Shading Effect Research Articles

The potential of shading to optimize the performance ratio of a solar power system

The aim of this research is to investigate the effect of shading to evaluate the performance ratio (PR) of a solar power system. In order to accomplish the objective of this study, the PVsyst software was utilized to assess the impact of shading, generate an energy input/output loss diagram and determine the PR during the entire year. This work only considers shading effect due to the position of a building and the location of the PV site. The suggested method also evaluates the financial analysis of the proposed PV system, specifically focusing on the payback period (PBP) and return on investment (ROI). Two types of perspective design of the PV position for the values of tilt and azimuth have been evaluated. The value of tilt and azimuth were 15o and 0° for design-1 and design-2 with different perspective, such as North building and South building for design-1 and design-2, respectively. The result of optimization illustrated that the PR yearly levels for Designs-1 and 2, were 0.821 and 0.759, respectively. In addition, the financial analysis investigated to examine PBP and ROI, were 8.1 years with 140.5 % return rate; 8.7 years with 110 % return rate, respectively. The proposed method has been simulated and analysed for applied on the rooftop of Teaching Industrial Learning Centre building, the University of Gadjah Mada (UGM) Yogyakarta-Indonesia.

Metabolomic and transcriptomic analyses reveal the mechanism of polysaccharide and secondary metabolite biosynthesis in Bletilla striata tubers in response to shading

Polysaccharides and various secondary metabolites are the major bioactive ingredients in Bletilla striata tubers and their biosynthesis and accumulation are influenced by light intensity. However, the mechanisms underlying shading effects remain largely unknown. In the present study, we used a combined analysis of the physiology, metabolome, and transcriptome to investigate the physiological activities and bioactive component accumulation of B. striata under different shading treatments (S0, S50, S70, and S90). The dry weight of shoots and tubers, net photosynthetic rate, and polysaccharide content were highest in S50 and lowest in S90. The content of precursors (sucrose, Glucose-6P, and Mannose-6P) for polysaccharide synthesis significantly increased in S50. However, the expression levels of genes involved in starch biosynthesis decreased in S50. Several structural genes involved in secondary metabolism, including cinnamic acid 4-hydroxylase (C4H), chalcone synthase (CHS), and 1-Deoxy-D-xylulose-5-phosphate synthase (DXS), showed decreased expression in S50. However, the shading effect on the biosynthesis of secondary metabolites (phenylpropanoids, flavonoids, and terpenoids) was inconsistent. Our study provides the molecular mechanisms underlying the effects of shading on the biosynthesis of polysaccharides and secondary metabolites in B. striata and offers a theoretical basis for the artificial cultivation and industrial production of bioactive ingredients.

Partial Shading Effect on Road-Integrated Photovoltaic Systems

Partial Shading Effect on Road-Integrated Photovoltaic Systems

Enhance Power Generation of PV Array under Partial Shading Conditions by a Lo Shu and Optimal SuDoKu Puzzle Fusion Topology

A novel Lo Shu and Optimal SuDoKu Puzzle Fusion Topology (LS-OSDKP) is presented to disperse shading effects and enhance photovoltaic (PV) array output power under partial shading conditions (PSCs). Incorporating the ancient Chinese Lo Shu magic square puzzle and the Optimal SDKP topologies, the proposed LS-OSDKP is capable of alleviating current mismatch losses, decreasing wiring loss, simplifying the P-V curves of the array, and significantly improving shading dispersion. Under six PSCs, the performance of the proposed topology was evaluated using a 9 × 9 PV array and compared to the total-cross-tied (TCT), Twisted Two-Step, SDKP, Optimal SDKP, and Lo Shu topologies. Simulation results confirmed that the proposed method could extract the highest averaged power of the PV array among the six topologies, with a 10.47% power improvement when compared to the TCT. Additionally, the LS-OSDKP is capable of effectively reducing the wiring length by 29.09% compared to the Lo Shu. Moreover, the proposed method has the highest potential for energy savings and revenue generation. Compared to the conventional TCT configuration, it could improve extracted energy by approximately 9.58% and shorten payback time by approximately 9.06%. Consequently, the advantages of the proposed LS-OSDKP topology include an increase in extracted power, a reduction in wiring loss, and a shorter energy payback period.

