Shading Distribution Research Articles

An adaptive two-step staircase static reconfiguration method for improving the power generation of PV array

Partial shading of solar photovoltaic (PV) panels can significantly affect the performance of solar PV arrays. Various reconfiguration techniques have been explored in recent years. Still, their applicability to actual PV power generation is controversial due to the number of electrical switches, physical locations, interconnections and complexity. This study proposes an adaptive two-step staircase (A2SS) static reconfiguration method. The technique is experimentally validated in several conditions and compared with the conventional TCT connection, single-step staircase (1SS) static reconfiguration method, Arrow soduku, modified odd–even–prime (MOEP) and two-step staircase(2SS) static reconfiguration method. For the eight shading cases of LN, LW, LD, Ran, Cen, Cor, CD, and Plus at SET#1, after reconfiguring the PV array using A2SS, the power has a significant improvement of 17.6%, 17.0%, 13.4%, 13.4%, 20.6%, 20.2%, 3.1%, and 0.82% than TCT. In the four shading cases of Lr. C, Lr. O, Lr. T, and Lr. U at SET#2, the power showed a significant improvement of 11.8%, 9.2%, 10.7%, and 15.8% compared to TCT. It also has the best performance in various reconfiguration techniques, which are mentioned. In addition, the A2SS reconfiguration method can be better applied to various sizes of PV arrays. By optimizing the shading distribution and adjusting the row irradiance deviation, the power stability of PV power generation is improved while maximizing energy efficiency.

Vector-Based Advanced Computation for Photovoltaic Devices and Arrays: Numerical Reproduction of Unusual Behaviors of Curved Photovoltaic Devices

Most equations and models for photovoltaics are based on the assumption that photovoltaic (PV) devices are flat. Therefore, the actual performance of nonplanar PV devices should be investigated and developed. In this study, two algorithms were developed and defined using vector computations to describe a curved surface based on differential geometry and the interaction with non-uniform solar irradiance (i.e., non-uniform shading distribution in the sky). To validate the computational model, the power output from a commercial curved solar panel for the Toyota Prius 40 series was monitored at four orientation angles and in various climates. Then, these were compared with the calculation results obtained using the developed algorithm. The conventional calculation used for flat PV devices showed an overestimated performance due to ignorance of inherent errors due to curved surfaces. However, the new algorithms matched the measured trends, particularly on clear-sky days. The validated computation method for curved PV devices is advantageous for vehicle-integrated photovoltaic devices and PVs including building-integrated photovoltaics (BIPVs), drones, and agriphotovoltaics.

Impact of Shade on Pedestrian Activities—A Mixed-Methods Research in the City of Colombo, Sri Lanka

This research delves into the influence of shade on pedestrian activities, employing a comprehensive mixed-methods approach along the primary thoroughfares of Colombo, Sri Lanka. Google Street View photographs served as the primary data source for this spatial analysis. Hotspot analysis and spatial autocorrelation were utilized to depict the spatial distribution of shade and establish its correlation with pedestrian activities. The spatial analysis results revealed a consistent pattern of shade concentration aligning with areas of heightened pedestrian activities. The findings hold significant implications for urban planning and design practitioners, as well as policymakers.

The structure of the thermal landscape determined behavioural and physiological responses to simulated predation risk

Abstract Although predators can deter an animal from regulating its body temperature by basking or shuttling, this response to predation should depend on the spatial distribution of thermal resources. By simulating predation risk, we showed that movement, thermoregulation and corticosterone of male lizards (Sceloporus jarrovi) depended on the spatial distribution of shade. Simulated risk caused lizards to move less, thermoregulate worse and circulate more corticosterone than they did without risk. However, a patchier distribution of shade enabled lizards to move more, thermoregulate better and circulate less corticosterone when exposed to a simulated predator. In the absence of simulated risk, lizards in patchier environments moved less, thermoregulated better and circulated less corticosterone, indicating the distribution of shade also affected the energetic cost of thermoregulation. This study provides the first test of a spatial theory of thermoregulation under the perceived risk of predation. Read the free Plain Language Summary for this article on the Journal blog.

