and a preferential orientation along the (112) plane. SEM observations revealed rough and non-uniform surfaces accompanied by an increase in grain size with increasing substrate temperature. Room-temperature PL measurements indicated a band-gap energy of approximately 1.3 eV, suitable for photovoltaic applications, and confirmed the presence of secondary phases in the p-type stannite CCTS films. Despite the promising photovoltaic properties of CCTS, numerical studies on CCTS-based solar cells remain scarce in the literature. In this context, a numerical study of the CCTS-based solar structure grown on glass was also performed using SCAPS-1D, showing good agreement with experimental photovoltaic results and validating the simulation model. Replacing the glass substrate with silicon improved the device efficiency to 5.77%. Further optimization of the series and shunt resistances significantly enhanced the photovoltaic performance, achieving a power conversion efficiency of 16.77%, with FF = 52.94%, V_oc = 0.89 V and J_sc = 35.19 mA/cm². Full article

Reverse osmosis (RO) desalination is a major technology for freshwater production in arid regions, but its energy demand becomes more challenging when the system is supplied by variable renewable energy. This study presents an offline digital-twin-assisted decision-support framework for dynamic RO under Kuwait solar-availability conditions. Within this framework, the predictive models are driven primarily by the dynamic RO process variables, while NASA Prediction Of Worldwide Energy Resources (POWER) data provide the Kuwait solar-availability context, and the PV power margin serves as a scenario-level energy indicator. The purpose is to predict instantaneous permeate flow rate, estimate specific energy consumption, and identify energy-efficient operating conditions using machine learning. Kuwait City was used as the solar case-study location. Hourly solar and meteorological data were obtained from NASA POWER, while dynamic RO membrane data were obtained from the open experimental wave desalination dataset published by the National Renewable Energy Laboratory (NREL) through Data.gov and the Marine and Hydrokinetic Data Repository. The RO dataset includes steady-state, ramp, sinusoidal, and Wave Energy Converter SIMulator (WEC-Sim) pressure/flow experiments. The process-flow image used in the system description was also taken from the same NREL dataset and is cited in the figure caption. The raw RO files were cleaned, harmonized, and transformed into a process-informed modeling dataset. Derived features included pressure rate, recovery ratio, salt rejection, estimated pump power, specific energy consumption (SEC), PV power margin, and rolling pressure/flow features. Three supervised regression models were tested: Gradient Boosting, Random Forest, and XGBoost. A representative subset of 60,000 records was used to preserve the main experimental conditions while reducing redundancy in the densely sampled sequential data. Results show that permeate flow rate can be predicted with high accuracy using Gradient Boosting (R² = 0.981; RMSE = 0.161 L/min). The moderate energy prediction performance yielded an R² of 0.654 and RMSE of 7.570 kWh/m³ for Random Forest. The accuracy of permeate conductivity predictions was lower (R² = 0.257; RMSE = 245.44 µS/cm) because membrane and feed characterizing parameters should be included for an adequate water quality control. The proposed approach is best suited as an offline decision-support framework for dynamic RO process analysis. Full article

This study investigates the dominant mechanisms governing transient-voltage evolution in hydro–wind–solar hybrid systems to address practical engineering requirements. A quantitative index system is constructed to evaluate the factors affecting system transient voltage, and the impacts of key factors are quantified. Specifically, the voltage drop during system faults is mainly affected by fault location and network structure, whereas post-fault recovery depends more on the collaborative process of dynamic reactive power balance and multi-time-scale control. A multi-level transient voltage quantification method is proposed to identify system influencing factors and weak points. The evaluation system comprises maximum voltage drop depth, voltage recovery time, transient voltage severity index (TVSI), hierarchical aggregation indicators, and system-level SSI indicators. The ability of these indicators to characterize systemic risks and disturbance propagation effects is enhanced by introducing fault-point extreme-value correction. The key mechanisms affecting transient voltage stability of hydro–wind–solar hybrid systems are clarified. Multi-scenario analysis shows that transient voltage risks are mainly concentrated in the 220 kV and 110 kV collection layers and are most sensitive during the recovery stage after fault clearing. Detailed quantitative analyses are conducted on four influencing factors: fault location, wind and solar power output, wind-to-solar ratio, and renewable energy penetration rate. Full article

