Characteristics Of Solar Radiation Research Articles

Adaptive Design of Solar-Powered Energy Systems Based on Daily Clearness State Evolution

The optimal designing of the hybrid energy system (HES) is a challenging task due to the multiple objectives and various uncertainties. Especially for HES, primarily powered by solar energy, the reference solar radiation data directly impact the result of the optimization design. To incorporate the stochastic characteristics of solar radiation into the sizing process, a data-driven stochastic modeling method for solar radiation is proposed. The method involves two layers of stochastic processes that capture the intraday variation and daily evolution of solar radiation. First, the clearness index (CI) is introduced to describe the radiation intensity at different times. Then, the daily clearness state (DCS) is proposed, based on the statistical indicators of the intraday CI. The Markov model is used to describe the stochastic evolutionary characteristics between different DCSs. The probabilistic distribution of the CI under different DCS is obtained based on the diffusion kernel density estimation (DKDE), which is used for the stochastic generation of the CI at various times of the day. Finally, the radiation profile required for the optimal design is obtained by the stochastic generation of the DCS sequences and the intraday clearness index under corresponding states. A case study of an off-grid solar-powered HES is provided to illustrate this methodology.

Development of a simplified cool coating thermal model for predicting street canyon air temperature

Thermal environment within a typical street canyon can be represented by the heat exchange interactions between the microclimate and built-up urban fabric elements, consisting of walls, roofs and pavement surfaces. Morphology of these elements, material thermophysical and surface solar radiation characteristics under the prevalent weather conditions determine heat storage, convective as well as radiative heat exchanges within the street canyon. Predicting these heat transfer mechanisms using thermal model can facilitate assessing air temperature within the street canyon. Therefore, in this study, an easy-to-use resistance capacitance based thermal model is developed and verified using real-scale experimental measurements under the tropical climate of Singapore. Furthermore, the impact of increased solar reflectance of walls and the driveway surfaces (by application of cool coating) on the street canyon air temperature is predicted. Increasing the solar reflectance of wall from 0.5 to 0.8 and driveway from 0.2 to 0.7 can reduce the peak air temperature up to 1.70°C and daily mean air temperature up to 0.85°C as observed in this study. The results of the proposed cool coating thermal model can be used in early-stage design by the designers and planners for assessing the thermal impact of cool coating implementation on the street canyon surfaces under any weather conditions.

Using multilayered neural networks for determining global solar radiation upon tilted surface in Fianarantsoa Madagascar

The knowledge of the local solar radiation characteristics is indispensable in the survey of any system exploiting solar energy in any location. The author is particularly interested by the global solar radiance upon tilted surface per time unit to help operators using solar energy in their work. The target is, among others, helping solar drying operators that need while tuning drying system the knowledge of the global solar radiation that could be received on inclined solar captors in implantation site. The aim of this paper is to use neural network method to search for solar radiation upon a tilted surface. Multilayered neural networks (MNN) trained by gradient back-propagation are used to determine numeric values of monthly means and hourly variations of the global solar radiation upon a titled surface per time unit. The numerical calculations are made with the geographical and meteorological parameters (latitude, longitude and clearness index) of the location of Fianarantsoa, Madagascar.

The theoretical approach of the solar organic Rankine cycle integrated with phase change material for the Hungarian region

AbstractHungary is not only dependent on imports of natural gas and fossil fuels, but Hungary is also the lowest in renewable energy utilization; otherwise, only 11.3% compared to other Central European countries in renewable energy utilization, above 13%. The percentage of renewables in power generation quadrupled from 8% to 16% between 2010 and 2020, with most of the gains coming from the rapid expansion of solar energy, particularly after 2016. Regarding solar energy resource potential, Hungary has a daily total of around 3.2–3.6 kWh/m2 and a yearly total of about 1168–1314 kW.h/m2. This makes it a suitable location for putting solar thermal collectors in conjunction with an organic Rankine cycle (ORC) system. In this study, the authors analyzed solar thermal as a heat source to generate electricity with ORC using two types of working fluids (R245fa and R123). Hungary's weather data for a whole year is used as primary data to look for solar radiation characteristics and ambient temperature. Based on the general solar collector equation, the parabolic tube collector was selected as the best solar collector to utilize solar radiation by producing a maximum heat of around 654.68 kW. Therefore, the evacuated flat plate collector was selected as the solar collector that can produce the maximum outlet temperature of around 372.15 K with a similar size aperture area. Producing a temperature output from the solar collector for heat transfer in the ORC system and from the performance showed that R245fa resulted in better Wnet performance compared with R123 with values of 45.82 and 28.17 kW, respectively, under the same solar collector. Meanwhile, the material suitable for the thermal energy storage‐evaporator combination is organic phase change material using N‐Octacosane, which in the same temperature range (350–375 K) has the smallest ζ(T) value (1.08–1.103), so the mass required for the system is very efficient.