Analytical evaluation of thermal comfort in the pedestrian environment using pedestrian shade space distribution

Shade distribution in the pedestrian environment directly affects pedestrian thermal comfort, so it is necessary to evaluate the influence of shade on thermal comfort and guide shade planning. This study proposed a concept of pedestrian shade space from a 3D perspective for accurately analyzing the thermal impact of shade on pedestrians. Pedestrian shade space is a space that can completely cover a pedestrian in the shade when the pedestrian is on a sidewalk. Pedestrian space is considered to be composed of two types of space: pedestrian sunlit space and pedestrian shade space. A quantification method of pedestrian shade space distribution on sidewalks was also discussed in this paper. By estimating a thermal index (Physiological equivalent temperature, PET) in the pedestrian space, pedestrian thermal comfort can be analyzed based on pedestrian shade space distribution. The evaluation process and application of the proposed method were demonstrated through case studies in actual urban districts. The analysis results show that the proposed method can be used to support the planners in the thermal evaluation of the pedestrian environment and design proposal optimization.

Shading and PAR under different density agrivoltaic systems, their simulation and effect on wheat productivity

The introduction of renewable energy to mitigate climate change and the need for sufficient land to increase food production are mutually exclusive. Agrivoltaic systems (AVS) integrate the production of agricultural crops and electric power on the same piece of land but the main issue is the reduced availability of light to crops below the AVS, which restricts optimum crop growth and yield. This study examines the radiation and shade distribution over the crop surface among three densities of photovoltaic (PV) panels {Partial density (PD), Half density (HD) and Full density (FD)} under the AVS. Wheat variety GW 496 was chosen to grow under the AVS with line sowing and drip irrigation. Among three densities of photovoltaic (PV) panels, the proportion of shaded area over the crop surface was found highest in full density plot and lowest in partial density plot. The shaded area under AVS varied from 24.1% to 75.4% of the total area. The shaded area under different density plots, adversely affects the availability of photosynthetically active radiation (PAR) over the crop surface. The reduction of PAR under the AVS was more affected by panel density. Maximum reduction in PAR under AVS was observed in FD plot and minimum in the PD plot. A sharp increase in the PAR level was observed from shading to open sun conditions. The lowest value of PAR level (56 μmol m−2 s1) was recorded in just below the panel’s array. The consistent overestimation of PAR was observed during the crop growing period in all the PVPs density plots. The result revealed that the grid points under shade conditions showed a better association between observed and simulated incident PAR than unshaded grid points. Furthermore, the simulation results revealed that the model modeled PAR better in PD plot. The study also found that wheat grown under no shade yielded 4.51 t/ha over reduced light either in PD (3.06 t/ha), HD (2.77 t/ha), and FD plots (2.62 t/ha). Shading treatments showed that the crop yield decreased with an increase in shading intensity.

Augmenting Power Efficiency by Virtue of a Novel Physical Reconfiguration of Solar Photovoltaic Array in Tandem with Experimental Validation

The growing interest in solar energy has led to large photovoltaic (PV) energy parks in today's world. Though the commonly used total‐cross‐tied (TCT) interconnection scheme reduces mismatch losses (MLs), the occurrence of partial shading on massive PV arrays (PVAs) reduces the output power. It invokes numerous local maximum power points (LMPPs) on the power–voltage (P–V) profiles. To counteract the undesired LMPPs, reconfiguration of PVAs is done either through electrical or physical reconfiguration methods. In this respect, physical relocation scheme is more economical for better distribution of partial shade. A novel greater‐than‐SuDoKu (GTS) topology is presented in this paper for achieving physical rearrangement of PV modules amalgamated with TCT interconnection scheme. For analysis, five shading cases are considered and obtained results are compared with conventional TCT and 10 newly established methods. In general, the proposed GTS strategy has shown its eminence in receiving a smoother P–V characteristic, enhanced efficiency, better fill factor, and reduced MLs, which ranges up to 1343 W. Moving forward, herein, the efficacy of the proposed reconfiguration scheme is validated, under the influence of partial shading conditions, through an experimental lab prototype for a 3 × 3 PVA.