The 4 km/15 min downward surface shortwave radiation (DSSR) product from Fengyun-4B (FY-4B)/AGRI shows great potential for solar energy assessment in China, but its applicability requires further validation. This study conducts a comprehensive evaluation of the FY-4B DSSR product over Guangxi for 2025, using ground-observed irradiance from a dense network of 101 photovoltaic (PV) power stations. The overall comparison shows a correlation coefficient (R) of 0.84, a root-mean-square error (RMSE) of 161.78 W/m², a relative prediction error (RPE) of 51.02%, and a mean bias error (MBE) of 56.23 W/m², indicating systematic overestimation. Seasonally, the largest discrepancies occur in spring (MBE = 85.27 W/m², RPE = 53.12%) and summer (R = 0.82, RMSE = 184.10 W/m²). Diurnally, retrievals are most reliable around 09:00–13:00 local time, deteriorating notably in the early morning and, especially, the afternoon and evening. Spatially, errors are larger in the hilly, elevated terrain of northwestern Guangxi (e.g., Hechi) than in flatter southern and coastal cities, with RPE rising from roughly 40–60% at lower elevations to around 80% above 600–700 m. Sky-condition classification confirms that data quality follows clear > cloudy > overcast sky, while AOD-binned analysis shows aerosol loading playing a secondary but non-negligible role, especially under high-AOD pollution events. Solar zenith angle (SZA) also strongly affects accuracy: R peaks around 0.75–0.8 in the 30–50° SZA range and drops below 0.4 beyond about 75°. This study offers the most spatially and dimensionally comprehensive validation of FY-4B DSSR over Guangxi to date, characterizing accuracy across seasonal, diurnal, spatial, cloud, aerosol, solar-geometry, and elevation dimensions using a denser ground-truth network than previously available, with direct implications for photovoltaic resource assessment and power forecasting in subtropical hilly regions. Full article

Fresnel high-concentration photovoltaic/thermal (HCPV/T) systems operating in sandy environments are susceptible to natural lens soiling, which attenuates the effective concentrated solar input and alters electrical and thermal performance. Natural-soiling comparison tests were conducted over 0–28 d, and an SD-CNN-BiLSTM-Attention model was developed to forecast cell-center temperature and electrical power 5, 10, and 20 min ahead. At a surface soiling density of 10.760 g·m⁻², current and electrical power decreased by 38.37% and 39.28%, respectively, relative to the concurrently operated clean-reference unit; cell-center temperature and water-tank temperature rise decreased by 7.74% and 15.13%. Thermal power also showed an overall downward trend, although the magnitude was affected by relatively large measurement uncertainty. Under grouped cross-validation, temperature RMSEs were 0.473, 0.515, and 0.555 °C at 5, 10, and 20 min, corresponding to reductions of 8.34%, 21.68%, and 44.07% relative to Persistence. Electrical-power RMSEs were 0.661, 0.618, and 0.640 W, with an 18.24% reduction relative to Persistence at 20 min. Ablation analysis showed a limited contribution from surface soiling density at 5 and 10 min but a clearer contribution at 20 min. These results support electrical and thermal performance assessment and short-term operational forecasting of Fresnel HCPV/T systems in sandy environments. Full article

Organic solar cells (OSCs) and perovskite solar cells (PSCs) are emerging photovoltaic technologies owing to their high efficiency, low-cost processing, and diverse applications ranging from utility-scale power generation to small-scale electronics. A key advantage of OSCs and PSCs over traditional silicon-based solar cells is their solution-processability, which enables fabrication via cost-effective scalable printing technologies suitable for commercialization. In addition to organic and perovskite photoactive layers, other functional layers, including interfacial layers and electron and hole transport layers, can also be processed using solution-based printing techniques. However, the conventional architecture of these emerging photovoltaics relies on vacuum-based deposition processes for both oxide-based electrodes (e.g., indium tin oxide and fluorine tin oxide) and metallic top electrodes (e.g., Au, Ag, Cu, and Al), which contrasts with printing-based processing. The implementation of printing technologies for electrode fabrication is necessary to achieve low-cost production and flexible photovoltaic applications. Herein, we review printed electrodes—including metal electrodes, conductive polymers, and carbon-based materials—used to fabricate OSCs and PSCs. Full article

Photovoltaic converters operate under varying climatic conditions and non-ideal grid regimes, but factor importance is often assessed either through isolated local metrics or through pooled operating data that hide regime shifts and interaction effects. This study develops a hierarchical framework for sensitivity analysis of operating profiles of grid-connected PV converters under climatic and grid uncertainty. A compact operating-profile formulation is introduced that relates solar radiation, cell and ambient temperature, grid voltage, load, and selected design/control parameters to active power, efficiency, power factor, harmonic distortion, DC bus ripple, clipping behavior, and thermal headroom. The proposed workflow combines local normalized sensitivities for fast ranking around nominal conditions, Morris screening for factor reduction, and Sobol/Saltelli variance-based indices for global prioritization under uncertainty. The framework is demonstrated on a 100 kW synthetic reduced-order benchmark representing a three-phase two-level grid-connected PV inverter with an LCL filter. To clarify the scope of validity, the reduced-order model is cross-checked against switching-level simulations for representative nominal, clipping-prone, high-temperature and grid-stress operating windows. The results show that factor importance is not universal, but depends on the selected KPI, operating regime and uncertainty scenario. In the considered benchmark, grid voltage, cell temperature and equivalent thermal resistance are the dominant total-effect contributors, while the strongest second-order contribution appears between grid voltage and filter inductance under grid-stress conditions. The proposed framework is therefore intended as a reproducible, regime-aware sensitivity workflow rather than as a universal ranking of PV converter parameters. Full article