Simulation of source sink partitioning in wheat under varying nitrogen regimes using DSSAT-CERES-wheat model

Grain yields in wheat can be limited by the assimilate supply (source) or by the carbohydrate demand of the grains (sink). Recently, there have been questions regarding the capability of crop models to simulate the physiology of source-sink interactions in crops; however, crop models scarcely tested with source-sink partitioning. DSSAT_CERES_Wheat model was used with details of field experimental data having treatments of manipulated source (i.e., assimilate supply), sink (i.e., kernel number). The aim of the present study was to assess the impact of different levels of nitrogen and source-sink manipulation on wheat crop and to model source-sink partitioning in wheat under varying N-Regimes and climatic conditions. The experiment was conducted during wheat growing seasons of 2015–16 and 2016–17, at two locations (Islamabad and URF Koont Chakwal), under five different levels of nitrogen and three source sink treatments (Control (100 % RUE), 50 % shading pre-anthesis (50 % RUE), 50 % spike removal i.e. spike halving) using randomized complete block design. Recommended rates of fertilizer were applied with the exception of nitrogen which was 0, 50, 100, 150 and 200 kg ha−1, while each treatment was replicated thrice. CERES-Wheat model was calibrated using 2015–16 observed data while model was evaluated using two-year field collected data of two sites i.e. Islamabad and Chakwal. The model was able to simulate treatments impacts on phenology (R2, RMSE and d-index values of 0.89, 2.80 days and 0.97 respectively at Islamabad while at Chakwal R2 = 0.89, RMSE = 2.65 days and d-index = 0.94), leaf area index (R2 = 0.94, 0.94, RMSE = 0.51, 0.38 and d-index = 0.98 and 0.92 at Islamabad and Chakwal respectively), biomass (R2 = 0.98, 0.96, RMSE = 370, 450 kg ha−1 and d-index = 0.96 and 0.95 at Islamabad and Chakwal respectively), grain yield (R2 = 0.97,0.96, RMSE = 0.17, 0.2 t ha−1, and d-index = 0.95 and 0.93 at Islamabad and Chakwal respectively), harvest index, soil nitrogen, crop nitrogen and grain nitrogen with good accuracy. The observed range for biomass water use efficiency (BM_WUE) was 34.1–14.5 kg ha−1 mm−1 while grain WUE remained in the range of 10.3–3.7 kg ha−1 mm−1. The results depicted that model could reproduce observed effects of shading and halving the spikes. Crop response to modified radiation use efficiency (RUE) was variable among sites which could be critical for studying crop environment interactions, improving WUE, estimating genetically and atmospheric CO2-related increased RUE, analyzing impact of solar dimming and source manipulations under biotic stress.

Synergistic interplay of photobioreactor mixing and static mixer configuration on Rhodoseupdomonas palustris’s growth and biohydrogen production

Inducing light/dark (L/D) cycles through mixing or recirculating the media in a photobioreactor improves light utilization for biohydrogen production during photoferentation. However, the mutual shading effect is a key challenge for photofermentation using purple non-sulphur bacteria (PNSB). In this study, mixing was explored as a mitigating methodology through the investigation of three different static mixer configurations: concentric, spiral, and half-moon, across four laminar flowrates: 1.2 L/min, 0.71 L/min, 0.31 L/min and 0.15 L/min. At 0.15 L/min, the half-moon and spiral static mixers significantly improved specific and cumulative hydrogen production by 11.2-fold and 114 %, respectively. Also, recirculating the fluid via a peristaltic pump resulted in a significant shearing effect, impacting cell viability. Inducing L/D cycles via a static mixer was thus beneficial for hydrogen production over an increased flow rate. Additionally, biomass productivity increased by up to 70 %, reaching a cell dry weight of 7.0 g/L with the spiral static mixer configuration at 0.15 L/min flow rate. Interestingly, this study found that the static mixers only significantly increased specific hydrogen production and light conversion efficiency at the lowest flow rate of 0.15 L/min, beyond which they showed no significant improvement in biohydrogen production. This indicates that high L/D cycling frequencies are unnecessary to alleviate the mutual shading effect for R. palustris, which is advantageous for upscaling. These findings emphasise the potential of static mixers as an alternative to increase light conversion efficiency and industrial hydrogen production.