Optimized topology for a photovoltaic array using switches control

The photovoltaic (PV) industry is experiencing rapid growth driven primarily by rising global energy demand and the inevitable transition to sustainable energy sources. Nevertheless, various factors impede the performance of PV panels, prompting researchers to consider novel PV systems. Mismatch loss is a significant concern induced by dust accumulation, nearby objects, or bird droppings, which restrict the power output of the PV array, particularly when interconnected in the standard mode. In this context, the present investigation aimed to identify the optimal topology for different partial-shading models. The proposed approach automatically manipulates switches to ensure an appropriate interconnection scheme by utilizing a novel process based on the perturb and observe (P&O) concept. Furthermore, this study applies advanced global maximum power point tracking (GMPPT) techniques based on PV curve scanning and the enhanced P&O method to effectively manage the PV system’s maximum power output during dynamic partial shading conditions (PSC). The power–voltage (P–V) curves and power production associated with each shading model are analyzed using MATLAB Simulink to assess the validity and effectiveness of the approach. Ultimately, the methodology achieves a special power rate exceeding 20 W for a small-scale PV plant with a capacity of 240 W under certain shading patterns, notably random shading distribution.

Solar Electric Vehicles as Energy Sources in Disaster Zones: Physical and Social Factors

Electric vehicles (EVs) have the advantage of being resilient to natural disasters. However, users hesitate to donate electricity when they lose the chance to recharge at the utility. Solar electric vehicles (SEVs) save energy through vehicle-integrated photovoltaics (VIPV) and make it possible to voluntarily donate excess energy, thus maintaining facility resilience. Given that the supply of solar energy to VIPV systems is not continuous and is difficult to forecast, the contribution of VIPV to the resilience of the larger energy system has been called into question. This is the first study in which the potential of VIPV to maintain utility resilience is investigated in the context of physical factors, such as irradiance, and social factors. The actual energy yield of a VIPV car was determined using an advanced 3D solar irradiation model under a nonuniform shading distribution, with validation from actual measures of solar irradiance on five orthogonal sides of the car body. The Monte Carlo method was used to model the complex factors in VIPV energy storage and energy donations under different scenarios. Depending on the climate, population density, and shading environment, the voluntary contribution of stored electricity in SEV is sufficient to provide disaster relief support.

Does age determine the lightness and darkness of tooth shades? A retrospective study.

The study aimed to analyze whether age determines the lightness and darkness of tooth shades. The demand for esthetics has soared to a next level progressively in many developing countries including India; the importance provided to match the tooth shade creates a great difference in the satisfactory outcome of the patient in the field of dentistry. Therefore, this particular study analyzed the differences in tooth shade values based on age factor among the Indian population. 238 individual's case sheets with the age between 18 and 65 years. 18-30 years of age were considered as group 1 (young adults), 31-45 years in group 2 (middle age), and above 45 years in group 3 (older age). The clinical intraoral pictures of the patients which were taken prior to the treatment were obtained and the shade of any one of the upper permanent central incisors was assessed using the Vitapan 3D-Master shade guide, especially the middle portion of the facial surface of the incisors. The collected data were imported to Statistical Package for the Social Sciences, version 17 (IBM Corporation). Chi-square test was used to assess the significance. From the data, 17.2% showed A1 shade, 35.2% A2 shade, 7.5% A3 shade, 5% A4 shade, 7.1% B1 shade, 15.9% B2 shade, 7.1% B3 shade, 3.3% B4 shade, and 1.1% C1 shade. The individuals under the category of above 45 years showed darker tooth shade compared to young adults and middle age population (Chi-square test, P < 0.001). Significant association was established with darker tooth shades by increasing age and vice versa. The older age population showed a higher correlation for dark shade between teeth. The aging process significantly affects the teeth color. Hence, as a dentist, it is important to know about the distribution of tooth shade and its association with age to get an outcome with adequate patient satisfaction.

A novel prime numbers-based PV array reconfiguration solution to produce maximum energy under partial shade conditions