Building Information Modeling (BIM)-enabled performance assessment workflows for rural constructions remain relatively unexplored. This is even more important for buildings implementing process-oriented systems, such as airflow networks. This study presents a BIM-integrated framework for the early-stage design and performance assessment of rural constructions, with application to solar barn dryers and their ventilation systems through reduced-order airflow-network modeling. The proposed workflow combines parametric BIM-based geometry generation with lumped-parameter fluid-dynamic modeling to evaluate the influence of airflow-network topology on pressure losses, airflow distribution, fan power demand, and energy consumption. Nine BIM-generated design alternatives and ten geometric parameter sets were investigated under equivalent operating conditions. The airflow system was represented as a pressure-driven network including solar air panels, ducts, collectors, fan chambers, ventilation channels, and drying cells, accounting for both localized and distributed pressure losses. Results show that airflow-network geometry significantly affects system performance. Configurations characterized by more compact and aerodynamically efficient layouts reduced cumulative pressure losses by approximately 10–20% compared with less optimized solutions. More efficient designs enable reductions in required airflow rates of ~22% and in fan power demand of up to ~40% (≈11–18 kW). The most efficient configurations also exhibited lower annual energy consumption while maintaining the minimum overpressure required for effective hay drying. The study demonstrates how BIM environments can support physics-informed comparative evaluation of alternative ventilation layouts during the early design stage, extending BIM applications toward performance-oriented design and digital management of agricultural building systems. The proposed methodology provides a computationally efficient design-support framework that may also apply to other controlled-environment agricultural infrastructures governed by airflow-network dynamics. Full article

Hybrid solar–thermal energy harvesting systems are an important advancement in renewable energy technology, enabling simultaneous production of electrical power and useful thermal energy within a single compact platform. However, their performance is often limited by poor heat transfer and inefficient mass transport of working fluids, leading to photovoltaic thermal degradation and significant exergy losses. This study aims to optimize heat and mass transport processes in a hybrid solar–thermal mechanical system to enhance energy recovery and ensure long-term operational reliability. A three-dimensional numerical model based on the finite volume method (FVM) was developed using the governing equations of continuity, momentum, and energy conservation. A Multi-Objective Genetic Algorithm (MOGA) was employed to determine optimal microchannel geometries by analyzing variable cross-section effects on flow behavior and thermal boundary layer disruption. At the Reynolds number of 2000, the optimized configuration increases the average Nusselt number by 43.5% compared to a smooth channel. Consequently, the photovoltaic operating temperature decreases by 12.6 °C, improving electrical efficiency by 9.3%. The system achieves a maximum thermal efficiency and net energy gain of 76.8%, while maintaining an acceptable 16.3% increase in pumping power. The results confirm that optimizing mass transport is essential for effective thermal regulation and improved energy conversion performance, providing a strong foundation for high-efficiency solar collector design. Full article

Grain boundaries (GBs) are important recombination-active defects in polycrystalline and multicrystalline silicon solar cells, but the effects of their electrical activity, geometry, and spatial arrangement are often difficult to separate. In this work, two-dimensional (2D) drift–diffusion simulations are used to investigate how GB trap density, carrier capture cross-section, orientation, length, number, and network geometry affect silicon solar-cell performance. A controlled comparison between rotating GBs whose length changes with angle and fixed-length GBs shows that the strong apparent orientation dependence is dominated by the accompanying variation in active GB length. When the GB length is fixed at 100 μm, the variations in short-circuit current density ($J_{\mathrm{sc}}$), open-circuit voltage ($V_{\mathrm{oc}}$), efficiency, and fill factor are comparatively small. As a second contribution, irregular polycrystalline microstructures are generated by Voronoi tessellation, producing distributions of grain sizes, shapes, boundary lengths, and junctions that are more representative than simplified structures based on isolated or regularly spaced boundaries. These networks are used to connect grain size, total electrically active GB length, recombination, local electric fields, carrier-flow redistribution, and device performance. As the characteristic grain size increases from 5 to 100 μm, $J_{\mathrm{sc}}$ rises from 15 to $34\mathrm{mA}{\mathrm{cm}}^{-2}$, $V_{\mathrm{oc}}$ from $0.54$ to above $0.61$ V, and the power conversion efficiency from $6.5\%$ to $17\%$. GB-induced photovoltaic loss is therefore governed not by GB number or nominal orientation alone, but by the combined effects of electrical activity, total active boundary length, and network geometry. Full article