A Study on the Impact of Different PV Model Parameters and Various DC Faults on the Characteristics and Performance of the Photovoltaic Arrays

PV systems play a vital role in the global renewable energy sector, and they require accurate modeling and reliable performance to maximize the output power. This research presents a thorough analysis and discussions on the effects of different PV models’ parameters and certain specific faults on the performance and behavior of the photovoltaic systems under different temperature and irradiation conditions. It provides a detailed analysis of how several parameters affect the performance of the PV arrays, for instance, the series resistance, shunt resistance, photocurrent, reverse saturation current, and the diode ideality factor. These parameters were extracted mathematically and verified with the help of wide-ranging simulations and practical experiments. Additionally, the investigation of the effect of DC faults, including line-to-line, line-to-ground, partial shading, and complete shading faults on PV arrays, provides important fundamentals for fault detection and classification, thus improving the efficiency and protection of PV systems. It can, therefore, be stated that the outcomes of this research will assist in the enhancement of PV systems in terms of design, operation, and maintainability of photovoltaic plants, as well as contribute positively to the advancement of sustainable solar energy technology.

Near-Ground wind field characteristics of tracking photovoltaic systems based on field measurements

The study conducts field measurements at a tracking photovoltaic power station in Zhongwei City, Ningxia Hui Autonomous Region, investigating near-ground incoming wind characteristics, spatial coherence, and their impact on the flow field of the tracking photovoltaic system. Actual measurements indicate a low dispersion degree in the roughness index of this area, with an average roughness index of α = 0.1228, which is consistent with the characteristics of open land and desert areas. The incoming wind speed profile largely complies with European wind load specifications, with turbulence intensity measured at different heights exceeding other wind load specifications, primarily due to increased sand movement contributing to turbulence in desert areas. Additionally, this study proposes calculation formulas for measured turbulence intensity, integration scale, and gust factor, offering valuable insights into the incoming wind field characteristics in this region. Furthermore, the investigation into spatial coherence and decay parameters revealed the superior performance of the Krenk model in high frequency bands and over long distances. Lastly, the tracking photovoltaic array induces noticeable shading effects, altering flow field characteristics significantly, with a diminished impact on wind flow velocity as the tilt angle of the photovoltaic panel decreases. These studies serve as a valuable reference for gaining a deeper understanding of wind field characteristics, wind load calculation, and the optimal design of tracking photovoltaic systems.

Daylighting and energy performance of window with transparent insulation slats combined with building shading in the hot-summer and cold-winter zone

The shading from surrounding buildings significantly affects the energy and daylighting performance of transparent insulation materials (TIM) systems. In previous studies, the performance of TIM systems was primarily discussed in ideal situations without considering the influence of surrounding buildings. However, this is not realistic in actual urban scenarios. This study presents a case study conducted in Changsha to evaluate and compare the energy and daylighting performance of the window with transparent insulation slats (WTIS) and normal double glazing (NDG). The study considers the varying degrees of building shading effects. The results show that windows facing west exhibit the best energy efficiency, while windows facing south have the worst. WTIS achieves a higher Useful Daylight Illuminance (UDI) when building shading effects are not significant, whereas NDG achieves a higher UDI when building shading effects are significant. Despite increasing lighting energy consumption by 69.8 % to 84.3 %, WTIS consistently outperforms NDG in terms of total energy savings. Furthermore, strategically utilizing or deactivating WTIS according to recommended periods during winter can enhance the total solar gain for the building by approximately 22.3 %. This study provides valuable recommendations for the application of WTIS systems and the design of buildings in the hot-summer and cold-winter zone.