Mechanical Stubble Righting after the Mechanical Harvest of Primary Rice Improves the Grain Yield of Ratooning Rice

Ratooning rice is an essential rice-planting method. However, mechanical harvesting of the primary rice crop, while increasing efficiency, can negatively affect the yield of ratooning rice. Therefore, it is crucial to find ways to improve the grain yield of ratooning rice after the mechanical harvest of the primary rice. A two-year field experiment was conducted; the grain yield of ratooning rice was assessed by stubble righting after mechanical harvesting of primary rice. The study used two popular rice cultivars, YLiangyou911 and Kenliangyou801, as experimental materials. The experimental treatments included three groups: one without righting after rolling rice stubble (CK), another with mechanized righting after rolling rice stubble (T1), and a third one without rolling rice stubble by the machine (T2). The results of the study demonstrate that stubble righting after the mechanical harvest of primary rice (T1) had a substantial impact on the grain yield of ratooning rice. It led to grain yields similar to ratooning rice without mechanical rolling of the rice stubble (T2) and significantly outperformed the treatment without stubble righting after the mechanical harvest of primary rice (CK). The study observed significant effects of the year of the experiment (Y), the treatment applied (T), and the interaction between year and treatment (Y×T) on grain yield. Additionally, the treatment showed a significant influence on the yield components. Specifically, in 2021, the T1 and T2 treatments showed remarkable grain yield increases in YLiangyou911 by 107.41% and 147.97%, respectively, compared to CK. For Kenliangyou801 in 2021, the T1 and T2 treatments also resulted in notable improvements in grain yield by 45.85% and 114.26%, respectively. Similarly, in 2022, the grain yield increased by 6.99% for T1 and 23.87% for T2 in YLiangyou911, and by 77.23% for T1 and 187.13% for T2 in Kenliangyou801, compared to CK. The study also detected enhancements in several aspects, including biomass accumulation, solar radiation and photosynthetic characteristics, antioxidant response and nitrogen metabolism, and bud-regeneration capacity due to T1 and T2 treatments. Furthermore, correlation analysis was conducted to assess the relationship between grain yield and the investigated parameters. In conclusion, stubble righting after the mechanical harvest of primary rice resulted in significantly improved grain yield for ratooning rice. This improvement can be attributed to enhanced biomass accumulation, solar radiation and photosynthetic characteristics, antioxidant response and nitrogen metabolism, and increased bud-regeneration capacity.

An algorithm for the optimal sizing of the PV system for prosumers based on economic indicators and the input data time step

This paper elaborates on an algorithm for finding the optimal size of a photovoltaic (PV) system of a prosumer based on economic factors. The proposed algorithm was developed in the MATLAB programming language and is applied to the Croatian case study considering the Croatian legislation regarding prosumers. The proposed algorithm uses load profile, solar radiation, external temperature and PV module technical characteristics as input data. The algorithm considers the impact of electricity generated from the prosumer’s PV system on the price that the prosumer will receive for the energy exported to the grid as well as achieved savings to calculate the economic indicators — Levelized Cost of Electricity (LCOE), Return on Investment (ROI) and Net Present Value (NPV). Based on the calculated economic indicators LCOE, ROI, and NPV, the optimal size of the PV system is selected. The proposed algorithm was applied to two profiles of prosumers (household and industrial) to demonstrate its usefulness. Furthermore, the impact of the time step of input data on the results has been also investigated. Finally, the proposed algorithm is applied to the input data with 15- and 60-minute time steps for the household prosumer and for the industrial prosumer to obtain the optimal size of the PV system considering the calculated economic indicators.

Comparison and interpretation of solarimetric station data (diffuse solar radiation, UVB radiation, temperature, and relative humidity) from January 2017 to November 2018 in Zacatecas

In this research work, the data from the solarimetric station in Zacatecas during the period from January 2017 to November 2018 are compared and interpreted. The main objective is to analyze the climate and solar radiation characteristics in the region and identify possible correlations between variables. The methodology involved data collection using the solarimetric station and data processing in Excel. Hourly, daily, and monthly averages were calculated for diffuse solar radiation, UVB radiation, temperature, and relative humidity. In addition, graphs were generated using Excel, and two R codes were developed: one to obtain correlations among the analyzed variables and another to visualize the UVB index. This study provides a detailed analysis of climate data and solar radiation patterns in Zacatecas. The obtained results are relevant for the design and implementation of solar energy systems in the region and in areas with similar climatic conditions. In summary, this study compares and interprets the data from the solarimetric station in Zacatecas, aiming to understand the climate and solar radiation characteristics. The conducted analyses contribute to the development of solar energy strategies in Zacatecas and similar regions. solar radiation, climate analysis, Zacatecas.

