Solar Irradiance Variations Research Articles

Design and PIL Implementation of Fuzzy Logic-based MPPT Control for Symmetrical Multilevel Boost Converter

This paper aims to introduce a fuzzy logic adaptive MPPT controller to control a symmetrical multilevel converter in a standalone PV system. The system is evaluated under fixed and variable solar radiation with 15 V as the input voltage 60 V as the required output voltage and 50 kHz as the switching frequency. Results prove that by using the controller, the system successfully tracks the MPPT point for constant and variable radiation without oscillation around the maximum power point. In addition, the overshoot and time response is reduced while the voltage ripples are eliminated. The proposed controller is verified through practical implementation in Arduino mega board to test the accuracy of results. The practical finding via a processor in the loop test validates the simulation results.

Nonlinear Control of Photovoltaic (PV) Solar-Powered Centrifugal Pump for Irrigation System: A Case Study of Fadak Farm in Karbala

Abstract In both the agricultural and industrial sectors, pumping water is essential. Due to its arid climate, our Saharan area has a substantial solar energy resource, making constructing a PV solar irrigation system possible. Given solar resources' unpredictable and intermittent nature, it is imperative to set up a system that permits optimal usage. This study aims to design and simulate a solar pumping system's effective nonlinear direct torque command. A solar generator provides an asynchronous three-phase machine coupled to a centrifugal pump as part of the system. MPPT monitors the boost converter via duty cycle. The solar generator's functioning at full power will be ensured. The first uses PSO in the MPPT system to supply the motor pump with three phases of power. The second one employs direct torque command (DTC) to regulate the operation of a centrifugal pump coupled with an induction machine. More advancements will be made to the DTC scenario. The proposed mathematical model of the solar irrigation system was simulated using a MATLAB simulation environment, adopting accurate data provided by Fadak Farm. The maximum power extracted from PV tends to peak at 280 Wp with the assistance of particle swarm optimization that energizes the use of the centrifugal pump for the proposed irrigation system. It is evident from numerical simulation results based on accurate input data that the power extracted from PV solar is positively affected by solar radiation and surface temperature variations. It is clear from simulation results that the speed of three–phase I.M motor converges to 22.5 rad/sec, and water flow pumping by centrifugal is decreased and increased, converging to 7.5 *10-8 m/s with the variation of solar irradiance.

Correlation analysis of the long-term interplay of cosmic rays, solar activity, and solar irradiance

Abstract This study presents a comprehensive analysis of the interplay between solar irradiance variability, solar activity, and cosmic rays over an extensive period from 1950 to 2023, well beyond the scope of previous research that focused on fewer solar cycles. Besides, using a robust dataset, we investigated the correlation between solar activity, represented by sunspot numbers, and the total solar irradiance, alongside the influence of cosmic rays. In this respect, our methodology incorporated sophisticated statistical techniques, including correlation analysis and linear regression, in order to elucidate the complex relationships among these variables. We identified a strong positive correlation between solar activity and total solar irradiance r ≈ + 0.95 , together with a significant anti-correlation between solar activity and cosmic rays r ≈ − 0.72 as well as cosmic rays and total solar irradiance r ≈ − 0.67 . As a consequence, the results of this study offer new insights into the long-term solar influence on climate through cosmic rays, enhancing our understanding of the Sun-Earth dynamic over prolonged periods. Likewise, the extended time series and the analytical framework developed in this study pave the way for further research into related phenomena, including the effects of cloud cover and potential links between cosmic rays and climate change.