Characterisation of view relative to solar-control systems

Solar shading can be an effective way of avoiding overheating by reducing solar gains in buildings. However, solar shading systems can block or obscure the view-out with the consequence that occupants may refrain from using the shading system. As such, there is a need to quantify the effects of shading on occupants’ perception of the view.In this study, we developed a method to identify the photometric parameters and compositions that are effective in characterising the view-out in relation to different solar-control systems. We hypothesized that the photometric composition, e.g., contrast, in the visual environment as a result of using solar-control systems impacts the subjective assessment of the view. We conducted objective photometric measurements using calibrated luminance cameras and subjective responses from 64 participants in a semi-controlled work environment to test the hypotheses. The participants were randomly allocated to a combination of five view-outs and six solar shading systems in a work environment where they answered questions related to the indoor environment and view quality. The relation between view and solar-control systems and their impact on the subjective view assessment was tested using linear mixed-effects models. The models were developed using forward and backward selection based on AIC and likelihood ratio tests (LRT) to test the effects of adding or removing variables. The achromatic contrast calculated based on the measured luminance data both locally and globally was significantly associated with view assessment and satisfaction when using different shading types.

Algorithmic advancements in agrivoltaics: Modeling shading effects of semi-transparent photovoltaics

Radiation is a crucial factor in the field of agrivoltaics in greenhouses. Depending on the type of photovoltaics integrated into greenhouses, the effect on radiation varies through the phenomenon of shading. Shading in greenhouses can be either beneficial or detrimental, making its analysis imperative. In this study, the improvements and modifications made in an algorithm capable of calculating the shading from photovoltaic units installed in greenhouses are presented. A key modification to the algorithm is the calculation of shading from semi-transparent photovoltaic modules, in contrast to its original form, in which photovoltaic modules were considered opaque. The algorithm was validated using radiation data from pyranometers within a greenhouse. The coefficients used were Pearson's r correlation coefficient and the Coefficient of Variation. The correlation coefficients for times without shading effect approached the values for the case without photovoltaics installed on the roof. Simultaneously, based on the coefficients of variation, the uniformity of radiation within the shade was validated, thereby confirming its existence. Finally, the effect of semi-transparent photovoltaic units on Global Horizontal Irradiance and Photosynthetically Active Radiation was studied, with the reduction for the former approaching 52 % and about 60 % for the latter. These changes in radiation can be either beneficial or not, depending on the type of crop and the needs of the greenhouse, such as cooling.

Optimisation of Convolution-Based Image Lightness Processing.

In the convolutional retinex approach to image lightness processing, an image is filtered by a centre/surround operator that is designed to mitigate the effects of shading (illumination gradients), which in turn compresses the dynamic range. Typically, the parameters that define the shape and extent of the filter are tuned to provide visually pleasing results, and a mapping function such as a logarithm is included for further image enhancement. In contrast, a statistical approach to convolutional retinex has recently been introduced, which is based upon known or estimated autocorrelation statistics of the image albedo and shading components. By introducing models for the autocorrelation matrices and solving a linear regression, the optimal filter is obtained in closed form. Unlike existing methods, the aim is simply to objectively mitigate shading, and so image enhancement components such as a logarithmic mapping function are not included. Here, the full mathematical details of the method are provided, along with implementation details. Significantly, it is shown that the shapes of the autocorrelation matrices directly impact the shape of the optimal filter. To investigate the performance of the method, we address the problem of shading removal from text documents. Further experiments on a challenging image dataset validate the method.

Integration of Crops, Livestock, and Solar Panels: A Review of Agrivoltaic Systems

This review article focuses on agrivoltaic production systems (AV). The transition towards renewable energy sources, driven by the need to respond to climate change, competition for land use, and the scarcity of fossil fuels, has led to the consideration of new ways to optimise land use while producing clean energy. AV systems not only generate energy but also allow agricultural and livestock yields to be maintained or even increased under PV structures, offering a sustainable production strategy that may be more acceptable to local communities than traditional PV installations. This review assesses the technical feasibility of AV systems, the environmental, economic and social benefits, as well as the challenges faced and the legal framework regulating their implementation. It is highlighted that despite the advantages in land use efficiency and dual food and energy production, there are important challenges related to the initial investment required, the need for technological adaptation, social and regulatory obstacles, or the effects of shading on production. This paper underlines the importance of further research and development of these systems to overcome technical and economic constraints and maximise their potential benefits. It is concluded that although they present significant challenges, AV management offers promising opportunities to improve land efficiency and contribute to several sustainable development goals.

