Fluctuations In Solar Radiation Research Articles

Temporal Evolution, Oscillation and Coherence Characteristics Analysis of Global Solar Radiation Distribution in Major Cities in China’s Solar-Energy-Available Region Based on Continuous Wavelet Transform

The majority of the energy required for human survival is derived either directly or indirectly from solar radiation, thus it is important to investigate the periodic fluctuations in global solar radiation over time. In this study, six cities—Harbin, Shenyang, Beijing, Shanghai, Wuhan, and Guangzhou—located in the utilizable areas of solar energy in China, were selected, and the periodicity of the daily global solar radiation of these six cities with time were investigated by means of wavelet power spectrum analysis. Furthermore, Harbin, which has the lowest monthly average of global solar radiation in the cold of winter, was selected to explore the temporal evolution relationship between global solar radiation and other meteorological factors, and air quality factors by wavelet coherence analysis. Among the meteorological factors, the correlation between global solar radiation and sunshine duration exhibits the highest level of consistency. Global solar radiation demonstrates a positive association with atmospheric temperature/wind speed/precipitation over the annual cycle. Conversely, it displays a negative correlation with atmospheric pressure during this time frame. Additionally, on shorter timescales, global solar radiation is negatively correlated with air humidity and precipitation. Among air quality factors, the relationship between global solar radiation and CO/NO2/O3/PM2.5/PM10/SO2 primarily manifests in the broader annual cycle time scale. Within this context, global solar radiation shows a positive correlation with O3, while displaying negative associations with the other five air quality indicators. These findings contribute to urban environmental planning and the effective management and utilization of solar radiation, thereby providing valuable insights to guide the future development of cross-regional comprehensive energy utilization projects under diverse climatic and geographical conditions. Additionally, they serve as a reference for subsequent research aimed at enhancing the accuracy of global solar radiation prediction models.

Particulate/gaseous pollutants and solar radiation fluctuations over Bhubaneswar amidst two special events: Diwali and solar eclipse

This work presents short-term investigations to assess variations in PM2.5, PM10, SO2, NO2, O3, CO, BC, light NMHCs (ethane, ethylene, propane, propylene, and acetylene) and solar radiation at Bhubaneswar, during two special events in consecutive years: Diwali (2021 & 2022) and partial solar eclipse (2022). During 2022, PM levels were affected by meteorology and simultaneous occurrence of solar eclipse on the day after Diwali day (D-Day). Interesting atmospheric chemistry was observed due to emissions from crackers during Diwali night influencing solar flux on post-D-day, which in turn had an impact on the pollutant levels. NO2, SO2, CO, and O3 were below prescribed safety limits for both years, however, BC and NMHC concentrations were high on D-day due to contribution from crackers, biomass, and jute burning as a ritual in the state. Also, a sharp increase in CO and NO2 concentrations was noticed exactly during the most intense phase of eclipse due to cooling of atmosphere. The oxidant levels reduced as a result of sudden drop in the solar intensity during the event. In comparison to alkanes, the alkenes exhibited high O3-forming potential (97–98%) during both the years. However, in 2022 the photo-oxidation process of alkenes was affected due to reduced solar flux on D-day. Further O3 concentration on 2022 D-Day was comparatively lower (10%) than 2021 D-day with a reduction in surface O3 concentration (43.50%) almost 2 h after the eclipse. Thus, O3 chemistry during Diwali can be attributed to both natural phenomena and man-made activities.

Data-based investigation of the effects of canopy structure and shadows on chlorophyll fluorescence in a deciduous oak forest

