Search Results (6,533)

Energy storage systems (ESSs) installed alongside traditional photovoltaic (PV) power plants are primarily used to track planned output, which often results in low utilization rates and extended payback periods. Moreover, existing research inadequately addresses actual grid frequency fluctuation characteristics and lacks multi-timescale optimization frameworks. To address these issues, this paper proposes a day-ahead and intraday multi-market coordinated rolling optimization strategy that integrates energy market trading with Automatic Generation Control (AGC) frequency regulation services through a zone-based frequency regulation control strategy. The strategy first defines distinct regulation zones based on regional control deviations, enabling a dynamic power allocation approach for the energy storage system. Recognizing that conventional constant power control can lead to battery overcharging, over-discharging, and reduced cycle life, the strategy introduces state of charge (SOC)-based variable power charging and discharging constraint coefficients. These constraints ensure the battery operates safely within its optimal range. Furthermore, an electrochemical energy storage life decay model is developed to quantify battery degradation. To accommodate the uncertainty in PV output, Latin hypercube sampling is employed. A day-ahead dispatch model is established to maximize the system’s total daily operating revenue, and rolling optimization is applied during the intraday phase to correct deviations from the day-ahead forecast. Finally, simulation studies using actual data from a PV power plant demonstrate that the proposed strategy achieves a total daily revenue of 107,477 ¥, representing a 24.6% improvement over energy market-only participation; battery aging costs are reduced by 11.1% compared to the scenario without zone-based frequency regulation control. Results indicate that the proposed strategy effectively balances battery life degradation against market revenue, significantly improving the overall operational efficiency and economic viability of PV-storage hybrid systems. Full article

Reliable air pollution monitoring remains a major challenge in Sub-Saharan Africa (SSA), limiting the assessment of population exposure and the development of effective mitigation strategies. Recent advances in low-cost (LC) sensors offer promising opportunities, but their deployment in low-infrastructure settings still faces significant technical and logistical challenges. This study presents the experience gained from deploying LC sensor networks in Burkina Faso, Niger, and the Republic of Guinea, focusing on the practical challenges of installing and maintaining these systems under demanding conditions. In Burkina Faso, an LC station was co-located with a reference-grade instrument, enabling field calibration. In Niger, factory-calibrated LC sensors were deployed across urban, semi-urban, and rural settings, while in Guinea they were installed in a remote area. Several practical issues and challenges emerged, including unstable power supplies, limited internet connectivity, safety, and logistical constraints. Careful planning and involvement of local expertise proved essential for the long-term sustainability of LC sensors. Knowledge transfer to local partners supported ongoing maintenance and strengthened data ownership. Overall, this study demonstrated that the reliability of LC air quality networks in SSA depends not only on technology, but also on adaptive strategies, robust calibration, and strong local engagement, offering practical guidance for future scalable and sustainable implementations in resource-limited settings. Full article

The rapid development of wind and solar energy necessitates a solution to the problem of the optimal spatial placement of wind farms (WFs) and solar farms (SFs) within electric power systems. The non-stationary generation schedules of WFs and SFs place increased demands on the flexibility of conventional generation, determined by the intensity of net load fluctuations. This paper proposes a methodology for the spatial optimization of WF and SF location, in which the optimization criteria include net load indicators (rate of net load change and net load increment), the base power of the RES system, and the economic criterion of maximum electricity generation. Unlike existing approaches, in which the geographical smoothing effect on power fluctuations is treated as an incidental outcome, the proposed methodology employs it as an explicit optimization criterion for RES placement. The algorithm provides for the preliminary ranking of candidate sites based on the maximum electricity generation criterion, followed by the redistribution of generating capacities among sites with an acceptable capacity factor in accordance with the selected optimization criterion. The methodology was tested on a model comprising six potential wind farm sites and two solar farm sites with a total installed capacity of 600 MW and a maximum power system load of 3000 MW. The obtained results show that the optimal redistribution of installed capacities among sites allows a 31.5% reduction in net load variability intensity to be achieved with an 11.6% reduction in electricity generation relative to the maximum possible. The study is based on idealized daily generation and consumption profiles and is theoretical in nature, proposing a pre-screening tool for RES siting that complements rather than replaces subsequent network-constrained planning studies, including power-flow analysis and grid verification, and establishes a methodological foundation for further development using real multi-year retrospective data. Full article