Alleviating Damage Extent and Enhancing Yield through Mild Shading in Microsperma and Macrosperma Genotypes of Lentil (Lens culinaris Medikus) at Terminal Heat and Combined Stress Condition

The threat of global climate change mainly in term of heat and combined stress is one of the utmost serious concerns for farmers, and have a negative impact on agriculture production and challenging food security worldwide. A field experiment was conducted during Rabi season at Pulse breeding Block, G.B Pant University of Agriculture and Technology, Pantnagar. The objective of this investigation was to effect of shading to mitigate the heat and combined stress as well as the comparison of heat and combined stress in microsperma and macrosperma genotypes. It was laid out in factorial random block design with three replications. The morpho-physiological and yield attributes of both genotypes under varied growth condition at different time interval were evaluated. The microsperma (PL-8) and macrosperma (PL-11) after shading changed their plant height (6% and 5%), NDVI value (5% and 4%), Membrane stability index (9% and 6%), days to maturity (7% and 6%) and total no of grain (15% and 37%) under heat stress while in combined stress it was changed by 8% and 10% in plant height, 9% and 3% in NDVI value,14% in MSI,7% and 3% in days to maturity and13% and 23% in yield. The above finding proves the effect of shading mitigate the damage extent and also increase production of both lentil genotypes (PL-8) and (PL-11).

Sensitivity of Local Climate Zones and Urban Functional Zones to Multi-Scenario Surface Urban Heat Islands

Local climate zones (LCZs) and urban functional zones (UFZs) can intricately depict the multidimensional spatial elements of cities, offering a comprehensive perspective for understanding the surface urban heat island (SUHI) effect. In this study, we retrieved two types of land surface temperature (LST) data and constructed 12 SUHI scenarios over the Guangdong–Hong Kong–Macao Greater Bay Area Central region using six SUHI identification methods. It compared the SUHI sensitivity differences among different types of LCZ and UFZ to analyze the global and local sensitivity differences of influencing factors in the 12 SUHI scenarios by utilizing the spatial gradient boosting trees, geographically weighted regression, and the coefficient of variation model. Results showed the following: (1) The sensitivity of different LCZ and UFZ types to multi-scenario SUHI was significantly affected by differences in SUHI identification methods and non-urban references. (2) In the morning, the shading effect of building clusters reduced the surface urban heat island intensity (SUHII) of some built environment types (such as LCZ 1 (compact high-rise zone) to LCZ 5 (open midrise zone)). The SUHIIs of LCZ E (bare rock or paved zone) and LCZ 10 (industry zone) were 4.22 °C and 3.87 °C, respectively, and both are classified as highly sensitive to SUHI. (3) The sensitivity of SUHI influencing factors exhibited regional variability, with importance differences in the sensitivity of importance for factors such as the impervious surface ratio, elevation, average building height, vegetation coverage, and average building volume between LCZs and UFZs. Amongst the 12 SUHI scenarios, an average of 87.43% and 89.97% of areas in LCZs and UFZs, respectively, were found to have low spatial sensitivity types. Overall, this study helps urban planners and managers gain a more comprehensive understanding of the complexity of the SUHI effect in high-density cities, providing a scientific basis for future urban climate adaptability planning.