Enhanced MPPT Based on Zebra Optimization Algorithm for Control of a Partially Shaded Photovoltaic System

Objective: The objective of this paper is to adapt the Zebra Optimization Algorithm (ZOA) to track the Global Maximum Power Point (GMPP) of a PV system when subjected to partial shading conditions. Theoretical Framework: Photovoltaic (PV) systems are increasingly being used due to their clean nature and low maintenance cost. However, solar cells exhibit a nonlinear relationship between current and voltage, which necessitates the use of Maximum Power Point Tracking (MPPT) algorithms to ensure the system operates at its full potential. Bypass diodes are integrated into PV modules to protect solar cells from damage during partial shading, but this leads to a distorted multi-peak Power-Voltage (P-V) curve. This distortion presents a challenge for algorithms to distinguish between Global Maximum Power Point (GMPP) and Local Maximum Power Points (LMPPs). Method: The Zebra Optimization Algorithm (ZOA) is applied to track the GMPP of a PV system under partial shading conditions. Simulations were conducted using the MATLAB/Simulink platform to evaluate the algorithm’s performance. The focus was on ensuring fast and accurate tracking of the GMPPT under rapid changes in solar irradiance levels. Results and Discussion: Simulation results demonstrated that the ZOA-based MPPT algorithm effectively tracked the GMPPT of the PV system, even under rapid variations in solar irradiance. The algorithm proved its accuracy and speed in distinguishing the GMPP from LMPPs, addressing the challenges posed by the distorted P-V curve. Research Implications: The successful application of the ZOA for tracking the GMPP in partial shading conditions offers a significant improvement for PV systems. This can lead to enhanced efficiency in energy production and more reliable performance in real-world scenarios, where shading and other environmental factors frequently affect solar panels. Originality/Value: This study introduces the adaptation of the Zebra Optimization Algorithm (ZOA) in MPPT for PV systems, addressing the issue of distinguishing between GMPP and LMPPs under partial shading. The approach demonstrates both innovation and practical value in improving the efficiency of PV systems in challenging environmental conditions.

Thermal-hydraulic transient performance and dynamic characterization analysis of direct steam generation for parabolic trough solar collectors

Parabolic trough solar direct-steam-generation (PTC-DSG) technology is a low-carbon technology by combining clean energy with green energy carriers. However, abrupt variations in solar radiation (I) due to weather changes can significantly affect the DSG performance and stable operation. In this work, PTC-DSG system's optical-thermal-flow-pattern transient coupling model is developed based on the Separated Flow model, Finite Volume method and Lagrangian method. The dynamic response of the loop's transient flow law and heat transfer performance under I step-variation are analyzed, and the correlation between the DSG system's transient flow characteristics and the multiple perturbation factors is discussed. The results reveal that adding (reducing) 12.5 % and 37.5 % of I shortens (lengthens) the evaporation phase by 7.2 % and 16.5 % (10.7 % and 16 %). The superheated zone has the greatest influence on the transient response characteristics and instability relative to the preheated and evaporated zones under various step-variations, and the heat transfer recovery still needs longer time after flow state is re-stabilized. Under I step-variation, adding mass flow can effectively shorten the superheat phase but not the response time, and the system instability range increases; Increasing inlet temperature (Tin) can augments the superheat zone, but effectively shorten the response time and regulate and improve the outlet steam quality; Raising inlet pressure not only reduces the evaporation phase, which is most favorable for heat transfer, but also requires longer re-stabilization time and increases the probability of stratified flow, which should be paid more attention.

Towards Sustainable Energy Solutions: Evaluating the Impact of Floating PV Systems in Reducing Water Evaporation and Enhancing Energy Production in Northern Cyprus