Line confocal sensors provide non-contact, high-resolution, and high-efficiency measurement and can be integrated into optical measurement systems such as Photon for three-dimensional topography measurement of complex surfaces. However, installation-induced tilt-pose errors of the sensor can couple height information with lateral position, thereby reducing the accuracy of profile reconstruction. To address this issue, this paper proposes a calibration-block-based tilt-pose error identification and compensation method for line confocal sensors. Using the known geometric features of the calibration block, the proposed method establishes a mapping relationship between sensor tilt-pose errors and measured profile distortion. Sensitivity analysis is performed to identify the dominant error components, and the tilt-pose errors are estimated in a single identification process, enabling quantitative compensation of the measured point cloud. Experimental results show that, after calibration and compensation, the maximum Z-direction height difference in the overlapping profile region of the calibration block is reduced from 12.782 μm to 0.307 μm. The proposed method requires no complex external alignment devices and provides an effective approach for high-precision integrated applications of line confocal sensors. Full article

This study examined how older adults living in public rental apartment complexes perceive and interpret information signs related to wayfinding, facility use, and safety. A questionnaire survey was conducted with 80 residents aged 65 years and older in two public rental apartment complexes in Nowon-gu, Seoul, and 12 participants with varying levels of cognitive function were selected for an eye-tracking experiment. The survey identified small sign and font sizes, insufficient color contrast and clarity, and inappropriate installation locations as the main problems. Time to First Fixation (TTFF) and dwell time were analyzed. Signs with clearer contrast against the background and increased sign size tended to elicit more favorable visual responses, whereas adjusting font size alone had limited effects. Heat map and scan path analyses also showed that the cognitively impaired group had more widely dispersed visual exploration patterns. Due to the limited sample size, statistical significance could not be sufficiently verified, and the findings cannot be generalized. Nevertheless, older adults’ subjective perceptions did not always correspond to the objective experimental results. Information sign improvements should therefore consider both rapid detection and ease of reading. Full article

The rapid transition toward renewable energy requires transparent and spatially explicit methods for identifying suitable photovoltaic (PV) development areas. This study develops a geospatial artificial intelligence (GeoAI) decision-support framework for PV site suitability assessment in Rajasthan, India. Eleven harmonized predictors were used: global horizontal irradiance (GHI), photovoltaic power output (PVOUT), temperature, wind speed, aerosol optical depth (AOD), elevation, slope, albedo, land use/land cover (LULC), distance to roads, and distance to power lines. Reference labels were generated from an explicit rule-derived suitability index, class thresholds, and exclusion logic; therefore, the machine-learning task was to reproduce a transparent suitability framework rather than to predict observed PV yield or project-level performance. Extreme Gradient Boosting (XGBoost) was compared with simpler baseline models, evaluated using random and spatial-block validation, and interpreted using SHapley Additive exPlanations (SHAP). Independent overlays with known solar-installation records, presence-background robustness testing, and uncertainty/sensitivity analysis were used to examine spatial plausibility, spatial autocorrelation, deterministic label effects, and parameter uncertainty. The resulting outputs include pixel-level suitability zones, contiguous candidate polygons, district-level capacity-oriented summaries, and planning-priority classes. The framework is intended as a risk-aware regional screening tool: high model agreement indicates consistency with the constructed suitability labels, while final project decisions require parcel-scale land, grid, environmental, social, and economic assessment. Full article

Temperate broadleaved forests support diverse arthropod communities, but canopy-dwelling insects in European lime (Tilia cordata Mill.) stands are still poorly known. We surveyed light-attracted canopy insects in six T. cordata Genetic Conservation Units and related protected stands across Lithuania. One modified, solar-powered UV light trap was installed in the canopy (10–15 m) at each site and operated twice per month from June to August in 2023 and 2024. We used diversity metrics, similarity indices, multiple regression, and non-metric multidimensional scaling (NMDS) together with PERMANOVA to examine the structure of insect communities and assess the influence of environmental factors. In total, 6031 individuals representing 295 insect species were recorded, with higher abundance, species richness and Shannon diversity in 2024 than in 2023. Across both years and all sites, Shannon H diversity index ranged from 3.21 to 3.92. Sørensen indices indicated moderate species similarity among sites and distinct species composition at the Ukmergė genetic reserve. The 20 most abundant taxa comprised over 60% of all individuals, and dominance structure changed markedly between years: Serica brunnea dominated in 2023 but was nearly absent in 2024. Regression revealed a significant positive effect of air temperature on insect abundance (about a 31% increase per 1 °C), while precipitation had no significant effect on insect abundance. NMDS and PERMANOVA showed strong spatial structuring, with sites explaining most of the variation, and weaker but significant temporal and site-by-year effects. Overall, insect diversity metrics showed non-significant correlations with T. cordata genetic diversity parameters. Results demonstrate that mature T. cordata forest stands are important reservoirs of canopy insect diversity and highlight pronounced spatial heterogeneity, interannual dynamics, and temperature sensitivity of canopy assemblages in Lithuanian forests. Full article

