Shading Conditions Research Articles

A model for energy predictions and diagnostics of large-scale photovoltaic systems based on electric data and thermal imaging of the PV fields

The aim of this investigation is the development of robust models for the performance prediction and automatic monitoring of large photovoltaic systems, based on historical and real-time electric and thermal data. This issue is increasingly important due to the worldwide diffusion of large photovoltaic systems and their need to identify and predict failures and malfunctions, in order to promptly assess the convenience of maintenance actions. The present model describes the response to irradiance and temperature conditions of both modules and inverters and also it is able to predict shading conditions able to affect the energy yield. The model has been validated against real electric measurements in 6 large PV plants located in southern Italy and it demonstrated to be able to predict the real time power production within a 4.1 % error. Even more importantly, the model and its comparison with subhourly measurements over several years has demonstrated its effectiveness in detecting downtime conditions caused by inverter or string problems. Simulations and measurements revealed that missed energy production due to electrical grid coupling downtime can exceed 50 % on certain days and that the shading conditions (up to 5 % of the daily energy production) can be easily detected and separated from component problems, thus avoiding false alarms. Finally, the analysis of aerial infrared images allowed to further test the model in failure detection capability, assess the relationship between thermal anomalies and underperformance conditions and in predicting the yearly deterioration rate at the PV plants.

Innovative solar PV array design: mitigating partial shading for Optimal Performance Index

Photovoltaic arrays are popular for green energy but suffer productivity loss from module faults and partial shading conditions (PSC). These two faults must be distinguished to avoid a permanent shutdown. Hence, this article presents two Novel 4 X 4 array structures with fewer tie-lines to address mismatch power loss under these abnormal conditions. The performances of these novel arrays are compared with Total-Cross-Tied (TCT), Honey-Comb (HC), and Bridge-Link (BL) under three PSC categories, with six cases falling into each category. PSCs are analysed at constant and varying temperatures, along with row and column module faults. Thirteen performance indices, including the Overall Performance Index (OPI), are addressed. The percentage reduction of tie-lines in novel topologies, along with their strengths and limitations, and variation of the performance indices of all the topologies are analysed. The obtained results reveal that the Novel-1 and Novel-2 arrays capture the global maximum power point (GMPP) in 67% and 78% of the analysed situations, respectively, outperforming standard arrangements and decreasing tie-lines. These findings support the efficacy and economic benefits of the novel array configurations, which provide considerable increases in PV system performance and reliability across a variety of environmental circumstances.

Mechanisms of ammonium detoxification in submerged macrophytes under shade conditions

Excessive ammonium disrupts the biological and physical characteristics of aquatic freshwater ecosystems, causing nutrient imbalances and toxicity. Different macrophytes exhibit varying tolerance levels to ammonium stress, influenced by species-specific adaptations. However, eutrophic water bodies not only have high nutrient loads but also exhibit low light transparency, necessitating an understanding of how submerged macrophytes cope with both high ammonium concentrations and low light conditions. In this study, we explored the tolerance of submerged macrophytes under these challenging conditions by testing various ammonium concentrations and light intensities. Our findings reveal that Myriophyllum spicatum demonstrates high ammonium tolerance under both optimal and low light intensities. Specifically, under optimal light, the primary ammonium assimilation pathway is catalyzed by NADH-GDH (Nicotinamide Adenine Dinucleotide-dependent Glutamate Dehydrogenase), with its activity increasing 4-fold at 50 mg L−1 [NH4+-N] compared to the control. Conversely, under low light intensity, the GS (Glutamine Synthetase)-catalyzed pathway becomes predominant, with GS activity rising 3-fold at 50 mg L−1 [NH4+-N] compared to the control. These results provide new insights into the adaptive mechanisms of M. spicatum, highlighting its flexible strategies for ammonium assimilation and its potential application in water restoration efforts. This study offers valuable information on the enzymatic pathways involved in ammonium detoxification, which is essential for developing effective strategies to manage and restore eutrophic aquatic systems.