Floating photovoltaic systems (FPVSs) are gaining popularity, especially in countries with high population density and abundant solar energy resources. FPVSs provide a variety of advantages, particularly in situations where land is limited. Therefore, the main objective of the study is to evaluate the solar energy potential and investigate the techno-economic perspective of FPVSs at 15 water reservoirs in Northern Cyprus for the first time. Due to the solar radiation variations, solar power generation is uncertain; therefore, precise characterization is required to manage the grid effectively. In this paper, four distribution functions (Johnson SB, pert, Phased Bi-Weibull, and Kumaraswamy) are newly introduced to analyze the characteristics of solar irradiation, expressed by global horizontal irradiation (GHI), at the selected sites. These distribution functions are compared with common distribution functions to assess their suitability. The results demonstrated that the proposed distribution functions, with the exception of Phased Bi-Weibull, outperform the common distribution regarding fitting GHI distribution. Moreover, this work aims to evaluate the effects of floating photovoltaic systems on water evaporation rates at 15 reservoirs. To this aim, five methods were used to estimate the rate of water evaporation based on weather data. Different scenarios of covering the reservoir’s surface with an FPVS were studied and discussed. The findings showed that annual savings at 100% coverage can reach 6.21 × 105 m3 compared to 0 m3 without PV panels. Finally, technical and economic assessment of FPVSs with various scales, floating assemblies, and PV technologies was conducted to determine the optimal system. The results revealed that a floating structure (North orientation-tilt 6°) and bifacial panels produced the maximum performance for the proposed FPVSs at the selected sites. Consequently, it is observed that the percentage of reduction in electricity production from fossil fuel can be varied from 10.19% to 47.21% at 75% FPV occupancy.

Double-Shell Encapsulation of Lead-Free Tin Halide Perovskite for Self-Powered Smart Windows.

Luminescent solar concentrators (LSC) have the potential application in building integrated photovoltaic (BIPV). 0D tin-based perovskites are a promising embedding phosphor in LSC due to the large Stokes shift and high photoluminescence quantum yield. But the instability and uncontrollable crystal growth are severe limiting their successful utilization in device fabrication. To tackle these issues, double-shell encapsulated configurations are presented, soft ligands of hypophosphorous acid and hard-shell of hollow mesoporous silica are simultaneously suppressing the oxidation of Sn2+ and restricting crystal growth within nano-matrix. The stable phosphor is subsequently embedded into LSC for harvesting solar energy and the resulting output power efficiently drives the combined electrochromic glass under natural light. These fabricated devices also offer the self-adaptable switch on/off functionality to regulate light absorption with variable solar irradiation intensity in real time. This approach is anticipated to open new avenues for utilizing lead-free perovskite nanomaterials in self-powered smart windows for BIPV.

Combining observations and simulations to investigate the small-scale variability of surface solar irradiance under continental cumulus clouds

Abstract. The amount of solar radiation reaching the Earth surface (surface solar irradiance, SSI) is critical for a variety of applications, ranging from surface–atmosphere interactions to solar energy. SSI is characterized by a large spatiotemporal variability, in particular in the presence of cumulus clouds. This results in complex spatial patterns of shadows and sunlight directly related to clouds' geometry and physical properties. Although key in many respects, the instantaneous spatial distribution of SSI remains largely unexplored. Here, we use unique observations from a dense network of pyranometers deployed during the HOPE field campaign to investigate the SSI spatial distribution. For cumulus scenes, bimodal distributions are found, with one mode corresponding to cloud shadows and the other to sunlit areas with enhanced SSI exceeding clear-sky values. Combining large-eddy simulations of cumulus clouds with Monte Carlo ray tracing, we demonstrate the capability of advanced numerical tools to reproduce the observed distributions and quantify the impact of cloud geometrical and physical properties on both modes. In particular, cloud cover strongly modulates their amplitudes, in addition to their position and width, which are also sensitive to cloud height, geometrical depth, and liquid water content. Combining observations and simulations, we also explore sampling strategies to estimate the SSI spatial distribution with a limited number of sensors, suggesting that 10 pyranometers integrated over 10 min can capture most details of the full distribution. Such a strategy could be used for future campaigns to further investigate SSI distributions and their impact on land–atmosphere exchanges or photovoltaic farm management.

Design, and dynamic evaluation of a novel photovoltaic pumping system emulation with DS1104 hardware setup: Towards innovative in green energy systems.