Microplastics, MPs, plastic particles with dimensions between 0.1 and 5 mm, represent an important environmental pollutant. The removal of microplastics from natural and wastewater is a challenging research topic. In this regard, high-performance technical solutions must be identified, which can be based on existing treatment and purification technologies, to ensure their removal at concentration values in accordance with the legislation in force. In this study, the efficiency of removing some fractions of polyurethane microplastics, with dimensions smaller than 500 µm, from aqueous synthetic solutions with a concentration of 0.2 g L⁻¹, i.e., around 175 NTU, was evaluated. In the first stage of the study, the doses of coagulants and flocculants effective for the removal of microplastics were identified through the Jar Test. The variation in turbidity and their removal efficiencies were evaluated in the presence of classic coagulants, such as aluminum sulfate, Al₂(SO₄)₃·18H₂O, SA; iron sulfate (ferrous sulfate), FeSO₄, IS; polyaluminum chloride, [Al₂(OH)_nCl_6−n], PAC; Aloe Vera, AV, a flocculant; and activated carbon, AC, of the Norit GAC 830 W type. Classic coagulants, such as aluminum sulfate, have a good efficiency in removing microplastics, being able to provide a residual turbidity in the range of 6–10 NTU after a retention time of 50–60 min. In the second stage of the study, the removal efficiency of microplastics was tested using a laboratory pilot plant—called in the study the Smart Decantation-Filtration System, SDFS. The efficiency of the decanter was studied using Response Surface Methodology (RSM) to identify mathematical models that characterize the influence of key process variables: flow rate (A), microplastic size (B) and aluminum sulfate concentration (C) on microplastic removal efficiency. Sedimentation in the specially constructed decanter can raise the optimal value of the removal efficiency of polyurethane microplastics to 98.98%, and filtration can ensure an efficiency that reaches over 99.5%. Through this research, we aimed to identify viable solutions that can be applied to remove microplastics, MPs, from natural and wastewater. A novel element is the fact that we chose to study the removal of polyurethane, which is studied little in the literature. We identified the optimal doses of coagulants and flocculants that help sedimentation of MPs. The efficiency of an installation called Smart Decantation-Filtration System, specially designed to ensure increased efficiency in the removal of microplastics, was determined. The results obtained were encouraging. Full article

Introduction: The Touvedo hydropower plant, located on the Lima River 47 km from its mouth, is equipped with a fish lift (2.14 m long × 1.29 m wide × 2.85 m high) on the left bank designed to facilitate fish migration past the dam. This mechanical system attracts fish by means of a guide current, traps them in a water-filled cage, and then lifts and releases them upstream, enabling passage over the dam. Within the framework of the Sustainability Policies from the EDP Group, particularly those related to Environment and Biodiversity, and under the Eel Management Plan, a long-term video-monitoring program has been implemented since 2011 to collect data on the species using the device and to evaluate its effectiveness. Objective: This study aims to present and analyze nine years of video-monitoring data collected across three programs—the “Action Plan for the Optimization of the Fish Lift at the Touvedo Hydroelectric Facility (2011/2014)”, which aimed to diagnose and assess the effectiveness of the fish lift and to define and implement measures needed to optimize its operation; “Video Monitoring of the Touvedo Fish Lift (2017/2020)”, that was carried out as a follow-up to the Action Plan; and more recently, a new video-monitoring project (2021–2024) which was implemented to expand the dataset and validate the patterns observed in the previous studies. Methodology: The fish lift was continuously monitored using an automatic video-recording system, which consists of a video camera installed at the top of the lift to capture images of the trapping cage during the final stage of its ascent, and a server for video storage. The trapping cage is lined with 20 cm × 20 cm white tiles to increase contrast and allow estimation of fish body length. Collected data included the timing of fish passage (day and hour), the number of fish per cycle, species-level identification and the estimated total length of each individual. Results: The European eel (Anguilla anguilla) has remained the dominant species using the lift, and, consistent with observations from Video-Monitoring 1, the Iberian barbel (Luciobarbus bocagei) has become the second most representative species, replacing the northern straight-mouth nase (Pseudochondrostoma duriense), whose proportion has declined. Brown trout (Salmo trutta) showed a slight but continued increase in Video-Monitoring 2, following the decrease recorded in Video-Monitoring 1 compared to the Action Plan. Conclusions: These results highlight the importance of continuing video monitoring of the Touvedo fish lift to assess its operability, confirm the observed passage patterns, determine the success of the implemented improvements, and evaluate the possible need for additional measures. Full article

