Seasonal Solar Radiation Research Articles

Mathematical modeling and seasonal solar radiation variability in Nigeria’s geo-political zones: A recurrence and multifractal analysis

This article delves into the seasonal variation of solar radiation patterns across Nigeria’s four geo-political zones, exploring their complex, scale-dependent behaviors. By employing chaotic quantifiers, the study characterizes irregular and self-similar patterns, enhancing our understanding of solar radiation variability and heterogeneity. The research uniquely fits meteorological parameters onto a global solar radiation model and focuses on the underexplored nonlinear aspects within tropical regions, specifically in the Nigerian context. Utilizing daily data from ERA INTERIM satellite archives for representative stations, the study employs nonlinear time series analysis methods like recurrence plots, recurrence qualitative analysis, and multifractal spectral analysis to comprehensively explore the unpredictable behaviors observed. The quantifier spectrums play a key role in revealing intricate scaling behaviors and correlation structures among environmental variables, shedding light on patterns often concealed by conventional statistical methods. For instance, we found that solar radiation variability in the northern region increases more significantly during the dry season compared to the wet season, unlike in the southern region. Additionally, the multifractal spectral analysis revealed a higher degree of complexity in solar radiation patterns during transition periods between seasons. The findings reveal a low recurrence quantitative analysis, long right tail, and truncations at both ends of the spectrum. This suggests instability in solar radiation across different seasons and locations. Nonetheless, the results also demonstrate that solar radiation is consistently available throughout the year, which is typical of tropical regions.

Estimating the efficacy of solar photovoltaic panels in Lebanon using a digital surface model: A geospatial approach

With the escalating need for alternative energy sources due to economic crises and fossil fuel shortages in Lebanon, solar photovoltaic (PV) panels have emerged as an attractive solution. This study examines the capacity and efficacy of rooftop-installed PV solar panels. Using geospatial technologies, including Digital Surface Models drone-based photogrammetry, the study assesses geometric and solar characteristics, seasonal solar radiation, solar duration, and power for 40 PV units installed in the study area. This research presents specific quantitative values for optimal orientations that result in high solar radiation across various seasons and identifies varying slopes influencing the performance of PV solar panels. Employing the Agglomerative Hierarchical Clustering (AHC) technique, PV units are systematically classified into clusters labeled as Moderate, High, Low, and Very Low solar power, offering quantitative metrics regarding the effectiveness of distinct panels. The high-efficiency Cluster exhibits an average solar power of 1868.114 kWh/m² during the summer season, whereas the Very Low Cluster, comprising panels with minimal solar power output, averages 150.578 kWh/m² in the same season. In conclusion, the most effective PV solar panels within the study area are those oriented between 195 and 225 degrees, with shallow inclination angles and larger surface areas contributing to enhanced performance in capturing solar radiation and generating power. These precise quantitative insights contribute to informed decision-making for optimizing the placement of PV panels to enhance energy generation. The study's recommendations are substantiated by specific numerical data, guiding future solar installations to maximize solar energy generation.

Day-ahead seasonal solar radiation prediction, combining VMD and STACK algorithms

Abstract This article proposes a method for accurately predicting solar irradiance over a 24-hour horizon to forecast photovoltaic energy generation in a positive-energy building. In order to make this prediction, the input data are divided into seasons and preprocessed using the variational mode decomposition (seasonal-VMD) method. The VMD method is used for extracting high-bandwidth features from the input data, decomposing them into a finite number of smooth modes and focusing on specific frequency ranges. Hence, the accuracy of signal extraction using the VMD method can be improved by selecting particular parameters judiciously, which impacts the smoothing and frequency concentration of the extracted signal. In this regard, the salp swarm algorithm (SSA) is employed to identify the optimal VMD parameters that can be used to enhance extraction accuracy. In addition, the obtained residual between the observed solar irradiation data and their decomposed modes is treated to enhance the prediction process. A stacking algorithm (STACK) is used to predict the following 24-hour solar irradiance modes and the residual, which are finally summed to reconstruct the desired signal. The performances of the proposed prediction method are evaluated using two quantitative evaluation indices: the normalized root mean square percentage error (NRMSPE) and normalized mean absolute percentage error (NMAPE). The proposed model is trained on data collected for three years in Rabat (2019–22). The performance of the proposed model is evaluated by predicting the 24-hour solar irradiance for a different season. The proposed approach seasonal-VMD-STACK is compared with two other methods in the case of using VMD-based STACK without season partition and STACK method only. Moreover, the proposed method has exhibited stability and proven good results with an NRMSPE of 3.87% and an NMAPE of 1.58% for cloudy days during the test phase. The results demonstrate that residual preprocessing, seasonal input data partition and appropriate selection of VMD parameters improve the performance and accuracy of the prediction.