Abstract. Data from satellite, aircraft, drone, and ground-based measurements have already shown that canopy-scale sun-induced chlorophyll fluorescence (SIF) is tightly related to photosynthesis, which is linked to vegetation carbon assimilation. However, our ability to effectively use those findings are hindered by confounding factors, including canopy structure, fluctuations in solar radiation, and sun–canopy geometry that highly affect the SIF signal. Thus, disentangling these factors has become paramount in order to use SIF for monitoring vegetation functioning at the canopy scale and beyond. Active chlorophyll fluorescence measurements (FyieldLIF), which directly measures the apparent fluorescence yield, have been widely used to detect physiological variation of the vegetation at the leaf scale. Recently, the measurement of FyieldLIF has become feasible at the canopy scale, opening up new opportunities to decouple structural, biophysical, and physiological components of SIF at the canopy scale. In this study, based on top-of-canopy measurements above a mature deciduous forest, reflectance (R), SIF, SIF normalized by incoming photosynthetically active radiation (SIFy), FyieldLIF, and the ratio between SIFy and FyieldLIF (named Φk) were used to investigate the effects of canopy structure and shadows on the diurnal and seasonal dynamics of SIF. Further, random forest (RF) models were also used to not only predict FyieldLIF and Φk, but also provide an interpretation framework by considering additional variables, including the R in the blue, red, green, red-edge, and near-infrared bands; SIF; SIFy; and solar zenith angle (SZA) and solar azimuth angle (SAA). Results revealed that the SIF signal is highly affected by the canopy structure and sun–canopy geometry effects compared to FyieldLIF. This was evidenced by the weak correlations obtained between SIFy and FyieldLIF at the diurnal timescale. Furthermore, the daily mean SIF‾y captured the seasonal dynamics of daily mean F‾yieldLIF and explained 58 % of its variability. The findings also revealed that reflectance in the near-infrared (R-NIR) and the NIRv (the product of R-NIR and normalized difference vegetation index (NDVI)) are good proxies of Φk at the diurnal timescale, while their correlations with Φk decrease at the seasonal timescale. With FyieldLIF and Φk as outputs and the abovementioned variables as predictors, this study also showed that the RF models can explain between 86 % and 90 % of FyieldLIF, as well as 60 % and 70 % of Φk variations under clear-sky conditions. In addition, the predictor importance estimates for FyieldLIF RF models revealed that R at 410, 665, 740, and 830 nm; SIF; SIFy; SZA; and SAA emerged as the most useful and influential factors for predicting FyieldLIF, while R at 410, 665, 705, and 740 nm; SZA; and SAA are crucial for predicting Φk. This study highlighted the complexity of interpreting diurnal and seasonal dynamics of SIF in forest canopies. These dynamics are highly dependent on the complex interactions between the structure of the canopy, the vegetation biochemical properties, the illumination angles (SZA and SAA), and the light conditions (ratio of diffuse to direct solar radiation). However, such measurements are necessary to better separate the variability in SIF attributable to radiation and measurement conditions from the subtler variability attributable to plant physiological processes.

Cycles of solar ultraviolet radiation favor periodic expansions of cyanobacterial blooms in global lakes

Global warming and eutrophication are known to increase the prevalence of cyanobacterial blooms, posing a severe threat to the ecological stability and sustainability of water bodies. The long-term (over an annual time frame) effect of UV radiation on cyanobacterial blooms in lakes are rarely discussed though the substantial effects of high-intensity UV radiation on the growth inhibition of marine phytoplankton were studied. Here, we employed the datasets on surface solar UV radiation, nitrogen and phosphorus concentrations, and the annual scales and frequencies of cyanobacterial blooms in lakes across long-term spatial scales to probe the relationship of UV radiation with cyanobacterial blooms. The results indicated that enhanced solar UV radiation may unintentionally stimulate cyanobacterial growth and favor the expansions of cyanobacterial blooms in lakes around the world. The fluctuating UV radiation significantly affects the annual scales of cyanobacterial blooms in both eutrophic and oligotrophic lakes. Solar UV radiation enhances the positive impact of rising phosphorus levels on cyanobacterial blooms because UV radiation prompts the synthesis of polyphosphate in cyanobacteria cells, which helps cyanobacteria to alleviate the stress of UV light. The scales of cyanobacterial blooms are significantly impacted by solar UV radiation intensities as opposed to the annual frequency of cyanobacterial blooms. Furthermore, solar UV radiation fluctuation with a 9-year period over a 14-year main cycles significantly affects the periodicities of cyanobacterial blooms in global lakes, which provides a basis for predicting the peak value of the scales of cyanobacterial blooms in lakes. These findings opened up new avenues of inquiry into the mechanism and management strategies of cyanobacterial blooms in lakes worldwide.

Non-photochemical quenching may contribute to the dominance of the pale mat-forming lichen Cladonia stellaris over the sympatric melanic Cetraria islandica.