Non-uniform solar irradiance on the photovoltaic arrays decreases the output power due to the partial shading conditions. In this paper, the distribution of shade in the photovoltaic array rows is done by reconfiguring the shaded modules related to the photovoltaic array. The method proposed in this paper is a static approach based on prime numbers. Due to the pattern of prime numbers, it reconfigures the shaded modules in each row. The effectiveness of the proposed procedure is done by testing five different shading patterns in 9×9 and one 23×23 Total-Cross-Tied PV arrays. The ability and superiority of the proposed method are tested by comparing the results of the suggested method of prime numbers with the results of the Total-Cross-Tied, Sudoku, optimal Sudoku, improved Sudoku, and Dominance square methods. Comparison and evaluation of the results are done by different statistical performance indicators. The evaluations showed that the prime numbers procedure with the values of 9.15%, 7.72%, 8.21%, 8.83%, 8.95%, and 8.77% for cases 1 to 6, respectively, had the highest power factor compared to other methods employed. In addition, the suggested method has the lowest mismatch power losses compared to other procedures by achieving the values of 3.84%, 4.87%, 4.53%, 4.10%, 3.97%, and 4.19% in cases 1–6, respectively. The results of the comparisons strongly emphasize the high ability of the proposed method compared to other methods studied. It should be noted that scalability, high-performance speed, and low cost are important advantages of the prime number method so that this method can be implemented on real-world PV arrays.

A novel on-time partial shading detection technique for electrical reconfiguration in solar PV system

Mismatch losses due to partial shading condition (PSC) is not permitted to extract maximum power from the solar PV array. Numerous techniques were proposed to reduce the partial shading effect. But the major problem is in finding out the occurrence and its distribution of the partial shading in the solar PV array. Conventional methods disconnect the load temporally from the PV array and measure the short circuit current (Isc) and use the information to detect the partial shading. Frequent disconnection of the solar PV array from the load makes the conventional method unpractical in a large solar power plant and even a stand-alone PV system. A novel on-time partial detection technique is proposed in this paper and useing difference in row voltage (Vd) instead of the short circuit current (Isc) to estimate the partial shading. Greater the Vd infers the severity of occurrence of the partial shading in the solar PV array. By using a static reconfiguration and then a modified couple matching (MCM) technique the voltage difference (Vd) gets reduced. This will ensure the mitigation of the PSC. As in this proposed technique, the load never be disconnected from the solar PV array, to detect the partial shading, it can be used practically even for a stand-alone PV system. Eight extensive partial shading patterns are simulated using MATLAB Simulink to validate the proposed work and the size of 3 × 4 120 W polycrystalline PV panel array is used for the experimental validation.

Development of a Surface Roughness Evaluation Method from Light and Shade Composition using Deep Learning

Many companies agree on the need to introduce smart factories that promote low-cost, high-efficiency operation by applying IoT technologies to manufacturing plants. To assist in efficient manufacturing, this paper proposes a system for evaluating surface roughness through deep learning AI methods from the distribution of shade on the surface of an object. This is thought to greatly relieve the meticulous and tedious process of manual quality control for precision-machined surfaces and assist in the establishment of smart manufacturing industries. To demonstrate the usefulness of the developed technique, 305 samples of paper were categorized into three classes based on Ra threshold values, and images of paper were taken using a microscope camera. Luminance values, standard deviations, mean values, and image histograms were used to train custom-designed CNN+ LSTM composite neural networks. Completely new samples of non-training data were used for validation, which showed an accuracy of 85.185%. The proposed method can be economical, efficient, and fast compared to conventional surface roughness evaluation procedures. It can be easily integrated into an assembly line and automate quality assurance processes. This method could also prove useful in reducing labor costs and streamlining quality assurance processes due to its flexible adaptability.

Development and validation of a spatially-explicit agent-based model for space utilization by African savanna elephants (Loxodonta africana) based on determinants of movement

African elephants (Loxodonta africana) are well-studied and inhabit diverse landscapes that are being transformed by both humans and natural forces. Most tools currently in use are limited in their ability to predict how elephants will respond to novel changes in the environment. Individual-, or agent-based modeling (ABM), may extend current methods in addressing and predicting spatial responses to environmental conditions over time. We developed a spatially explicit agent-based model to simulate elephant space use and validated the model with movement data from elephants in Kruger National Park (KNP) and Chobe National Park (CNP). We simulated movement at an hourly scale, as this scale can reflect switches in elephant behavior due to changes in internal states and short-term responses to the local availability and distribution of critical resources, including forage, water, and shade. Known internal drivers of elephant movement, including perceived temperature and the time since an individual last visited a water source, were linked to the external environment through behavior-based movement rules. Simulations were run on model landscapes representing the wet season and the hot, dry season for both parks. The model outputs, including home range size, daily displacement distance, net displacement distance, and maximum distance traveled from a permanent water source, were evaluated through qualitative and quantitative comparisons to actual elephant movement data from both KNP and CNP. The ABM was successful in reproducing the differences in daily displacements between seasons in each park, and in distances traveled from a permanent water source between parks and seasons. Other movement characteristics, including differences in home range sizes and net daily displacements, were partially reproduced. Out of the all the statistical comparisons made between the empirical and simulated movement patterns, the majority were classified as discrepancies of medium or small effect size. We have shown that a resource-driven model with relatively simple decision rules generates trajectories with movement characteristics that are mostly comparable to those calculated from empirical data. Simulating hourly movement (as our model does) may be useful in predicting how finer-scale patterns of space use, such as those created by foraging movements, are influenced by finer spatio-temporal changes in the environment.