MODELLING OF DIFFERENT MOTHER WAVELET TRANSFORMS WITH ARTIFICIAL NEURAL NETWORKS FOR ESTIMATION OF SOLAR RADIATION

IIn recent years, the interest in renewable energy sources has increased due to environmental damage and, the increasing costs of fossil fuel resources, whose current reserves have decreased. Solar energy, an environmentally friendly, clean and sustainable energy source, is one of the most important renewable energy sources. The amount of electrical energy produced from solar energy largely depends on the intensity of solar radiation. For this reason, it is essential to know and accurately predict the characteristics of the solar radiation intensity of the relevant region for the healthy sustainability of the existing solar energy systems and the systems planned to be installed. For this purpose, a two-stage forecasting model was developed using the hourly solar radiation intensity of 2014 in a region in Turkey. In the first stage of the study, the second month of each season was selected to investigate the seasonal effects of the region and large, medium, and small-scale events in the study area were examined using discrete wavelet transform. The performances of different mother wavelets in the Artificial Neural Network model with Wavelet Transform (W-ANN) are compared in the second stage. July, the most successful estimation result in seasonal solar radiation intensity was obtained. The most successful RMSE values for January, April, July and October were 65,9471W/m^2, 74,3183 W/m^2, 54,3868 W/m^2, 78,4085 W/m^2 respectively, the coiflet mother wavelet measured it.

Large-scale green hydrogen production using alkaline water electrolysis based on seasonal solar radiation

Abstract The research study provides a techno-economic analysis for the green hydrogen generation based solar radiation data for both the single and hybrid alkaline water electrolyzer and energy storage system systems. In addition, a carbon footprint study is conducted to estimate the developed system carbon dioxide emissions. The optimal size of the alkaline water electrolyzer and energy storage system is determined by a genetic algorithm that takes into account a carbon tax on carbon emissions. Based on itemized cost estimating findings, unit hydrogen production costs for a single system and a hybrid system were $6.88/kg and $8.32/kg respectively. Furthermore, capital cost it has been found as a key element in determining the optimal scale of the alkaline water electrolyzer and energy storage system, which are essential for minimizing the unit hydrogen production cost. Lastly, an effort to minimize the capital cost of producing green hydrogen is required when the rising trend of the carbon dioxide tax is taken into account.

Analysis of yield constraints and seasonal solar radiation and temperature limits for stable cultivation of dry direct-seeded rice in northeastern Japan

Analysis of yield constraints and seasonal solar radiation and temperature limits for stable cultivation of dry direct-seeded rice in northeastern Japan

Determining the role of richness and evenness in alpine grassland productivity across climatic and edaphic gradients.

Spatial heterogeneity of climatic and edaphic gradients can substantially affect the grassland productivity function. However, few studies have tested the importance of species richness and evenness on regulating grassland productivity across spatial-scale climatic and edaphic changes. This study examines the complex mechanisms by which species richness and evenness regulate productivity in alpine meadow and steppe. We used field survey data to explore above-ground productivity formation and sensitivity to spatial-scale climatic and edaphic response of alpine grassland based on species richness and evenness. Results showed that the growing season solar radiation was the main driving factor of above-ground biomass and was strongly negatively correlated with above-ground biomass. Furthermore, compared with alpine steppe, above-ground biomass in alpine meadow was more responsive to climatic variables, but less responsive to soil variables. Unexpectedly, we found that the regulation patterns of species richness and evenness on above-ground biomass were different in both habitats by a structural equation model analysis. Our study demonstrated that species evenness and richness were both important in co-regulating above-ground biomass in alpine meadow, whereas species richness mattered more than species evenness in regulating above-ground biomass in alpine steppe. Our results offer further support for species richness and evenness co-regulating grassland productivity across spatial-scale climatic and edaphic gradients, which helps maintain the benefits of plant diversity and alpine grassland ecosystems.