Understanding fiber quality in field-grown shaded cotton: Nitrogen fertilization implications

ContextHigh nitrogen rates are important to field-grown cotton (Gossypium hirsutum L.) for recovering from stresses such as light restriction and alleviating its negative impact on yield. However, there is little information on its influence on fiber quality after shading. ObjectiveThe objective of this study was to examine fiber quality responses to nitrogen fertilization of shaded cotton. MethodsCotton plants were exposed to a 42 % reduction in global radiation for 16–25 days during early flowering, and fertilizer with different N rates in the Center-West (Primavera do Leste - PL and Chapadão do Sul - CS) and Southeast (Itapeva - IT) Brazil. Four N rates were used in PL and IT, and 3 N rates and an early (FM 906GLT) and a late-cycle (FM 983GLT) cotton cultivar were used in CS. Fiber quality from bolls taken from entire plots (nonportioned plants) and from the lower, middle, and upper thirds of the canopy (portioned plants) was assessed. ResultsThe lack of interaction in most analyses indicated shading and nitrogen effects on fiber quality as independent. Shading resulted in occasional effects on micronaire, strength, length, length uniformity, and short fiber index. Micronaire of nonportioned plants decreased in response to N inputs, wherein values at the maximum N rate were lower than those at the minimum one by 5.21 % and 7.91 % in PL and IT, respectively. Increasing N rates also decreased micronaire in all canopy portions in IT and the lower third in CS but had nonconclusive effects on other fiber properties. Fiber length and strength were generally greater in the late-maturing cultivar, which had higher micronaire readings in the lower third of the canopy and lower readings in the upper canopy compared with the early cultivar. ConclusionsIn conclusion, shading during early flowering has limited and inconsistent effects on cotton fiber quality. Conversely, N fertilization leads to more predictable results, so higher N rates increase the risk of heightened immature fiber percentage. ImplicationsThe findings of this work provide new insights into how nitrogen fertilization management affects cotton fiber quality. Future research should consider other management techniques, such as the timing of the crop termination, to avoid the occurrence of low micronaire.

Evaluating the effects of envelope features on the pollutant distribution and ventilation performance by CFD simulations and scaled outdoor experiments

Previous studies on the effects of envelope features on ventilation performance have neglected the buoyancy effect or simplified it as a uniform surface heating effect. However, envelope features can create a shading effect that changes the temperature distribution and enhances the buoyancy effect, thus resulting in inaccurate findings. We conducted computational fluid dynamics (CFD) simulations based on scaled outdoor experiments to investigate the effects of different envelope features (balconies, overhangs, and wing walls) on pollutant dispersion and ventilation performance. The buoyancy effect created a new local vortex and changed the wind flow pattern at the base of the flat-facade and wing wall street canyons. The age of the air at the base of the flat-facade, balcony, overhang, and wing wall street canyons increased by 30.23 %, 20.45 %, 21.74 %, and 30.95 %, respectively. Moreover, when investigating the effects of envelope features on ventilation performance while ignoring the buoyancy effect, there was a high error rate in the ventilation performance, and the rates were as follows: wing wall (24.03 %) > flat-facade (23.20 %) > overhang (18.56 %) > balcony (14.05 %). This study provides a suitable methodology for investigating the effects of different envelope features on pollutant dispersion and ventilation performance in two-dimensional street canyons.

Antibiotic Removal by Three Promising Microalgae Strains: Biotic, Abiotic Routes, and Response Mechanisms

Microalgae represent an alternative to conventional wastewater treatment, potentially improving antibiotic removal and offering a solution to combat the spread of antimicrobial resistance. Through batch assays, this study investigates the routes for antibiotic removal using three strains (Chlamydomonas acidophila, Auxhenochlorella protothecoides and Tetradesmus obliquus). Using mixtures of ciprofloxacin, clarithromycin, erythromycin, metronidazole, ofloxacin, sulfamethoxazole, and trimethoprim at concentrations simulating wastewater composition, it also assesses antibiotic effects on microalgae physiology. The three strains primarily removed antibiotics through rapid biosorption, achieving up to 91.5% removal for specific ones like ciprofloxacin. T. obliquus and C. acidophila showed efficacy, with total removals of 37.2% and 49.3%, respectively. Over time, A. protothecoides demonstrated the highest active removal efficiency, eliminating 22.1% of total antibiotics, with a notable 67.6% removal for sulfamethoxazole. Abiotic degradation through hydrolysis and photolysis contributed to ciprofloxacin, ofloxacin, clarithromycin, and erythromycin removal (34.7% to 96.7%), showing pH-dependent photolysis. However, algae induced a shading effect, reducing the photolytic and hydrolytic degradation of specific antibiotics. T. obliquus and C. acidophila were inhibited by antibiotics, whereas A. protothecoides showed a 30.6% growth rate increase. The stimulatory effect was also observed for the nutrient removal, with A. protothecoides showing a 46.6% increase in ammonium removal and a 44.8% increase in phosphate removal with antibiotics. Additionally, antioxidant activities remained stable, except for a notable increase in peroxidase activity for A. protothecoides and T. obliquus. The study confirms efficient antibiotic removal and stimulatory responses in the three algal strains, indicating their potential for wastewater treatment and combating antimicrobial resistance.