Power Enhancement under Partial Shading Condition Using a Two-Step Optimal PV Array Reconfiguration

Under partial shading conditions, photovoltaic (PV) arrays are subjected to different irradiance levels caused by nonuniform shading. As a result, a mismatch between the modules, a reduction in the power generated, and the hotspot phenomenon will be observed. One method to reduce mismatch losses is to reconfigure the total-cross-tied (TCT) array in dynamic and static forms, where improved performance can be achieved through more efficient shading distribution thanks to increased dimensions. However, the increase in dimensions leads to the complexity of wiring and installation in static reconfiguration and the large number of switches and sensors required in dynamic reconfiguration. To rectify these problems, a two-step method is proposed in this paper. In the first step, the modules inside the PV array are divided into subarrays with wiring in static reconfiguration, rather than being wired as large-scale PV arrays. In the second step, an algorithm is developed for dynamic reconfiguration. The introduced algorithm searches for all possible connections and finally identifies the most optimal solution. As an advantage, this algorithm employs only the short-circuit current values of the subarray rows, which reduces the number of switches and sensors required in comparison to dynamic reconfiguration. Under 8 different partial shading patterns, simulations are conducted and results confirm that the proposed method outperforms the TCT array and statically modified TCT array in terms of power and mismatch losses. Among these, the highest power improvement is obtained with regard to the TCT array and statically modified TCT array under the fourth and eighth shading patterns, respectively.

Does Sentinel-1A Backscatter Capture the Spatial Variability in Canopy Gaps of Tropical Agroforests? A Proof-of-Concept in Cocoa Landscapes in Cameroon

A reliable estimation and monitoring of tree canopy cover or shade distribution is essential for a sustainable cocoa production via agroforestry systems. Remote sensing (RS) data offer great potential in retrieving and monitoring vegetation status at landscape scales. However, parallel advancements in image processing and analysis are required to appropriately use such data for different targeted applications. This study assessed the potential of Sentinel-1A (S-1A) C-band synthetic aperture radar (SAR) backscatter in estimating canopy cover variability in cocoa agroforestry landscapes. We investigated two landscapes, in Center and South Cameroon, which differ in predominant vegetation: forest-savannah transition and forest landscape, respectively. We estimated canopy cover using in-situ digital hemispherical photographs (DHPs) measures of gap fraction, verified the relationship with SAR backscatter intensity and assessed predictions based on three machine learning approaches: multivariate bootstrap regression, neural networks regression, and random forest regression. Our results showed that about 30% of the variance in canopy gap fraction in the cocoa production landscapes was shared by the used SAR backscatter parameters: a combination of S-1A backscatter intensity, backscatter coefficients, difference, cross ratios, and normalized ratios. Based on the model predictions, the VV (co-polarization) backscatter showed high importance in estimating canopy gap fraction; the VH (cross-polarized) backscatter was less sensitive to the estimated canopy gap. We observed that a combination of different backscatter variables was more reliable at predicting the canopy gap variability in the considered type of vegetation in this study—agroforests. Semi-variogram analysis of canopy gap fraction at the landscape scale revealed higher spatial clustering of canopy gap, based on spatial correlation, at a distance range of 18.95 m in the vegetation transition landscape, compared to a 51.12 m spatial correlation range in the forest landscape. We provide new insight on the spatial variability of canopy gaps in the cocoa landscapes which may be essential for predicting impacts of changing and extreme (drought) weather conditions on farm management and productivity. Our results contribute a proof-of-concept in using current and future SAR images to support management tools or strategies on tree inventorying and decisions regarding incentives for shade tree retention and planting in cocoa landscapes.