Improving residential energy efficiency is essential to meeting UK net-zero targets, yet retrofit uptake in the private rented sector (PRS) remains limited. While many studies examine retrofit measures or Energy Performance Certificates (EPCs), few integrate comparative technology performance, cost–benefit outcomes, and landlord–tenant perspectives within a single housing context. This paper addresses that gap through a mixed-methods case study of a professionally managed private rented housing portfolio in South London, assessing four retrofit technologies: photovoltaic (PV) panels, air source heat pumps (ASHPs), double glazing (DG), and insulation. Quantitative analysis showed that ASHPs delivered the greatest EPC improvement, with 54.5% of properties achieving a two-band uplift, while PV panels offered the strongest financial return, with an average payback period of 11.7 years. Houses achieved the strongest overall results, with combined PV + ASHP retrofits delivering the best technical and financial performance; however, this pairing was only feasible in houses because of the physical requirements for both roof space and external unit installation, whereas flats and maisonettes were more constrained by space and installation feasibility. Stakeholder analysis findings revealed knowledge and incentive gaps: many tenants overestimated the effectiveness of double glazing, while landlords identified high upfront costs and delivery challenges as key barriers. Wider PRS decarbonisation will therefore require stronger policy support, streamlined retrofit delivery, and improved tenant awareness. Full article

Hybrid renewable energy systems are regarded as one of the most promising solutions for the autonomous power supply of remote and weakly electrified sites, where diesel generation remains a costly and carbon-intensive energy source. This study presents the optimization of an off-grid PV/BESS/DGU microgrid for three representative regions of Kazakhstan—North, Central/East, and South/South-West—under different environmental scenarios. The aim of the study was to determine the optimal installed photovoltaic capacity, battery storage capacity, diesel generator rated power, and annual load coverage balance using the Generalized Reduced Gradient (GRG) method. The optimization was carried out using two objective functions: the conventional levelized cost of electricity, $LCOE$, and the environmentally adjusted cost of electricity, ${LCOE}_{\mathrm{e}\mathrm{n}\mathrm{v}}$, which includes the monetized cost of emissions associated with diesel generator operation. The model was formulated as a constrained nonlinear programming problem incorporating hourly energy balance, battery state-of-charge constraints, diesel generator operating constraints, and carbon price scenarios of 0, 25, 50, and 100 USD/tCO₂. The results show that an increase in the carbon price systematically shifts the optimum toward a higher share of photovoltaic generation and reduced diesel generator use in all regions. The strongest response is observed in the South/South-West region, followed by Central/East, whereas the North exhibits the lowest sensitivity due to the more pronounced seasonality of solar generation. Under the considered scenarios, the optimal PV capacity increases by approximately 24–28%, while the share of diesel generation in annual load coverage decreases by approximately 28% in the North, 44% in Central/East, and 61% in the South/South-West. At the same time, the rated diesel generator capacity remains unchanged in most scenarios, indicating the persistence of its backup function. The results confirm that the PV/BESS/DGU configuration constitutes a technically and economically justified baseline architecture for autonomous power supply under Kazakhstan’s conditions, while the inclusion of environmental costs supports the cost-effective displacement of diesel generation. The GRG method proved to be suitable for the transparent and efficient optimization of hybrid microgrid parameters. Full article

This paper presents a novel design approach for mitigating the adverse effects of antenna mountings on the radiation pattern of GNSS antennas. By employing a resistive structure integrated into the ground plane, the proposed solution suppresses unwanted edge diffraction and near-field reflections caused by nearby mounting hardware. The design is developed using the concept of tapered resistive sheets and optimized using a customized cost function that accounts for pattern degradation across multiple realistic mounting configurations, ensuring robust performance under varying installation conditions. The resulting structure is fabricated using additive manufacturing (AM), enabling precise realization of complex resistive profiles with tailored surface impedance. Comprehensive validation through both electromagnetic simulations and experimental measurements demonstrates significant improvements in radiation pattern stability and reduced sensitivity to near-field objects, particularly in critical GNSS bands such as E5a/L5 and E1/L1. The results demonstrate that the proposed structure significantly enhances antenna reliability and calibration integrity in real-world deployments, offering a practical, hardware-based solution to a persistent challenge in high-precision GNSS systems. Full article