A transition towards sustainable transportation requires efficient integration of electric vehicles (EVs) with renewable energy sources. This work proposes a two-stage Parking Lot Energy Management Scheme (PLEMS) to minimize charging costs while maximizing solar photovoltaic utilization in commercial parking facilities. In the first stage, the optimization phase is formulated using a mixed-integer linear programming (MILP) that minimizes the overall cost of EV charging while ensuring maximum utilization of locally available PV energy. In the second stage, a gated recurrent unit (GRU)-based deep learning model performs state of charge (SOC) forecasting for EVs parked in the parking lot. Using the predicted SOC for the next time step, the system decides whether each EV will be charged or discharged, ensuring consistency with the cost-optimal MILP strategy from the first stage. The proposed PLEMS achieves up to 62% daily cost savings in charging compared to uncoordinated direct grid charging. However, this cost saving is the outcome of proposed optimization as well as the integration of PV panels in power grid. When compared with nine similar vehicles to grid (V2G)-enabled approaches from the literature, which report cost savings ranging from 9.73% to 52%, the proposed framework shows an improvement of 10% to 52% over these methods. This hybrid MILP-GRU framework offers practical V2G operation and high scalability for large EV fleets in solar-powered smart parking lots. Full article

Large-scale renewable energy bases with high penetration of renewable energy are facing increasing challenges related to renewable energy curtailment. Concentrated solar power plants with thermal energy storage can provide dispatchable power output, while electric heaters offer a promising pathway for converting surplus renewable electricity into useful thermal energy. In this study, a photovoltaic–wind turbine–electric heater–concentrated solar power integrated energy system with a fixed CSP-EH configuration is investigated. The electric heater is introduced as the key electrical-thermal coupling device, which recovers otherwise curtailed photovoltaic and wind power and injects the converted thermal energy into the heat transfer fluid loop of the concentrated solar power plant. A mixed-integer linear programming model is developed to optimize the coordinated scheduling and evaluate different PV/wind capacity mixes under fixed CSP and electric-heater capacities. Results show that, under the fixed capacities of 100 MW concentrated solar power and 150 MW electric heater, the PV/wind capacity mix of 500 MW photovoltaic and 400 MW wind power achieves the best overall performance among the studied cases. Under different typical-day conditions, the electric heater recovers surplus renewable electricity, with recovery rates ranging from 16.06% to 20.21%. The proposed electric heater–concentrated solar power coupling mechanism transforms curtailed renewable electricity into dispatchable thermal energy, thereby reducing renewable energy curtailment, enhancing thermal-side flexibility, and improving the operating revenue of large-scale renewable energy bases under the studied PV/wind capacity-mix scenarios. Full article

This examines the development of the saltpeter industry in Chile after the War of the Pacific (1879–1883), a conflict between Chile and a Bolivian–Peruvian alliance. Chile’s victory meant the annexation of the territories of Antofagasta and Tarapacá, effectively controlling the production of sodium nitrate and the global saltpeter monopoly. Industrial development was reflected through changes in foreign and Chilean capitals, technologies, and work practices. In Tarapacá, the most important investments in the 19th century were British and German. In Antofagasta, Chilean, English, German, and Croatian investments were prominent in the 19th and 20th centuries. And since 1926, American capitals have occupied the spotlight. The dominant technologies were the Shanks system between 1880–1926, the Guggenheim from 1926–1954, and the introduction of Solar Evaporation in the 1950s. Work evolved from manual artisanal labor without legal protection to mechanization under social laws. Saltpeter represented, in the social and economic history of Chile, the rise of the proletariat, communal social movements, a strong labor press, and a series of strikes and massacres. From the saltpeter era sprouted powerful literature, poetry, and music throughout the 20th century until today. The nitrate industry reached its peak between 1881 and 1917. During this period, it had to confront competition from synthetic nitrate and ceased to be the main source of revenue for the national treasury of Chile. This was followed by a period of decline and crisis from 1918 to 1931, the latter intertwined with the global financial crisis. Various state and business measures made it possible for a small number of nitrate oficinas (processing plants and settlements) in Tarapacá and Antofagasta to continue operating until the nationalization of the nitrate industry in 1971. The nitrate industry took place during the first globalization of liberalism, one that brought flows of capital, migration from Europe to the American Continent, changes to marine navigation, and the opening of various markets in Asia, Europe, and Africa. Nitrate became the most effective fertilizer for agriculture and replaced guano in crop production. In order to analyze this topic, we will utilize the results of the main monographic studies, texts used for historical and political context, and works with interpretative theses about specific periods of nitrate production. Full article