Diesel engines (DEs) commonly power pumps used in agricultural and grassland irrigation. However, relying on unpredictable and costly fuel sources for DEs pose's challenges related to availability, reliability, maintenance, and lifespan. Addressing these environmental concerns, this study introduces an emulation approach for photovoltaic (PV) water pumping (WP) systems. Emulation offers a promising alternative due to financial constraints, spatial limitations, and climate dependency in full-scale systems. The proposed setup includes three key elements: a PV system emulator employing back converter control to replicate PV panel characteristics, a boost converter with an MPPT algorithm for efficient power tracking across diverse conditions, and a motor pump (MP) emulator integrating an induction motor connected to a DC generator to simulate water pump behaviors. Precise induction motor control is achieved through a controlled inverter. This work innovatively combines PV and WP emulation while optimizing system dynamics, aiming to develop a comprehensive emulator and evaluate an enhanced control algorithm. An optimized scalar control strategy regulates the water MP, demonstrated through MATLAB/Simulink simulations that highlight superior performance and responsiveness to solar irradiation variations compared to conventional MPPT techniques. Experimental validation using the dSPACE control desk DS1104 confirms the emulator's ability to faithfully reproduce genuine solar panel characteristics.

Quantification and assessment of the atmospheric boundary layer height measured during the AWAKEN experiment by a scanning LiDAR

The atmospheric boundary layer (ABL) height plays a key role in many atmospheric processes as one of the dominant flow length scales. However, a systematic quantification of the ABL height over the entire range of scales (i.e., with periods ranging from one minute to one year) is still lacking in literature. In this work, the ABL height is quantified based on high-resolution measurements collected by a scanning pulsed Doppler LiDAR during the recent American WAKE experimeNt (AWAKEN) campaign. The high availability of ABL height estimates (≈2200 collected over one year and each of them based on 10-min averaged statistics) allows to robustly assess five different ABL height models, i.e., one for convective thermal conditions and four for stable conditions. Thermal condition is quantified by a stability parameter spanning three orders of magnitude and probed by near-ground 3D sonic anemometry. The free-atmosphere stability, quantified by the Brunt–Väisälä frequency, is both calculated from simultaneous radiosonde measurements and obtained from the best fit of two of the chosen ABL height models. Good agreement is found between the data and three of the chosen models, quantified by mean absolute errors on the ABL height between 281 and 585 m. Furthermore, the seasonal variability of the convective ABL height model parameters (−15% to +23% with respect to the year baseline) agrees with the variability of buoyancy-generated turbulence caused by the variation in solar radiation throughout the year.

Double pass solar air heater with aerofoil and bio-inspired fins: A numerical analysis of thermohydraulic performance

In the present study, a numerical flow analysis is performed on a double pass solar air heater (DPSAH) with a bottom plate surface roughened using aerofoil fins to study its thermohydraulic performance. The experimentally validated DPSAH model was studied considering factors like different fin shapes, diurnal variation of solar radiation, absorber plate material, and the flow conditions at different relative height ratios (h/H) between 0.17 and 0.50 and fin length ratio (l/H) of 0.29. Using the RNG k-ε turbulence model, the relative Nusselt number (Nu/Nus), relative friction factor (f/fs), and thermohydraulic performance factor (THPF) were found for Reynolds number between 3000 and 21000 with an increment of 3000. The maximum enhancements of 4.23 and 2.51 times were achieved in the Nu/Nus and THPF values, respectively, for a Re value of 3000 in a 2-row setup with h/H of 0.50. The DPSAH with bio-inspired fins performed better than optimized aerofoil fins for majority of the tested range even with similar increase in effective heat transfer area. The values predicted using correlations developed in this study and numerically obtained values of the Nusselt number and friction factor matched closely with an extreme deviation of 5 % in f values.

Century‐Long Variations in Surface Incident Solar Radiation Over Japan——Characterized by Observations and Reanalyses