Outlook of industrial-scale green hydrogen production via a hybrid system of alkaline water electrolysis and energy storage system based on seasonal solar radiation

Hydrogen has been considered as a clean energy carrier by generating electricity via fuel cells without carbon dioxide emissions; however, in the current stage, most hydrogen is produced by a steam methane reforming, emitting carbon dioxide as a byproduct, together. In this context, a green hydrogen production system, which is consisted of water electrolysis and a renewable energy plant, should be expanded to prepare for the upcoming hydrogen society in the future. A techno-economic analysis is carried out for green hydrogen production based on seasonal solar radiation data in the case of the single and the hybrid system, which is designed as only alkaline water electrolyzer and a combination of alkaline water electrolyzer and energy storage system. In addition, a carbon footprint analysis is performed to quantify the carbon dioxide emissions for the proposed systems. And the optimal scale of alkaline water electrolyzer and energy storage system is figured out via a genetic algorithm considering a carbon tax on emitted carbon dioxide. Based on itemized cost estimation results, 6.55 and 6.88 USD kgH2−1 of unit hydrogen production costs were obtained for the case of a hybrid and a single system, respectively. Further, the results present that the hybrid system is preferred when Li-ion battery costs decrease to under 79.67 USD kWh−1. In addition, the capital cost is a crucial factor to figure out the optimized alkaline water electrolyzer scale and energy storage system capacity that set the optimized size is important to minimize the unit hydrogen production cost. Finally, the effort to reduce the capital cost to produce the green hydrogen is necessary when increasing trend of carbon dioxide tax is considered.

The role of physicochemical and biochemical processes on carbonate precipitation within the Laguna Timone maar in the Pali Aike Volcanic Field, southernmost extra-Andean Patagonia

Carbonate deposits and sedimentary records from lakes in southern Patagonia provides an excellent contribution in the regional environmental register. The Laguna Timone is situated within a maar of the Pali Aike Volcanic Field, a Quaternary volcano-tectonic complex in southernmost South America and represents one of hundreds of “pools” of brines developed after explosive volcanic eruptions in a periglacial environment. The lake constitutes an endorheic hydrological system where processes leading to carbonate precipitation took place under extreme physicochemical conditions and biological influences that can be explored. Laguna Timone is recharged by groundwater and sporadic episodes of precipitation (ca. 200 mm/year) and high evaporation rates are controlled by regimes of strong wind (westerlies) and seasonal solar radiation. Carbonate precipitation was studied in microbialite fragments of tufa deposits and carbonate crust located in the edge of the lake, and the mineralogy of all samples is calcite. The clay fraction of the sediment underlying the carbonates was characterized and HRTEM analysis shows that authigenic smectites have influence on calcite crystal precipitation. The positive δ18O values (2.28 ‰) in thin crust layers are associated with evaporation processes. In contrast, the negative δ18O values (−6.52 ‰) in the microbialites show meteoric and/or groundwater influences. The δ13C (−0.43 ‰ to 2.50 ‰) values indicate physico-chemical and biochemical processes controlling the precipitation. The carbonate precipitation involves the interrelations of hydrogeological properties, climate and biological influences. Laguna Timone provides a natural laboratory for understanding mineral precipitation processes that register continuous climatic and environmental archives.

Optimum design and orientation of a greenhouse for seasonal winter drying in Morocco under constant volume constraint