ARIMA Models in Solar Radiation Forecasting in Different Geographic Locations

The increasing demand for clean energy and the global shift towards renewable sources necessitate reliable solar radiation forecasting for the effective integration of solar energy into the energy system. Reliable solar radiation forecasting has become crucial for the design, planning, and operational management of energy systems, especially in the context of ambitious greenhouse gas emission goals. This paper presents a study on the application of auto-regressive integrated moving average (ARIMA) models for the seasonal forecasting of solar radiation in different climatic conditions. The performance and prediction capacity of ARIMA models are evaluated using data from Jordan and Poland. The essence of ARIMA modeling and analysis of the use of ARIMA models both as a reference model for evaluating other approaches and as a basic forecasting model for forecasting renewable energy generation are presented. The current state of renewable energy source utilization in selected countries and the adopted transition strategies to a more sustainable energy system are investigated. ARIMA models of two time series (for monthly and hourly data) are built for two locations and a forecast is developed. The research findings demonstrate that ARIMA models are suitable for solar radiation forecasting and can contribute to the stable long-term integration of solar energy into countries’ systems. However, it is crucial to develop location-specific models due to the variability of solar radiation characteristics. This study provides insights into the use of ARIMA models for solar radiation forecasting and highlights their potential for supporting the planning and operation of energy systems.

Impact of climate changes on the stability of solar energy: Evidence from observations and reanalysis

Climate change alters the amount and spatiotemporal characteristics of solar radiation at the surface. How this affects the stability of solar energy has not yet been explored on a global scale. In this study, we combine ground observations and ERA5 reanalysis to calculate indicators of resource stability and solar intermittency to find evidence of changes in global solar energy stability over the past 20 years. The calculated results of ERA5 are highly consistent with those based on observations, allowing spatially continuous analysis using ERA5 estimates. We find that solar resource availability is on the rise in most regions, with a maximum decadal increase of up to 30 W/m2 and a rate of about 1–2 W/m2/year. The regions of significant downward trend are concentrated in the Northern Hemisphere. In addition, approximately 85% of the world's land is at risk of increasing intermittency, particularly in India, Central and Northern Africa, China, and the United States, which means that adaptation measures to mitigate intermittency should be coordinated in the context of climate change. This study contributes to understanding the climate impacts on solar energy stability and has practical value for future planning and development of solar energy.

Photovoltaic Solar System for the Residents of Faisalabad: A Cost-Benefit Analysis

The negative environmental impact of fossil fuels is growing, with the accumulation of the elevation financial charge of energy resources required to meet Pakistan's increasing demand for electricity uses. This study was conducted with the objective to determine the economic viability and feasibility of installing photovoltaic (PV) solar energy in Pakistan. It was discovered that Pakistan’s favorable solar radiation characteristics are crucial for improving the viability of installing solar systems. This study was conducted in an industrial city of Pakistan, Faisalabad. Using the CVM technique primary data on solar PV systems installed in the households was collected. The Cost-Benefit Analysis shows that the true financial cost of a PV module will drastically decrease when the charges of energy assets saved are used in generating conventional electricity.

Evaluation of Solar Radiation and Atmospheric Air during Hay Harvesting in Kazakhstan

The study presents a probabilistic and statistical assessment of the actinometric characteristics of solar radiation and temperature and humidity parameters of atmospheric air during the hay harvesting period in Kazakhstan. The following characteristics are considered actinometric: The duration of the sunshine period, the total solar radiation flow, and the average intensity of the total solar radiation per unit area of the horizontal surface with clear skies and average cloud cover. From the parameters of atmospheric air, its temperature, humidity, and moisture absorption capacity are calculated. The authors present their average values, standard deviations, confidence intervals for the average value, coefficients of variation, and probability densities of the distribution of these parameters.