An enhanced global MPPT method to mitigate overheating in PV systems under partial shading conditions

The hot-spot phenomenon in photovoltaic modules is a reliability issue typically caused by many reasons, including partial shading conditions. In such situations, the P-V curve exhibits a unique global maximum power peak (GMPP) and several local maximum power peaks (LMPPs). However, all the existing tracking methods (GMPPT) track the GMPP, even for a slight difference between peaks. For this purpose, an experimental investigation of the relationship between the operating point of a PV module and the temperature of their shaded parts has been carried out. In the studied case, it was found that the shaded cells’ temperature exceeds 99 °C, and it is directly related to the GMPP position on the P-V curve, where it decreased as the operating point is moved from the short circuit current towards the open-circuit voltage. As the shaded cells' temperature may reach high levels, which can result in early degradation of PV modules, an enhanced GMPPT method is proposed in this paper to handle the overheating issue. The proposed method aims to track the secure peak when two peaks or more have closer power values. Consequently, it alleviates the overheating and hot-spotting risks. Furthermore, the scanning voltage interval of this technique is bounded by lower and upper voltage limits. The proposed technique is experimentally validated and compared to two existing methods: the 0.8 Voc and the full sweeping method. The results show that when the power peaks have approximately the same value, the proposed method tracks the peak with the upper voltage (automatically the lower current) to minimize the thermal stress within the shaded cells. Moreover, the proposed method exhibits a 40 % saving in tracking time compared to the full sweeping method thanks to the efficient tracking mechanism that allows skipping certain intervals in the search space.

A new neuro-fuzzy controller based maximum power point tracking for a partially shaded grid-connected photovoltaic system

Today, renewable energy systems like photovoltaic system are widely used in various applications. Among the different types of microgrids, hybrid microgrids are the most used type, therefore, inverters should be used to exchange power between DC and AC sides. According to the existing economic issues, extracting the maximum possible power from these systems are an important issue. This paper presents a new neuro-fuzzy controller for achieving maximum power point tracking (MPPT) in a grid-connected PV system under partially shaded conditions. This controller uses the Gravity Search Algorithm (GSA) to track the global maximum power point (GMPP) of the presented grid-connected PV system. The method controls the grid-connected inverter at the desired voltage to achieve maximum power after receiving its required specifications from the system. The Matlab/Simulink software is used to evaluate the performance of the proposed method. The results show that the proposed method can track the maximum power point under uniform and partial shading conditions with high speed and accuracy. Specifically, the proposed algorithm improves the tracking speed and increases the power output compared to traditional methods. The neuro-fuzzy controller's adaptive capabilities allow it to respond efficiently to dynamic changes in shading, ensuring stable and optimal power output. These advantages make the proposed method a significant improvement over existing MPPT techniques.

Mission-oriented dynamic reconfiguration of airborne photovoltaic array based on multidisciplinary model

The solar-powered stratospheric airship is demonstrated overwhelming superiority because of affordable cost, recyclable material and low carbon emission. Progress has been made in the schemes of energy system consisting of curved photovoltaic array, storage, and energy management devices. However, research on various flight conditions and the resulting presence of non-uniform irradiance on the airborne solar array is rare. Moreover, the methods to reduce the power losses of on-board solar array are not investigated. This paper proposed a dynamic reconfiguration method to improve the output performance of on-board solar array in different mission conditions. The partial shading conditions of airborne and ground-based solar arrays are compared. The multiple traveling salesman problem with solar array is introduced. The Simulated annealing algorithm is adopted. The real-time optimization of solar array is obtained with the dynamic reconfiguration method according to the operating condition consisting of various parameters. The results show the proposed method effectively improves the output power of solar array compared with common total-cross-tied connections. The improvements of daily output energy of the airborne array are more than 13.7 %. The work provides a conducive reference for realizing the utilization prospect of solar energy system on aerial vehicles in a low carbon future.