In this work the solar radiation intercepted by two commonly used greenhouses, namely the even-span and uneven-span shapes, was optimized under a constant volume for the first time. The optimal shape and orientation of the greenhouse was determined for drying purposes during the winter period (from 1st October to 31st March) by varying the two decision variables (orientation of the greenhouse and its roof tilt angle) with a small step of 1°. The seasonal solar radiation transmitted inside the greenhouse was computed for each configuration and orientation in order to identify the optimal design and orientation. The solar energy transmitted was evaluated by taking into account the incidence angle dependence of the transmittance of the greenhouse cover (polycarbonate). The results showed that the uneven–span greenhouse with a roof tilt angle of 45° and an orientation of −80° (10° from the E-W orientation) was optimal for capturing the maximum solar radiation compared to all other configurations, shapes and orientations for Marrakech Morocco. This incidence angle dependence of the transmittance did not significantly affect the optimal shape and orientation but reduced the solar radiation inside by 10% compared to the reference case of normal incidence transmittance. It is estimated that the optimum configuration (shape, orientation) will enable to reduce the heating costs of the greenhouse system during the winter season by $ 90 per square meter of the greenhouse floor. This model can be easily extended to assess the total solar radiation intercepted by all such greenhouse systems under different weather conditions.

Data-driven dynamics of phytoplankton blooms in a reaction–diffusion NPZ model

Abstract The causes of seasonal phytoplankton blooms in the ocean are a debated topic. The disturbance-recovery hypothesis posits that blooms are initiated when seasonally changing light and mixing conditions disrupt attractive equilibrium states in the predator–prey relationship between zooplankton and phytoplankton, leading to an accumulation in phytoplankton biomass. This paper follows up on this notion with a nutrient-phytoplankton-zooplankton (NPZ) model incorporating diffusion and depth-dependent coefficients in which we explore the nature of these attractive states. The reaction–diffusion NPZ model, incorporated with seasonal solar radiation and mixed layer depth data, simulates blooms with better timing than a related ordinary differential equations model but still leaves room for further modeling and improvement. The results of the data-driven, reaction–diffusion model aid in understanding the driving forces of the simulated phytoplankton blooms. The results also reveal a significant influence on the vertical structure of plankton concentration by the attenuation of light with depth in the ocean. Models that accurately simulate blooms tend to share characteristics of the reaction–diffusion model in this paper. The dynamics described in this paper could be a key mechanism that seasonally disrupts the ecological balance between phytoplankton and zooplankton and facilitates a high-latitude marine phytoplankton bloom.

Low-power solar stations on dam surfaces of reserrvoirs

Agriculture in the Republic of Uzbekistan is based on irrigated agriculture, therefore, not all rivers existing in the country fully satisfy the needs of consumers, and water resources are accumulated mainly from reservoirs. From this point of view, the strength of the dams of these reservoirs has been studied in detail. However, in most cases, the external slopes of the dams of these artificial hydraulic structures are not used. This, in turn, requires new scientific solutions for the development of solar energy in Uzbekistan, where the amount of solar radiation is quite large. As an example, to study this problem, the amount of seasonal solar radiation in the southeastern region of the republic was obtained using simulation values using a geographic information system on the ArcGIS 9.3 platform and a seasonal map of solar radiation was developed. At the same time, to ensure the efficient operation of solar photovoltaic installations made of photovoltaic cells based on semiconductor silicon materials, it is proposed to use the external slope of the Talimarzhan dam located in this territory. This, in turn, makes it possible to eliminate the problem of preventing the drop in the coefficient of performance (COP) of solar photovoltaic cells, which is an important working part, with an increase in one of the most negative external factors - temperature.The results show that based on the generated direct electric current from the solar photovoltaic station, the following can be supplied: lighting system for the reservoir, uninterrupted power supply of synchronous motors installed at pump station №7, consumers of auxiliary needs of the hydroaccumulative power station, which is planned to be installed in the reservoir, potential electricity consumption, consisting of from tourism services infrastructure to the development of ecotourism.

Skillful statistical models to predict seasonal wind speed and solar radiation in a Yangtze River estuary case study

This paper illustrates the potential for seasonal prediction of wind and solar energy resources through a case study in the Yangtze River estuary. Sea surface temperature and geopotential height-based climate predictors, each with high correlation to ensuing seasonal wind speed and solar radiation at the Baoshan weather observing station, are identified and used to build statistical models to predict seasonal wind speed and solar radiation. Leave-one-out-cross-validation is applied to verify the predictive skill of the best performing candidate model for each season. We find that predictive skill is highest for both wind speed and solar radiation during winter, and lowest during summer. Specifically, we find the most skill when using climate information from the July-September season to predict wind speed or solar radiation during the subsequent November-January season. The ability to predict wind and solar energy availability in the upcoming season can help energy system planners and operators anticipate seasonal surpluses or shortfalls and take precautionary actions.