ABSTRACTSurface incident solar radiation (Rs) is of great importance in determining the energy balance in the Earth system. In this study, we use century‐long homogenized observations over Japan to constrain five 20th century reanalyses to explore their performance in reproducing Rs variation on different time scales (high‐frequency components [HFCs], for signals with cycles less than 10 years; low‐frequency components [LFCs], for signals with cycles more than 10 years) by ensemble empirical mode decomposition (EEMD) method and to quantify the impact factors on the Rs estimations by the sum of tree (SOT) model. It is found that ERA20C, ERA20CM and CERA20C overestimated Rs by 0.48–1.49 W/m−2, while 20CRv2c and 20CRv3 underestimated Rs by −0.63 and −1.18 W/m−2, respectively for 1931–2010. Poor correlation coefficient (R) was found to be 0.10 for ERA20CM and 0.22 for 20CRv2c. 20CRv2c failed for 1931–1960 but improved considerably for 1961–2010. 20CRv3 uses an upgraded model and assimilates more observations compared with its predecessor 20CRv2c; however, only the original components and HFCs in Rs were improved, with nearly no improvement in the LFCs. In general, CERA20C Rs, with small biases and higher R of 0.73 for original signals, 0.83 for HFCs and LFCs, is superior to other reanalyses. No obvious trend in clear sky Rs demonstrated that reanalysed Rs are insensitive to the aerosol forcings. Therefore, cloud cover and water vapour maybe the main factors influenced reanalysed Rs. Most of time, Rs is more sensitive to cloud cover than vapour pressure for all reanalyses except original signals (with contribution ratio of 0.29 for cloud cover and 0.71 for vapour pressure) and LFCs (with contribution ratio of 0.41 for cloud cover and 0.59 for vapour pressure) in CERA20C, and original signals (with contribution ratio of 0.37 for cloud cover and 0.63 for vapour pressure) in ERA20C. This work pointed out that aerosol related processes such as aerosol forcings or aerosol radiative effect in reanalyses should be improved in the future, which will ultimately improve the interaction between aerosol and cloud in Rs simulations.

Variability of solar UV radiation in the northern mountains of the Czech Republic, 2020–2021

Solar ultraviolet (UV) radiation has a crucial role in many atmospheric processes and a huge impact on living organisms. Its main positive effect is the synthesis of vitamin D, but it also causes problems such as sunburn, skin cancer or eye cataracts. In the mountains, high doses of UV frequently occur due to a specific combination of atmospheric and geographical factors such as a high ground reflection as a consequence of a large number of days with snow cover, or a lower concentration of atmospheric pollutants in comparison to lowland urban regions. This study used measurements of erythemal UV radiation from two high altitude areas: the Hrubý Jeseník Mountains (Vysoká hole meteorological station, 1 464 m a.s.l.) and the Giant Mountains (Luční bouda meteorological station, 1 413 m a.s.l.) in the Czech Republic, during 2020 and 2021. We evaluated the daily and monthly changes in erythemal dose and UV index. The maximum daily dose of 5.0 kJ.m-2 (8.9 of UV index) was measured on 28 June 2020 at Vysoká hole. The maximal UV index of 10.1 was observed at Luční bouda on 5 July 2020, while the maximum daily dose of 4.9 kJ.m-2 occurred on 14 June 2021. The main factors that caused changes in solar UV radiation were the amount of cloud cover as well as the total ozone column.

A novel heating system of solar-assisted enhanced jet enthalpy air source heat pump for cold regions

Solar energy and air source heat pumps are common heat sources for clean heating, but at lower ambient temperatures, the performance of solar energy and air source heat pumps will decline significantly, which can be ameliorated by integrating the two heat sources. However, the range of solar radiation and ambient temperature variation is very wide, and the existing integration methods cannot guarantee that they are optimal over a wide range. Therefore, this paper proposes a novel integration method of solar energy and jet enthalpy air source heat pump suitable for cold regions, where solar energy is used to heat the refrigerant in the jet branch to increase the flow rate of the jet branch, which enhances the effect of jet enthalpy. Under varying outdoor temperatures and solar radiations, the performances of the new integrated system and the traditional integrated systems are compared by simulation method. The results show that within the scope of this study (outdoor temperatures ranging from −30 °C to 10 °C, and radiations from 200 to 800 W/m2), the heat output and coefficient of performance of the new system are higher than those of the existing integrated systems. At an outdoor temperature of −30 °C and a radiation of 500 W/m2, the new system increases heat output by 45.8 % and coefficient of performance by 22.5 % compared with the existing two systems. This research can promote the application of solar energy and air source heat pump heating in cold regions.