Techno-economic-environmental optimization of hybrid photovoltaic-thermoelectric generator systems based on data-driven approach

Hybrid photovoltaic-thermoelectric generator (PV-TEG) system combines two types of energy conversion which is an important innovation to advance the development of renewable energy technologies. Hybrid system in practice needs to track the best operating point in real-time with the help of maximum power point tracking (MPPT) technology to ensure the system outputs maximum energy and optimizes performance. To improve the energy conversion efficiency and utilization of hybrid PV-TEG systems, as well as to effectively combat the negative impacts under partial shading conditions (PSC) and non-uniform temperature distribution (NTD), this paper proposes a hybrid system MPPT technique based on the bi-directional long and short-term neural networks (Bi-LSTM). The Bi-LSTM can consider both past and future data information, which will enhance the training process of the network and the accuracy of the model, making the results more comprehensive. It approaches the global maximum power point by searching for the maximum power down in the forward layer and up in the backward layer. The algorithm can effectively prevent from falling into local optimum under PSC and NTD. The case study section tests and explores the feasibility of utilizing Bi-LSTM to obtain the maximum power from a hybrid PV-TEG system under five case study scenarios, namely, start-up test, step change in solar irradiance, stochastic variation, Hong Kong four-season real case, and uncertainty analysis. Comparative analysis with the other five algorithms are also conducted to thoroughly verify the superiority of the proposed technique for hybrid system MPPT applications. The simulation results indicate that the hybrid PV-TEG system with Bi-LSTM achieves the optimal MPPT performance stably and efficiently under different operating conditions. In particular, low irradiate condition in spring, the energy generated by Bi-LSTM exceeds the INC, SAO and P&O energy outputs by 80.51%, 61.22%, and 31.04%, respectively.

Comparative assessment of various MPPT algorithms for solar photovoltaic systems under dynamic shading conditions

Comparative assessment of various MPPT algorithms for solar photovoltaic systems under dynamic shading conditions

Genome-Wide Identification of B-Box Family Genes and Their Potential Roles in Seed Development under Shading Conditions in Rapeseed.

B-box (BBX) proteins, a subfamily of zinc-finger transcription factors, are involved in various environmental signaling pathways. In this study, we conducted a comprehensive analysis of BBX family members in Brassica crops. The 482 BBX proteins were divided into five groups based on gene structure, conserved domains, and phylogenetic analysis. An analysis of nonsynonymous substitutions and (Ka)/synonymous substitutions (Ks) revealed that most BBX genes have undergone purifying selection during evolution. An analysis of transcriptome data from rapeseed (Brassica napus) organs suggested that BnaBBX3d might be involved in the development of floral tissue-specific RNA-seq expression. We identified numerous light-responsive elements in the promoter regions of BnaBBX genes, which were suggestive of participation in light signaling pathways. Transcriptomic analysis under shade treatment revealed 77 BnaBBX genes with significant changes in expression before and after shading treatment. Of these, BnaBBX22e showed distinct expression patterns in yellow- vs. black-seeded materials in response to shading. UPLC-HESI-MS/MS analysis revealed that shading influences the accumulation of 54 metabolites, with light response BnaBBX22f expression correlating with the accumulation of the flavonoid metabolites M46 and M51. Additionally, BnaBBX22e and BnaBBX22f interact with BnaA10.HY5. These results suggest that BnaBBXs might function in light-induced pigment accumulation. Overall, our findings elucidate the characteristics of BBX proteins in six Brassica species and reveal a possible connection between light and seed coat color, laying the foundation for further exploring the roles of BnaBBX genes in seed development.