The mat-forming fruticose lichens Cladonia stellaris and Cetraria islandica frequently co-occur on soils in sun-exposed boreal, subarctic, and alpine ecosystems. While the dominant reindeer lichen Cladonia lacks a cortex but produces the light-reflecting pale pigment usnic acid on its surface, the common but patchier Cetraria has a firm cortex sealed by the light-absorbing pigment melanin. By measuring reflectance spectra, high-light tolerance, photosynthetic responses, and chlorophyll fluorescence in sympatric populations of these lichens differing in fungal pigments, we aimed to study how they cope with high light while hydrated. Specimens of the two species tolerated high light equally well but with different protective mechanisms. The mycobiont of the melanic species efficiently absorbed excess light, consistent with a lower need for its photobiont to protect itself by non-photochemical quenching (NPQ). By contrast, usnic acid screened light at 450-700nm by reflectance and absorbed shorter wavelengths. The ecorticate usnic species with less efficient fungal light screening exhibited a consistently lower light compensation point and higher CO2 uptake rates than the melanic lichen. In both species, steady state NPQ rapidly increased at increasing light with no signs of light saturation. To compensate for less internal shading causing light fluctuations with a larger amplitude, the usnic lichen photobiont adjusted to changing light by faster induction and faster relaxation of NPQ rapidly transforming excess excitation energy to less damaging heat. The high and flexible NPQ tracking fluctuations in solar radiation probably contributes to the strong dominance of the usnic mat-forming Cladonia in open lichen-dominated heaths.

Enhanced Convolutional Neural Network for solar radiation nowcasting: All-Sky camera infrared images embedded with exogeneous parameters

Electrical power production by renewable energy sources is unpredictable in nature and this may cause imbalance between power generation and demand. Therefore, an accurate prediction of solar radiation is crucial for the stability and efficient management of electric grid. This study focuses on very short-term forecasts of solar radiation with a horizon in the range of 5–15 min. In this paper, a Convolutional Neural Network is proposed that uses sequences of infrared images captured by an All-Sky Imager to forecast the Global Horizontal Irradiance on different time horizon. A real case study, exploiting six months of high-resolution data, is analyzed. Additionally, an innovative technique, the Enhanced Convolutional Neural Network (ECNN), is proposed in which exogenous data, as the solar radiation measurement, is encoded in terms of colored pixels in the upper corner of the images. Considering the naïve persistence method as a baseline, a clear improvement across the key metrics has been noted with the proposed methodology. A deeper analysis of the results reveals that the proposed models are more accurate than persistence when high fluctuations of solar radiation are experienced. In that case, the ECNN achieves a forecast skill exceeding 19% for all the tested forecast horizons.

Enhancing photovoltaic performance through solar radiation splitting: A beam splitter-assisted hybrid approach with 2-D tracking and PCM integration

Solar energy is an abundant and environmentally friendly power source; however, its conversion efficiency is limited by the mismatch between the response of photovoltaic (PV) and the solar spectrum. This paper proposes a novel hybrid system that splits solar radiation into visible and thermal components using a beam splitter. Through experimental and theoretical analyses, the study explores the integration of a phase change material (PCM) packed bed with a PV cell as a hybrid system to optimize energy conversion. The experiment is carried out using a 2D tracker. The concentration ratio, determined based on the maximum concentration ratio (MCR) supported by the PV cell, is established as the optimum point. For Silicon PV, the maximum concentration ratios are determined to be 8 and 16 sun for the cases of using and not using the beam splitter, respectively. The ratios of thermal and visible energy, measured at a wavelength of 700 nm, are observed to be 60.66 % and 39.33 % respectively. Under MCR conditions, in the PV system alone, the generated power reaches approximately 850 W/m2, while in the hybrid splitting configuration, it increases to around 1200 W/m2, resulting in a 43 % increase in the system's net power when employing the beam splitter. Furthermore, the study reveals that the utilization factor remains constant at 0.13 across all irradiation ranges for PV-alone systems. In contrast, for the PV/PCM hybrid splitting system, the utilization factor exhibits an increasing trend with higher solar irradiation intensities, reaching values of 0.31, 0.41, and 0.46 for irradiation ranges of 900, 950, and 1000 W/m2, respectively. The findings of this study suggest the potential of using a beam splitter in combination with a 2-D tracker and PCM-packed bed to increase PV efficiency. The proposed configuration demonstrates a substantial enhancement in total net power output, offering a promising avenue for advancing solar energy conversion technologies. Adding PCM to the system has proven to be beneficial, as it addresses the fluctuations in solar radiation and may enhance the total system efficiency.