Applied Machine Learning to Study the Movement of Air Masses in the Wind Farm Area

Modeling the atmospheric boundary layer (ABL) in the area of a wind farm using computational fluid dynamics (CFD) methods allows us to study the characteristics of air movement, the shading effect, the influence of relief, etc., and can be actively used in studies of local territories where powerful wind farms are planned to be located. The operating modes of a wind farm largely depend on meteorological phenomena, the intensity and duration of which cause suboptimal operating modes of wind farms, which require the use of modern tools for forecasting and classifying precipitation. The methods and approaches used to predict meteorological phenomena are well known. However, for designed and operated wind farms, the influence of meteorological phenomena on the operating modes, such as freezing rain and hail, remains an urgent problem. This study presents a multi-layered neural network for the classification of precipitation zones, designed to identify adverse meteorological phenomena for wind farms according to weather stations. The neural network receives ten inputs and has direct signal propagation between six hidden layers. During the training of the neural network, an overall accuracy of 81.78%, macro-average memorization of 81.07%, and macro-average memorization of 75.05% were achieved. The neural network is part of an analytical module for making decisions on the application of control actions (control of the boundary layer of the atmosphere by injection of silver iodide, ionization, etc.) and the formation of the initial conditions for CFD modeling. Using the example of the Ulyanovsk wind farm, a study on the movement of air masses in the area of the wind farm was conducted using the initial conditions of the neural network. Digital models of wind turbines and terrain were created in the Simcenter STAR-CCM+ software package, version 2022.1; an approach based on a LES model using an actuating drive disk model (ADM) was implemented for modeling, allowing calculation with an error not exceeding 5%. According to the results of the modeling of the current layout of the wind turbines of the Ulyanovsk wind farm, a significant overlap of the turbulent wake of the wind turbines and an increase in the speed deficit in the area of the wind farm were noted, which significantly reduced its efficiency. A shortage of speed in the near and far tracks was determined for special cases of group placement of wind turbines.

Assessing the impact of glazing and window shade systems on view clarity

Windows provide access to daylight and outdoor views, influencing building design. Various glazing and window shade materials are used to mitigate glare, overheating and privacy issues, and they affect view clarity. Among them, we evaluated the effect of window films, electrochromic (EC) glass, and fabric shades on view clarity. We conducted an experiment with 50 participants using visual tests adapted from clinical vision tests (visual acuity, contrast sensitivity, color sensitivity) and images displayed on a computer monitor in a controlled laboratory. Window films and EC glass tints outperformed fabric shades in visual acuity, contrast sensitivity and view satisfaction with the exception of the darkest EC tint state and dark grey VLT 3% shade for color sensitivity and view satisfaction. The EC tints pose internal reflection issues and fabric shades are preferred for visual privacy. Window films and EC glass hinder participants’ blue–green color discrimination while fabric shades also decrease red–yellow color discrimination. Visual acuity predicts view satisfaction and contrast sensitivity is the strongest predictor for visual privacy. Generally, higher visible light transmittance and lower solar reflectance (darker color) enhance human visual performance. The proposed workflow provides an experimental procedure, identifies the primary variables and establishes a predictive framework for assessing view clarity of fenestration.