Latitudinal responses of litter decomposition to solar radiation.

Photodegradation driven by solar radiation has been confirmed as an important driving factor for litter decomposition. However, previous single-site studies could not quantify the relative contribution of variation in solar radiation to litter decomposition. To address it, we conducted a field experiment in Heshan National Field Research Station of Forest Ecosystem, Guangdong (Heshan Station, south subtropical climate), Jigongshan Ecological Research Station, Xinyang, Henan (Jigongshan Station, north subtropical climate) and Daqinggou Ecological Research Station, Institute of Applied Ecology, Chinese Academy of Sciences (Daqinggou Station, temperate climate) at intervals of 10 degrees. We examined litter decomposition of Populus davidiana and Larix olgensis, two species with significant differences in initial litter quality through an in-situ spectral-attenuation experiment. Treatments included full-spectrum, No-UV-B (attenuating UV-B radiation <315 nm) and No-UV & Blue (attenuating all UV and blue wavelengths <500 nm). After nearly 1-year decomposition, litter dry mass remaining of P. davidiana and L. olgensis under full-spectrum treatment was lowest at Heshan (30.2% and 36.3%), and highest at Jigongshan (37.3% and 45.8%). Among all sites, litter dry mass remaining was lowest under the full-spectrum, and lower than that of No-UV-B and No-UV & blue. UV and blue light significantly increased litter mass loss of P. davidiana and L. olgensis, with contributions of 59.7% and 57.0% (Heshan), 46.4% and 42.1% (Jigongshan), and 39.0% and 45.9% (Daqinggou), respectively. The contribution of UV-A and blue light (315-500 nm) was greater than UV-B (280-315 nm); the cumulative irradiance, soil temperature and moisture were the main driving factors for litter photodegradation.

Evaluating solar ramp rate correlations by simple radiation and wind measurements

The stability of photovoltaic (PV) energy output is critical to power supply and is a crucial factor for the reliability of power supply systems but is significantly influenced by the unpredictable shading caused by clouds. Assessing the variability of solar radiation across a spatially dispersed PV fleet can be challenging, as it is usually lower than that taken by routine measurements at a singular, localized point. This study refines the previously developed spatial radiation variability model by depicting the attenuation mode of solar irradiance correlation across spatial distances and considering the differences in the along-wind and cross-wind directions under various weather and solar radiation conditions. These modes are further connected to the variables that properly depict the weather conditions and are straightforward to measure. The data being adopted in developing and validating the model are collected from 17 pyranometers over a 0.56 km2 area for about half a year with a 1-s resolution. The model's performance, with a percentage root-mean-square error that surpasses isotropic models by 2.42 %–10.6 % for solar ramp intervals ranging from 5 to 240 s, underscores its accuracy and potential for optimizing the integration of PV fleets into power grids.

Variation of surface solar radiation components from 2016 to 2020 in China: Perspective from geostationary satellite observation with a high spatiotemporal resolution

At present, traditional satellite datasets still grapple with inadequacies in terms of capturing solar radiation with fine spatiotemporal granularity. This study utilizes the high spatiotemporal resolution of CARE data, which is developed based on geostationary satellite observations, and employs multivariate analysis techniques to conduct an in-depth investigation into the multidimensional spatiotemporal variations of different types of solar radiation across various regions in China from 2016 to 2020. In addition, the potential of solar energy resources was also assessed using cluster analysis method. The results revealed an upward trend in different components of solar radiation across most of China, with shortwave radiation exhibiting a significantly negative correlation with PM2.5 concentrations (R = −0.91, p < 0.05). This finding suggests that the increase in SWR may be attributed to the effective implementation of China's Air Pollution Prevention and Control Action Plan. It suggests that China's endeavors to mitigate air pollution have not only resulted in improvements in national air quality but have also had an indirect positive effect on enhancing the potential for photovoltaic power generation. The assessment of solar energy resources potential indicated, with 99 % statistical confidence, that western China constitutes the core region for solar energy resources development, whereas northeastern and southeastern regions face certain constraints in solar energy resources utilization. Furthermore, we examined the specific influence of atmospheric circulation patterns on solar energy resources, uncovering that the El Niño phenomenon, by altering cloud distribution and variability, indirectly affects solar radiation intensity in specific regions. This study aids in understanding China's solar radiation variations, crucial for shaping effective energy policies towards carbon neutrality.