The role of climate in the trend and variability of Ethiopia's cereal crop yields

Food security has been and will continue to be a major challenge in Ethiopia. The country's smallholder, rainfed agriculture renders its food production system extremely vulnerable to climate variability and extremes. In this study, we investigate the impact of past climate variability and change on the yields of five major cereal crops in Ethiopia—barley, maize, millet, sorghum, and wheat—during the period 1979–2014 using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model. The model is calibrated at both the site and agroecological-zone scales. At the sites studied, the model results suggest that climate in the past four decades may have contributed to an increasing trend in maize yield, a decreasing trend in wheat yield, and no clear trend in the yields of barley and millet; cereal crop yield is positively correlated with growing season solar radiation and temperature, but negatively correlated with growing season precipitation. For modeled cereal crops across the nation during the study period, yield in western Ethiopia is positively correlated with solar radiation and day time temperature; in the eastern and southeastern Ethiopia where water is a limiting factor for growth, yield is positively correlated with precipitation but negatively correlated with solar radiation and both day time and night time temperature. The national average of simulated yields of most crops (except maize) showed an overall decreasing (although not statistically significant) trend induced by past climate variability and changes. Over a large portion of the highly productive areas where there is a negative correlation between yield and temperature, yield is simulated to have significantly decreased over the past four decades, an indication of adverse climate impact in the past and potential food security concern in the future.

Environmental analysis of a nano-grid: A Life Cycle Assessment

Renewable energy sources are fundamental to face the problem of climate changes. Unfortunately, some resources, such as wind and solar radiation, have fluctuations affecting the electrical grids stability. Energy storage systems can be used for a smart energy management to accumulate power from renewable sources. For such reason, these devices play a key role to achieve a sustainable electric system. On the other hand, they are affected by some environmental drawbacks mainly connected with the depletion of rare and expensive materials. Based on these considerations, in this study a nano-grid composed by a photovoltaic plant, a backup generator and an energy storage system is analysed by an environmental Life Cycle Assessment approach. A Solar Home System is designed, and its environmental profile is evaluated considering several Lithium-ion batteries. Among them, nickel-cobalt aluminium oxide cells resulted to be the most suitable solution for a Solar Home System (46.66 Pts/MWh). Moreover, a sensitivity analysis of the Solar Home System is performed and a hybrid energy storage plant integrating hydrogen and batteries is proposed to face the problem of seasonal solar radiation variability. Four scenarios having different gas pressure levels and lifespan of the devices are considered. Results show that currently the most sustainable configuration is represented by the Solar Home System, but in the future a hybrid nano-grid equipped with 700 bar hydrogen storage might be the best off-grid configuration for minimizing the impact on the environment (37.77 Pts/MWh). Extending the perspective of our analysis to future on-grid potential configurations, an efficient connection of the Solar Home System with a smart-grid is assessed as it looks more sustainable than other off-grid solutions (22.81 Pts/MWh).

Spatial and temporal assessments of complementarity for renewable energy resources in China

More wind and solar power will be integrated into future power systems in China. Assessing the complementarity of wind and solar resources helps to mitigate the fluctuation of renewable power output effectively. This study comprehensively assesses the complementarity of wind and solar resources over China based on MERRA-2 reanalysis dataset. The results show that the complementarity between two resources and that between different regions for a single resource are significantly affected by the time scales. The complementarity between wind and PV power plants is superior to that between wind or solar power plants in different regions. Furthermore, the complementarity between wind and PV power can be further improved by dispersing the locations of wind farms, especially when the PV power is significantly positively correlated with wind power at the same location. However, dispersing the locations of PV plants may not work since the diurnal and seasonal solar radiation are highly similar in different regions. Extreme value analysis is employed to assess the benefits obtained from the wind-solar complementarity. The duration of no power output and the hourly negative fluctuation in power output are significantly reduced due to the complementarity.