Analysis of temporary variability of the total intensity of solar radiation when assessing energy resources

The results of the analysis of temporary variability of average monthly and annual amounts of solar radiation in Ukraine for the period 2011-2020 are presented. Measurement data were compared with earlier periods and the standard period of 1961-1990. The statistical characteristics of the series of changes in solar radiation have been determined. Comparison of the characteristics of solar radiation with the normative data of SSU NBV .1.1-27-2010 was made. It has been shown that in recent years the annual amounts of direct radiation have increased by 18-23%. The total annual radiation in 2020 increased by 6% according to the period 1961-1990. The analysis of the calculated results of determining hourly values and daily sums of direct and scattered radiation obtained using empirical dependencies of engineering methods is carried out. The efficiency of using the sustainable potential of solar energy depends on the climatic characteristics of this area or region. Inconsistencies in regulations can therefore create a problem where the best places for energy production lack public interest, infrastructure and cost-effective consumption. Depending on the regional climatic conditions of Ukraine, the solar energy potential varies from 1400 MJ/m2 in the western regions to 1950 MJ/m2 in the eastern regions. An important characteristic of solar energy resources is the duration of sunshine. For the conditions of Kyiv, the average monthly value of the actual duration varies from 180 hours in March to 120 hours in November. The possible annual duration of sunshine varies accordingly from 4452 hours (2011) to 4481 hours (2020). The maximum values are observed in June (331 hours) and August (334 hours). In the southern regions of Ukraine, the actual annual duration of sunshine for Odesa conditions varies from 2387 hours (2011) to 2709 hours (2020). The criterion for the expediency of using solar energy is the annual number of clear days of more than 200. The number of clear days is not given in SSU.

Correction to: Analyzing solar radiation characteristics using copula and solar power potential in Peninsular Malaysia

Correction to: Analyzing solar radiation characteristics using copula and solar power potential in Peninsular Malaysia

Natural Capital and Its Services in the Caatinga Phytogeographic Domain

A new millennium has begun, and a new paradigm in exploitation of natural resources to generate products has emerged. In this sense, a model in line with local environmental reality and based on the sustainable development goals (SDG) proposed by the UN is required. The document addresses the suitability of natural capitals in the Caatinga phytogeographic domain (CPD) for generating products, encompassing primary (solar energy and rainfall) and secondary (soil and vegetation) natural resources. These resources have well-defined scarcity (water, soil, and vegetation) and abundance (solar radiation) characteristics. Water is scarce due to uncertain rainfall and frequent droughts. Due to their fragility, soils, when shallow and/or with a low organic matter content, are susceptible to erosion and salinization. In turn, vegetation is scarce due to low potential for biomass production (50% of the area has a biomass production below 2 Mg ha-1. As for solar energy, there is no uncertainty regarding its occurrence in the CPD. Moreover, the region has the highest solar radiation intensities in Brazil, with daily averages ranging from 4.8 to 6.0 Kwh m-2 within a year. Therefore, a new model must be adopted, in which socioeconomic development is based on the potential of local natural resources. In short, abundant resources should be prioritized over scarce ones. Furthermore, exploitation must be democratized and not only in the hands of few privileged individuals

Analyzing solar radiation characteristics using copula and solar power potential in Peninsular Malaysia

Analyzing solar radiation characteristics using copula and solar power potential in Peninsular Malaysia

Corrigendum: Spatial and temporal characteristics of surface solar radiation in China and its influencing factors

Incorrect Funding In the published article, there was an error in the Funding statement. [This work was supported by the National Natural Science Foundation of China (Grant Nos. 42005056, 42005058), the Industry Support Project of University in Gansu Province (Grant Nos. 2020C-34) and the Meteorological scientific research project of Gansu Meteorological Bureau (grant no. ZcZd2022-25).]. The correct Funding statement appears below.FUNDING[This work was supported by the Industry Support Project of University in Gansu Province (Grant Nos. 2020C-34), the National Natural Science Foundation of China (Grant Nos. 42005056, 42005058), and the Meteorological scientific research project of Gansu Meteorological Bureau (grant no. ZcZd2022-25).]

Solar Radiation Characteristics in Shanghai

Based on the solar radiation and meteorological data of five meteorological stations of Baoshan, Chongming, Minhang, Fengxian, and Songjiang meteorological stations in Shanghai from 1982 to 2021, the suitable climatological formula for calculating solar radiation in the Shanghai area was selected as Qg = Qt (a+bS) by applying the climatological calculation principle of total solar radiation. The empirical coefficients for each month of the equations were fitted using the least squares method based on the total radiation and sunshine percentages for each month of the calendar year at five meteorological stations. The results show that the average total radiation of Shanghai in 1982-2021 is 4688.69 MJ/m2, among which the total radiation is the most in May, the least in January and December, and although the noon solar altitude angle is the largest in June and July, the total radiation is less than in May and August due to the new influence of the rainy season sky shading than in May. Due to the small area of the Shanghai region, the difference in total solar radiation between the five stations for each month is insignificant. In terms of the spatial distribution of total solar radiation, the northeastern and coastal areas of Shanghai have the most, and the Baoshan area has relatively less; the northern part has the most in spring; the coastal area has the most in summer; the spatial distribution of total solar radiation in winter and autumn is similar, both having the least in the northeast.