A new hybrid model for photovoltaic output power prediction.

Recently, with the development of renewable energy technologies, photovoltaic (PV) power generation is widely used in the grid. However, as PV power generation is influenced by external factors, such as solar radiation fluctuation, PV output power is intermittent and volatile, and thus the accurate PV output power prediction is imperative for the grid stability. To address this issue, based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), improved artificial rabbits optimization (IARO) and convolutional bidirectional long short-term memory (CBiLSTM), a new hybrid model denoted by CEEMDAN-IARO-CBiLSTM is proposed. In addition, inputs of the proposed model are optimized by analyzing influential factors of PV output power with Pearson correlation coefficient method. In order to verify the prediction accuracy, CEEMDAN-IARO-CBiLSTM is compared with other well-known methods under different weather conditions and different seasons. Specifically, for different weather conditions, MAE and RMSE of the proposed model decrease by at least 0.329 and 0.411, 0.086 and 0.021, and 0.140 and 0.220, respectively. With respect to different seasons, MAE and RMSE of the proposed model decrease by at least 0.270 and 0.378, 0.158 and 0.209, 0.210 and 0.292, and 1.096 and 1.148, respectively. Moreover, two statistical tests are conducted, and the corresponding results show that the prediction performance of CEEMDAN-IARO-CBiLSTM is superior to other well-known methods.

A passive continuous flow pasteurisation process designed for solar application. Part I: Indoor experiments for thermal characterization and bacteria inactivation

Within the framework of the WHO's universal sanitation policy, water disinfection processes with low manufacturing and maintenance costs must be developed. This is the case with solar pasteurisation, the effectiveness of which, at 50–70 °C, has been already demonstrated in the literature. To be fully acceptable, the process must be appropriately energy efficient and be able to adapt to natural fluctuations in solar radiation. An experimental indoor test platform under controlled conditions, with thermal powers supplied similar to those of a future solar application with a standard thermal panel, was designed. Experimental results highlighted the specific thermal energy consumption (SECtherm), which is highly dependent on the effectiveness of a deliberately oversized heat recovery exchanger. The operation under both stationary and dynamic regimes underscored the role of the thermostatic valve which autonomously calibrated the flow of the fluid according to the injected available power. For the temperature range sufficient to inactivate microorganisms [50–70 °C], the specific thermal energy consumption reached values between 3.5 and 6 kWhtherm.m−3. The bacterial indicators, Escherichia coli and Enteroccocus, currently present in surface waters in the south of France, were no longer detected (<10 MPN.100 mL−1) after one-minute of pasteurisation at 55 °C and 60 °C, respectively.

Impact of Solar Radiation on Luminaires and Energy Efficiency in Isolated Residential Photovoltaic Systems

This research centers on the implementation of photovoltaic systems in residential applications, coupled with battery-based energy storage, and evaluates their efficiency in generating energy, specifically for lighting in buildings. The methodology hinges on detecting interharmonic signals to characterize potentially disruptive frequencies and identify the origins of various failures. Multiple case studies are presented to validate the method’s efficacy, including one involving fluorescent lamp circuits and another examining variations in solar radiation during the summer season. Real-world experiments are conducted in a residential setting, and the results are thoroughly analyzed. Various types of interharmonic generation behaviors are demonstrated, which are influenced by fluctuations in solar radiation and the appropriate installation of solar panels. The findings reveal that the absence of solar radiation below 300 W/m2 in a photovoltaic system relying on energy storage adversely affects interharmonics in luminaires installed within a residential space.

Back propagation neural network based proportional-integral hybrid control strategy for a solar methane reforming reactor

To handle the impact of solar radiation fluctuations on the solar reactor, a new proportional-integral (PI) hybrid control strategy based on back propagation neural network (BPNN) is designed in this study to achieve stable operation. Firstly, the BPNN model optimized by genetic algorithm is trained using reactor model simulation data. Then, the BPNN model is combined with PI feedback control to obtain a BPNN-based PI feedforward-feedback hybrid control strategy for regulating the inlet flow rate. Finally, the effectiveness of the control strategy during transient operation under different disturbances is tested. The results show that during actual solar radiation disturbance, the integral square errors (ISE) of outlet hydrogen fraction and methane conversion for BPNN-based PI hybrid control are 7.03 × 10−6 and 1.05 × 10−4, respectively. Compared to traditional PI feedback control, the new hybrid control strategy represents a reduction of 94% and 91% in ISE, indicating that the strategy can significantly improve production stability.