Maximum power enhancement under partial shadings using modified Sudoku reconfiguration

Partial shading is one of the important factors in reducing maximum power generation from PV (Photovoltaic) arrays. Maximum power generation can be improved by selecting PV array in Total-Cross-Tied (T-C-T) connection. But still maximum power generated from T-C-T can be improved by distribution of shading over various rows. Due to distribution of shading, the current entering the node increases and results in improved maximum power generation. This can be done effectively by using Sudoku reconfiguration techniques. These techniques are economical, since they don't require any sensors and switching networks. This technique only changes the physical location of PV panel but electrical connection between the panels remains same. This paper proposes a Modified Sudoku reconfiguration pattern which enhances the maximum power from T-C-T connected PV array. Further, theoretical calculation of row current and power output have been done for existing and proposed topologies under various shading patterns. The performance of proposed pattern has been analyzed and compared using the specifications like Global Maximum Power (GMP), Fill Factor (FF), mismatch losses, and efficiency. From the results, it can be concluded that the Modified Sudoku reconfiguration enhances the GMP under all shading conditions.

A prediction model coupling occupant lighting and shading behaviors in private offices

Lighting control in office buildings is driven by occupant's demand for indoor light environment. The control behavior not only has a direct impact on occupants’ visual comfort, but also relates with the building lighting energy consumption. However, due to the effect of glare, lighting control is often associated with shading adjustment. In this regard, this paper proposed a prediction model which can accurately describe the lighting and shading coupling control behavior by fully considering the difference and diversity of occupants. The light environment preferences and the usage habits of lighting and shading system of occupants were firstly investigated and classified by means of questionnaire. Markov model and log-logistic survival model were introduced to quantitatively describe the probability distribution of various shading and lighting control behaviors. On this basis, combined with the indoor workplane illumination prediction model, the behavior of occupant's lighting and shading coupling control can be predicted. By comparing the four models considering or not considering the diversity and coupling effect, it is found that the proposed coupling prediction model shows better performance, the maxium error rate is only 13.04% for the lighting energy consumption prediction.

Optimal SuDoKu Reconfiguration Technique for Total-Cross-Tied PV Array to Increase Power Output Under Non-Uniform Irradiance

Partial shading condition drastically reduces the maximum power output of photovoltaic array. Partial shading occurs due to several factors, such as flying birds, trees, and passing clouds. Many ways can be mitigated partial shading problems in photovoltaic (PV) array. One among the way is reconfiguration techniques, namely reconfigure the location of PV modules in PV array based on irradiance levels in order to distribute shading effects and increasing maximum power. This paper proposed an optimal SuDoKu reconfiguration pattern for $9\times 9$ total-cross-tied (TCT) PV array to improve maximum power under partial shading conditions. In this approach, the physical location of PV modules in TCT array are rearranged based on optimal SuDoKu style without altering the electrical connections, so that the shading effects can distribute over the array. Further, the performance of proposed pattern investigated with existing SuDoKu pattern under different shading conditions by comparing the global maximum power point, mismatch losses, fill-factor, and efficiency using MATLAB-Simulink. Based on the results of this paper, it concluded that the proposed optimal SuDoKu reconfiguration arrangement is reducing the wiring arrangement and increasing the shading distribution over the array as compared to SuDoKu arrangement.

Sustainable co-production of food and solar power to relax land-use constraints

Renewable energy could often be land constrained by the diffuse nature of renewable resources. To relax land constraints, we propose the concept of ‘aglectric’ farming, where agricultural land will be sustainably shared for food and energy co-production. While wind turbines on agricultural land are already put into practice, solar power production on agricultural land is still under research. Here, we propose photovoltaic systems that are suitable for installation on agricultural land. Adjusting the intensity, spectral distribution and duration of shading allows innovative photovoltaic systems to achieve significant power generation without potentially diminishing agricultural output. The feasibility of solar aglectric farms has been proven through shadow modelling. The proposed solar aglectric farms—used alone or in combination with regular solar parks or wind plants—could be a solution for a sustainable renewable economy that supports the ‘full Earth’ of over 10 billion people. Diffusion of renewable energy technologies can be constrained by alternative land uses. Here the authors propose the idea of ‘aglectric’ farming and show with modelling how to use agricultural land sustainably for food and energy co-production.