Growth and Yield of Two Mustard Varieties (Brassica Juncea L.) at Various Shading Levels

Mustard greens are one of the vegetable commodities plants. The part used is the young leaves, which can be processed into traditional medicinal and vegetable ingredients that benefit human health. This research aims to determine the level of shade tolerance on the growth and yield of mustard plants and determine mustard varieties that are tolerant of minimum sunlight conditions. This research was carried out in experimental fields using artificial fields in June – July 2023. This research used a split-plot design with 2 factors. Tafif shade as the main plot consists of no shade 0%, 55%, 70%, and 95%. The sub-plot varieties consist of the Tosakan variety and the Kumala variety. The results of the research indicate that sunlight intensity reduction negatively impacted the growth and yield of mustard plants. However, under 55% shade conditions, there was no significant difference observed in the growth and yield of mustard plants compared to those grown without shade. The Tosakan and Kumala varieties did not show any differences in the growth or yield of mustard plants.

Growth and Yield of Two Mustard Varieties (Brassica Juncea L.) at Various Shading Levels

Mustard greens are one of the vegetable commodities plants. The part used is the young leaves, which can be processed into traditional medicinal and vegetable ingredients that benefit human health. This research aims to determine the level of shade tolerance on the growth and yield of mustard plants and determine mustard varieties that are tolerant of minimum sunlight conditions. This research was carried out in experimental fields using artificial fields in June – July 2023. This research used a split-plot design with 2 factors. Tafif shade as the main plot consists of no shade 0%, 55%, 70%, and 95%. The sub-plot varieties consist of the Tosakan variety and the Kumala variety. The results of the research indicate that sunlight intensity reduction negatively impacted the growth and yield of mustard plants. However, under 55% shade conditions, there was no significant difference observed in the growth and yield of mustard plants compared to those grown without shade. The Tosakan and Kumala varieties did not show any differences in the growth or yield of mustard plants.

Retraction Note: Rigorous reduction of partial shading condition in grid connected solar PV system using discrete time-based PSO controller

Retraction Note: Rigorous reduction of partial shading condition in grid connected solar PV system using discrete time-based PSO controller

Intelligent Solar System for Effective Renewable Energy

Photovoltaic (PV) systems are gaining popularity as a sustainable and renewable energy solution. Charge controllers play a crucial role in maximizing the energy harvested from PV panels and ensuring efficient battery charging. This study presents a comprehensive comparison between Pulse Width Modulation (PWM) and Maximum Power Point Tracking (MPPT) charge controllers, analyzing their performance, efficiency, and suitability for different PV system configurations. The analysis begins with an overview of PWM charge controllers, which regulate the charging process by rapidly switching the PV panel voltage on and off. PWM controllers are known for their simplicity, affordability, and reliability. However, their fixed voltage operation limits their ability to extract maximum power from the PV panels, especially in scenarios with varying solar irradiance and temperature conditions. In contrast, MPPT charge controllers employ advanced algorithms to continuously track the maximum power point (MPP) of the PV panels. By dynamically adjusting the operating voltage and current, MPPT controllers can optimize the power transfer from the PV panels to the battery bank. This capability results in higher energy harvesting, especially in situations with partial shading or non-ideal operating conditions.

Advanced particle swarm optimization for efficient and fast global maximum power point tracking under partial shading conditions

Partial shading (PS) is a common issue in photovoltaic systems (PVs), and it can significantly reduce the system's output power. This paper presents the advanced particle swarm optimization (APSO) algorithm. APSO is designed to alleviate the challenges posed by PS in PVs in from where of effectiveness and stability speed so that it works to achieve and maintain the global maximum power point (GMPP) under PS conditions. It leverages persistent variables to store and track system states and iterations; it also includes checks to ensure that the duty cycle remains within specified bounds facilitating more effective optimization. Additionally, APSO optimizes solar panel duty cycles and velocities to converge toward an optimal solution to improve overall power generation efficiency and settling time. The results evaluation involves testing the performance of photovoltaic panels under three different shading scenarios and comparative analysis against recent Heuristic-optimization-based GMPP techniques, this study and comparative analyses demonstrate APSO's effectiveness and superiority in terms of high efficiency that reaches 99.85% and fast settling time of GMPP at less than 0.01 second across all test cases. APSO presents a promising solution for maximizing PV power output in the presence of partial shading.