Inorganic carbon fixation in ice-covered lakes of the McMurdo Dry Valleys

AbstractInorganic carbon fixation, usually mediated by photosynthetic microorganisms, is considered to form the base of the food chain in aquatic ecosystems. In high-latitude lakes, lack of sunlight owing to seasonal solar radiation limits the activity of photosynthetic plankton during the polar winter, causing respiration-driven demand for carbon to exceed supply. Here, we show that inorganic carbon fixation in the dark, driven by organisms that gain energy from chemical reactions rather than sunlight (chemolithoautotrophs), provides a significant influx of fixed carbon to two permanently ice-covered lakes (Fryxell and East Bonney). Fryxell, which has higher biomass per unit volume of water, had higher rates of inorganic dark carbon fixation by chemolithoautotrophs than East Bonney (trophogenic zone average 1.0 µg C l−1 d−1vs 0.08 µg C l−1 d−1, respectively). This contribution from dark carbon fixation was partly due to the activity of ammonia oxidizers, which are present in both lakes. Despite the potential importance of new carbon input by chemolithoautotrophic activity, both lakes remain net heterotrophic, with respiratory demand for carbon exceeding supply. Dark carbon fixation increased the ratio of new carbon supply to respiratory demand from 0.16 to 0.47 in Fryxell, and from 0.14 to 0.22 in East Bonney.

The response of tropical precipitation to Earth's precession: the role of energy fluxes and vertical stability

Abstract. The changes in Earth's precession have an impact on the tropical precipitation. This has been attributed to the changes in seasonal solar radiation at the top of the atmosphere. The primary mechanism that has been proposed is the change in thermal gradient between the two hemispheres. This may be adequate to understand the zonal mean changes, but cannot explain the variations between land and oceans. We have used a simple model of the intertropical convergence zone (ITCZ) to unravel how precipitation changes with precession. Our model attributes the changes in precipitation to the changes in energy fluxes and vertical stability. We include the horizontal advection terms in this model, which were neglected in the earlier studies. The final response of the land and oceans is a result of complex feedbacks triggered by the initial changes in the insolation. We find that the changes in precipitation over the land are mainly driven by changes in insolation, but over the oceans, precipitation changes on account of changes in surface fluxes and vertical stability. Hence insolation can be a trigger for changes in precipitation on orbital timescales, but surface energy and vertical stability play an important role too. The African monsoon intensifies during a precession minimum (higher summer insolation). This intensification is mainly due to the changes in vertical stability. The precipitation over the Bay of Bengal decreases for minimum precession. This is on account of a remote response to the enhanced convective heating to the west of the Bay of Bengal. This weakens the surface winds and thus leads to a decrease in the surface latent heat fluxes and hence the precipitation.

Design and Analysis of a Solar-Power Mini-UAV for Extended Endurance at Low Altitude

A solar-powered mini-UAV has been designed for long-endurance performance at low altitude, reflecting practical constraints from preceding experience of authors. The parametric analysis of the solar-power propulsion system is the primary interest of the present study, along with the power requirement estimation of the aircraft design. To cope with the wide range of flight speed, low-Reynolds number airfoils are selected, which possesses low drag characteristics at wide range of angle of attack. Aerodynamic design studies point out that maintaining Reynolds number above 100,000 is a requisite for extended flight operations of the solar-powered mini-UAV. The itemized drag prediction of the UAV design is performed based on the Xflr5 analysis of the UAV configuration. The solar modules and battery systems of the UAV design are represented as equivalent electric models, for the performance simulation of the solar-power propulsion system. Rigorous analyses on the seasonal solar radiation indicate that the capacity of the battery pack should be increased over 50% of the current design to provide continuous operation of the mini-UAV up to 60 days.

Development of seasonal solar radiation estimation models for Dokuz Eylul University campus area for controller of a two-axis solar tracker

In urban locations, it is generally hard to find enough spaces for solar power plants. However, micro-energy generation systems like solar trackers can be located even in crowded cities and becoming a significant technology in solar energy systems. In this study, the measured global solar radiation data for the research area, Tinaztepe/Izmir (38°22'15.3"N 27°12'28.5"E), were logged, then analysed using statistical methods and seasonal daily global solar radiation mathematical models of Tinaztepe/Izmir were developed. The results of these mathematical models give more precise daily average solar radiation value for Tinaztepe/Izmir than previous Izmir global solar radiation models.