Spatial and temporal characteristics of surface solar radiation in China and its influencing factors

The total-sky direct solar radiation at Earth’s surface (SRS) not only has an important impact on the earth’s climate and ecology, but also is a crucial parameter for solar photovoltaic power. SRS determines whether photovoltaic power plants can be built in the region and directly affects the efficiency of photovoltaic power generation. Therefore, the spatial and temporal distribution characteristics of SRS have a very important guiding significance for the construction of photovoltaic power stations. This study discusses the temporal and spatial characteristics of SRS and its influencing factors in China during 1961–2020 using ERA5 data and the empirical orthogonal function (EOF), rotated empirical orthogonal function (REOF), and ensemble empirical model decomposition (EEMD) methods. Our investigation reveals that the high-value SRS center is located on the southwestern Tibetan Plateau, while the low-value center occurs on the northeastern Yunnan–Guizhou Plateau and in the Sichuan Basin. Seasonal variability in SRS means that maximum values occur uniformly in summer, followed sequentially by spring, autumn, and winter. The spatial distribution of the leading SRS EOF mode exhibits a dipole pattern between the southern Tibetan Plateau and other regions. Combined with the time series, SRS in China underwent an interdecadal transition around the year 2000. The regression analysis shows that this pattern is mainly affected by surface air temperature, total precipitation, relative humidity and cloud cover. The time series evolution of SRS primarily reflects the interannual variability in annual-mean and four seasons; the variance contributions of decadal variability and secular trend are minor through the EEMD. The REOF separates Chinese SRS into 11 central regions, the top 5 being the western Tibetan Plateau, western Northwest China, the eastern Tibetan Plateau, northern Xinjiang, and North China. The relationship between SRS and meteorological parameters shows that SRS is positively correlated with surface air temperature and wind speed but negatively correlated with total precipitation, relative humidity, low and total cloud cover, and aerosol concentrations.

Optimization of feedstock and insulating strategies to enhance biogas production of solar-assisted biodigester system

Assisted by solar greenhouse, the temperature of the digestion liquid can be increased by solar radiation to promote the biogas production rate in cold climate. Due to the dynamic characteristics of solar radiation, air temperature and other variable parameters jointly affect the digestion process. A novel dynamic biogas production prediction model for solar-assisted biogas digestion is developed in this study. The model integrates soil heat transfer, feeding process and covering/uncovering of greenhouse insulation quilt, and coupled with biogas anaerobic digestion kinetic model. After validated by experimental results of an actual biogas project in rural area of Xuzhou, China, the feedstock process and insulating strategies for biogas plants are optimized based on prediction model. The results show a significant increase of 55% average volumetric biogas production rate could be achieved, it indicates that optimizing operation strategy of solar assisted biogas plants has a great potential for enhancing gas production in cold winter climates with sufficient solar radiation resources, which can promote biogas applications in rural North China. The models could be used for predicting biogas production rate of passive solar-assisted biogas digester, and could also help for energy savings and renewable energy utilization in China and other countries.

Piping formation and distribution in the semi-arid Northern Negev environment: A new conceptual model

Soil piping is a complex erosion process caused by subsurface water flow. We studied the effects of soil cracks and hillslope aspects on piping development and spatial distribution, and introduce a conceptual model of piping development in semi-arid environments. The model addresses factors that substantially influence piping formation: rainfall regime, solar radiation, soil properties, and geospatial characteristics extracted from unmanned aerial vehicle scans. To provide evidence for the ideas presented in the conceptual model, 322 pipes were sampled and measured in the field. Soil texture, sodium, calcium magnesium and organic matter contents, and sodium adsorption ratio (SAR) were analyzed using standard laboratory methods. Our results demonstrate the profound effects of subsurface soil properties on piping-formation processes but do not fully explain substantial differences in spatial distribution between north- and south-facing slopes. However, the synergy of soil properties, rainfall data, and simulated differences in heat flux between aspects led to the development of a landscape with considerably more pipes in the south-facing slopes.