Genome-wide identification and expression analysis of phytochrome-interacting factor genes during abiotic stress responses and secondary metabolism in the tea plant

Phytochrome-interacting factors (PIFs) are pivotal transcriptional regulators controlling photomorphogenesis, environmental responses, and development in plants. However, their specific roles in coordinating adaptation towards abiotic stress and metabolism remain underexplored in tea plants. Here, we identified seven PIF members from four distinct clades (PIF1, PIF3, PIF7, and PIF8). Promoter analysis implicated CsPIFs in integrating light, stress, hormone, and circadian signals. Most CsPIFs exhibited rapid increase in expression under shading, especially CsPIF7b/8a, which displayed significant changes in long-term shading condition. Under drought/salt stress, CsPIF3b emerged as a potential positive regulator. CsPIF3a was induced by low temperature and co-expressed with CsCBF1/3 and CsDREB2A cold response factors. Dual-luciferase assays confirmed that act as negative regulator of the CBF pathway. Expression profiling across 11 tea cultivars associated specific CsPIFs with chlorophyll biosynthesis and accumulation of anthocyanins, flavonols, and other metabolites. In summary, this study highlights the significance of CsPIFs as central coordinators in managing intricate transcriptional reactions to simultaneous abiotic stresses and metabolic adjustments in tea plants. This insight informs future strategies for enhancing this economically crucial crop through crop improvement initiatives.

The Effect of Climate on Strongly Disturbed Vegetation of Bait Sites in a Central European Lower Montane Zone, Hungary

Human landscape-transforming activities contribute to the global change in vegetation in different forms. Hunting is one of the most ancient human landscape-shaping activities. Feeders for hunting are particularly disruptive to vegetation. In the present study, we conducted a vegetation survey in these highly disturbed places. We investigated the vegetation dynamics over several years in the turkey oak–sessile oak zone, in two areas with different moisture and shade conditions (forest and clearing). Important background factors are the changes in precipitation and temperature. Our results confirm that weed infestation is detectable at bait sites over a long period. The seasonal changes in field weed vegetation, as well as the increase in the number and coverage of weed species at the end of summer, resulting from lifestyle characteristics, were generally detectable in all years and locations, especially in the case of open and more strongly degraded clearings. Meteorological factors played a role in the degree of weed infestation in each year. Degradation was more significant in drought years, while regeneration was also observed in wetter periods. At baits located in the clearing, we showed a positive correlation between the amount of summer precipitation and the total coverage of weed species, as well as between the average spring temperature and the coverage of certain weed species. With the drying of the climate, the disturbed areas are constantly losing their natural value, but wetter weather is not an automatic solution either. Considering that there are approx. 30,000 bait sites in the country, and they are used regularly and very intensively, they can serve as major infection hotspots for alien species in a network.

The light intensity in the cultivation environment and the impact of glyphosate on plants of the Urochloa genus

The variation in light within the environment triggers morphophysiological changes in plants and can lead to distinct responses in sun-exposed or shaded plants to glyphosate. The response of Urochloa genotypes subjected to desiccation with 2160, 1622.4, 1080, 524.4, 273.6, and 0.0 g ha−1 of glyphosate was evaluated in full sun and shade conditions. Cayana grass, mulato II grass, and sabiá grass – hybrids recently launched on the market, in addition to palisade grass and congo grass were evaluated. Under full sun, we achieved control of congo grass using 1080 g ha−1 of glyphosate, while the other grasses required 2160 g ha−1. In the low-light environment, sabiá grass was effectively controlled with 524.4 g ha−1 of glyphosate, but the other grasses needed 273.6 g ha−1. In shading, compared to full sun, the savings with glyphosate were 75 and 76% for the control of congo grass and sabiá grass, respectively, and 87% for palisade grass, mulato II grass and cayana grass. Increasing glyphosate doses leads to a decline in the quantum efficiency of photosystem II and in the electron transport rate, especially in the shade. Urochloa genotypes are more sensitive to glyphosate in the shade, which must be considered when determining the herbicide dose.