Exploring the Potential of Solar Energy for Electricity and Heat Production in Azerbaijan

Taking use of Azerbaijan's advantageous geographic and climatic characteristics, this thesis investigates the potential of solar energy for the generation of heat and electricity in the nation. In order to assess the viability of solar photovoltaic (PV) systems for electricity production and solar thermal technologies for heating, it evaluates important places with significant sun insolation. The report points up difficulties including geographical variations in solar radiation and infrastructural constraints, but it also implies that these obstacles may be addressed by technical innovation and strategic planning. Azerbaijan's energy security and sustainability may be enhanced by implementing hybrid systems, supporting policies, and infrastructural enhancements that optimize the use of solar energy.

Trend of surface solar radiation over China in relation to changing synoptic patterns

A comprehensive understanding of the relationship between atmospheric circulations and variations in surface solar radiation (SSR) is important for effectively utilizing solar resources and assessing climate change impacts. Here, we identify four synoptic patterns by T-mode principal component analysis method during 1980–2020 associated with the spatio-temporal variations of SSR in China, including geopotential height anomalies of west-high-east-low (Type 1), north-high-south-low (Type 2), east-low-west-high (Type 3), and north-low-south-high (Type 4). For the whole summer, there are more days of Type 1 and Type 2, accounting for 28.74 % and 28.58 % respectively. In particular, Type 1 experiences positive anomalies in cloud cover, water vapor and significantly reduced SSR reaching the Earth’s surface. Type 2 pattern is characterized with low (high) anomalies of SSR over the Yangtze River Basin (Northeast China). And the north of the Yangtze River Basin is controlled by a northerly dry and cold airflow, leading to low cloudiness and precipitation with increased SSR reaching the ground in Type 3. Type 4 pattern exhibits a negative (positive) SSR anomalies in the Yellow River Basin (the Yangtze River Basin and Northeast China). Notably, the reduction of summer SSR in China since the 1980s is largely explained by the long-term changes of Type 2 and Type 4 synoptic patterns. These findings improve the understanding of the relationship between atmospheric circulations and SSR, and provide a scientific basis for policy planning of solar energy and dual-carbon targets in China.

CloudSwinNet: A hybrid CNN-transformer framework for ground-based cloud images fine-grained segmentation

Solar irradiance is the main factor affecting the output of a photovoltaic (PV) power station. The dominant role of ground-based clouds on the variation of direct solar radiation in the whole sky. Ground-based cloud segmentation plays a crucial role in photovoltaic power generation prediction. Despite advancements, current cloud segmentation methods fail to meet the requirements of this application. While convolutional neural networks demonstrate impressive segmentation capabilities in ground-based cloud segmentation tasks, their inherent limitations hinder further performance enhancement. Hence, this paper introduces CloudSwinNet, a hybrid CNN-Transformer framework for ground-based cloud images fine-grained segmentation. CloudSwinNet leverages concepts from convolutional neural networks, including stepwise downsampling, local convolution, and skip connections. To further explore the fine-grained features in the ground-based cloud images, we incorporates the Fine-grained Feature Fusion Module (Fg-FFM) in encoder structure, while the jump connection structure integrates the GloRe spatial graph inference module. These additions enable comprehensive learning of multi-scale and long-range dependencies. We conducted extensive experiments on the fine-grained ground-based cloud dataset, demonstrating that CloudSwinNet outperforms six semantic segmentation networks in both qualitative and quantitative evaluations. The results of ablation experiments prove the effectiveness of the module introduced in this paper.