Early identification of thermal and electrical anomalies in grid-connected photovoltaic (PV) systems is becoming increasingly important to reduce energy losses, limit power quality (PQ) degradation, and avoid excessive operating stress on power electronic converters. Conventional electrical monitoring methods can provide overall performance information, but they are generally unable to detect and localize early-stage defects occurring at module or cell level. In this context, the present study proposes an integrated diagnostic framework that combines non-destructive infrared thermography (IRT) with advanced electrical signal processing techniques for PV condition monitoring. The proposed approach correlates thermographic information, capable of revealing defects such as hotspots, cell cracks, and bypass diode failures, with high-frequency electrical signal analysis based on frequency-domain and time–frequency methods, together with deep learning-driven thermographic segmentation. By associating thermal acquisitions with electrical PQ indicators, the framework enables the early detection of physical defects linked to inefficient Maximum Power Point Tracking (MPPT) operation and progressive degradation of PV system performance. The methodology was experimentally validated on a grid-connected photovoltaic installation under different fault conditions, including hotspots, bypass diode anomalies, and localized overheating effects, demonstrating the potential of the proposed approach for predictive maintenance and intelligent PV monitoring applications. The obtained results indicate that the proposed framework improves the reliability of photovoltaic fault detection by combining thermographic inspection with advanced electrical signal analysis and AI-based defect interpretation, thus supporting predictive maintenance strategies in smart PV infrastructures. The proposed approach demonstrates image segmentation capabilities, as evidenced by a precision (PA) of 96.88%, a mean IoU (mIoU) of 77.83% and a macro F1-score of 87.47%. The proposed framework maintained reduced computational requirements compatible with real-time monitoring applications. Full article

This study experimentally investigated the structural behavior of reinforced concrete beams with circular openings created by core drilling in the midspan and shear span regions under fixed-ended boundary conditions. A total of 21 full-scale beams with shear span-to-effective depth ratios (a/d) of 1.25, 1.75, and 2.25 were tested under a four-point bending setup. After concrete hardening, 100, 200, and 300 mm diameter openings were introduced by core drilling. The results showed that the effect of opening location on load-carrying capacity varied with the a/d ratio. In the a/d = 1.25 and 1.75 series, openings in the shear span caused more pronounced reductions, whereas in the a/d = 2.25 series, midspan openings became more influential. Increasing the opening diameter reduced both load-carrying capacity and energy dissipation capacity, and this reduction varied with opening location and a/d ratio. Openings in the shear span led to shear failure in the a/d = 1.25 and 1.75 series, whereas flexural effects became more pronounced in the a/d = 2.25 series. Nevertheless, 300 mm openings caused shear failure even in beams expected to exhibit more flexure-dominated behavior. Full article

Most studies in the field of application technology have focused on the interaction between adjuvants and agrochemicals, highlighting the need for further research to evaluate the behavior of adjuvants in association with other classes of crop protection products. In this context, the objective of this study was to evaluate the influence of adjuvants and air velocity on spray drift deposition in simulated applications conducted in a wind tunnel using a bioinsecticide based on Bacillus thuringiensis. The experiment was carried out in an open-circuit, blower-type wind tunnel installed at the Agricultural Machinery Laboratory of the State University of Goiás—Central Campus. The study was conducted in a completely randomized design arranged in a 5 × 4 × 4 factorial scheme, with three replications. Treatments consisted of five horizontal distances from the spraying point (0.45, 0.75, 1.05, 1.35, and 1.65 m), four wind speeds inside the tunnel (1 m s⁻¹, 2 m s⁻¹, 3 m s⁻¹, and 4 m s⁻¹), and four spray solution formulations (water; Dipel^®, Dipel^® + Veget’Oil^®, and Dipel^® + Break Thru^®). Artificial targets positioned transversely to the airflow were used to collect spray deposition and, after spraying, were divided into lower, middle, and upper thirds according to the height of the test section. Data were obtained by spectrophotometry and, after verification of the ANOVA assumptions, were subjected to analysis of variance (p < 0.05). When significant effects were observed, regression analyses were applied. Statistical analyses were conducted using the R and Sisvar software packages. Mean deposition values were converted into deposition percentage as a function of the total sprayed volume. The experimental data were also subjected to geostatistical analysis using GS+ software (Version 7^®). After confirming spatial dependence, contour maps were generated using kriging. Higher wind speeds led to higher deposition percentages. The use of adjuvants affected spray deposition in the upper and middle thirds, with responses depending on the spray solution composition. Spray deposition in the wind tunnel can be analyzed using geostatistics, as this variable showed a high degree of spatial variability across all treatments evaluated. Full article