Application of circle search algorithm for solar PV maximum power point tracking under complex partial shading conditions

Solar photovoltaic (SPV) energy exhibits a potential role in the world for generating electricity and avoiding the block out in the power system. However, the hardest task in the PV system is to track the global maxima power (GPP) instead of local peak power (LPP) under partial shading conditions (PSC). To track the GPP, a new circle search algorithm (CSA) is implemented in this paper and is executed in MATLAB/SIMULINK environment. This method is examined at various irradiation conditions and compared their performance with other studied methods in terms of tracking time, settling time and efficiency. The simulation outcome of the CSA method efficiencies 99.96 % in case 1, 99.74 % in case 2, and 99.94 % in case 3. For checking the robustness and stability of the system statistical analysis was done on the proposed methods. It is found that the suggested method exhibits higher performance than the other methods.

A modified invasive weed optimization for MPPT of PV based water pumping system driven by induction motor

A novel approach called Modified Invasive Weed Optimization (MIWO) technique has been developed and combined with the Perturb and Observes (P&O) algorithm to enhance the extraction of maximum power from photovoltaic (PV) panels in the presence of partial shading conditions. The conventional P&O algorithm falls short in extracting the maximum power from PV systems under partial shading conditions due to the existence of multiple maximum points. In such scenarios, optimization techniques can be employed to search for the global maximum point. The proposed MIWO-based P&O algorithm updates the reference voltage to ensure that the PV system operates at the Maximum Power Point (MPP) based on the prevailing weather conditions. This MIWO based PV system is further fed to water pumping system. A PV-based water pumping system is utilized for both irrigation and domestic purposes. Additionally, a sensorless vector control-based induction motor is employed in this study to drive the pump. The objective of this research is to demonstrate the achievement of an efficient PV-based water pumping system without the need for battery storage. Various results based on MIWO are compared with PSO and GWO. The results are presented based on various water pumping applications and the availability of solar irradiance during rapid climate changes. MATLAB/Simulink simulations, along with hardware-based experiments, are provided to validate the effectiveness of the proposed method under both transient and steady-state conditions.

Comparison of drying methods for biochemical composition, energy aspects, and color properties of alfalfa hay

AbstractAlfalfa is a crucial feed source for livestock, necessitating proper drying to achieve optimal moisture levels before consumption. This study aims to reveal alfalfa's drying characteristics and quality properties, defined as the queen of feed, by drying it under different drying conditions. Alfalfa samples were dried using different drying techniques: Open-sun, shade, greenhouse, hybrid (microwave-air-convective), air-convective, microwave, and freeze-drying. The influence of drying techniques on the drying kinetics, energy aspects, biochemical properties, mineral composition, fatty acids, carotene, and color attributes of alfalfa were investigated. Present findings revealed that shade and high-temperature drying conditions increased the crude fiber content (23.18%) of alfalfa samples. The highest protein values were found in open-sun drying (22.01%) and 60 °C air-convective drying (22.10%). The highest values for mineral composition were determined in freeze drying, and the greatest Zn (33.68 ppm) and Fe (135.45 ppm) contents were determined in 100 °C air-convective drying. The highest saturated fatty acids open-sun (21.27%) and freeze dryer (21.07%), unsaturated fatty acids at 60 °C (84.51%) and 80 °C (84.26%), poly unsaturated fatty acids at 60 °C (78.36%), 80 °C (78.14%) and 100 °C (77.74%) were obtained. The drying kinetics of alfalfa were best modeled with the Jena&Das, and in terms of a* (greenness) values, the hybrid drying yielded the best results. The lowest total energy consumption (54.00 kWh) was seen in 200W + 80 °C hybrid drying and the highest (324.72 kWh) in 100 °C air-convective drying. The color attributes and energy consumption findings showed that hybrid drying could efficiently be used for alfalfa drying. In addition, freeze drying was determined to be the best drying method in terms of nutrient preservation.