Fuzzy logic controller-based enhancement for grid-connected large-scale PV systems

: In recent years, considerable scholarly attention has been directed toward photovoltaic (PV) power generation, driven by the imperative to ameliorate the ecological ramifications inherent in conventional electricity generators. The economic viability of PV generation is intrinsically contingent upon both the cost-efficiency of the cells employed and the quantum of energy that the arrays have the capacity to deliver over their operational lifespan. This scholarly exposition elucidates an exploratory inquiry into the intricate realm of modeling and simulating solar PV systems, conjoined with the distribution grid via the employment of a Fuzzy Logic Controller (FLC). The inquiry delves into the nuanced realm of the influence wielded by fluctuations in solar radiation upon the system's operational efficacy, concurrently proffering a novel energy storage framework engineered to counterbalance the power quality predicaments stemming from the intermittent nature of solar energy. The empirical manifestations gleaned from simulations evince the system's conceptual prowess, effectuating an amelioration in the comprehensive operational dexterity of the solar PV system, thereby embellishing energy capture efficiency and mollifying the perturbing power quality predicaments. A comparative investigation, encompassing varied conditions, substantiates the prowess of the proposed methodology vis-à-vis the fixed perturbation Maximum Power Point Tracking (MPPT) algorithm. Empirical observations emanating from these investigations conspicuously affirm the feasibility and distinct advantages underpinning the purview of the proposed methodology.

Arctic Plant Responses to Summer Climates and Flooding Events: A Study of Carbon and Nitrogen‐Related Larch Growth and Ecosystem Parameters in Northeastern Siberia

AbstractBuilt upon a 5‐year field investigation and a 13‐year satellite data set, this study examines the intricate interrelationships among ecophysiological parameters of Larix gmelinii trees and the prevailing ecosystem, climatic, and environmental factors present in the Indigirka lowlands of northeastern Siberia. It identified spatial‐temporal patterns in July needle nitrogen (N) content as an indicator of N availability from 2009 to 2013. Needle N content (%) revealed distinct yearly values: 2012 (1.31 ± 0.24), 2013 (1.67 ± 0.39), 2009 (1.72 ± 0.15), 2011 (1.84 ± 0.34), and 2010 (2.08 ± 0.25). Positive correlations were found between ecosystem and larch parameters, as well as between September temperature or February/May precipitation and subsequent July ecosystem productivity. Soil moisture (SM) primarily influences N availability across sites, with higher SM levels reducing N availability. However, July air temperature (AT) is the primary driver of interannual N availability changes, with higher temperatures enhancing N availability. Larch photosynthesis is mainly influenced by solar radiation (SR), temperature, N availability, and SM. Annual fluctuations in SR positively impact larch photosynthesis, while high temperatures or wetting events impose limitations on photosynthesis, even if N availability has increased. Consequently, a moderate correlation exists between N availability and photosynthesis across various sites and years (r = 0.422, P = 0.133, n = 14). In summary, this research provides valuable insights into climatic and environmental impacts on larch trees and ecosystems, emphasizing the significance of SM, AT, and SR for predicting future growth patterns of larch.

Construction of a new LED chamber to measure net ecosystem exchange in low vegetation and validation study in grain crops

A vegetation canopy chamber system measures gas exchanges in the field between plants and the environment. Transparent closed chambers have generally been used to measure canopy fluxes in the field, depending on solar radiation as the light source for photosynthesis. However, measuring canopy fluxes in nature can be challenging due to fluctuations in solar radiation. Therefore, we constructed a novel transient-state closed-chamber system using light-emitting diodes (LEDs) as a light source to measure canopy-scale fluxes. The water-cooled chamber system used a 1600 Watt LED module to produce constant photosynthetically active radiation (PAR) and a CO2 gas analyzer for concentration measurements. We used the LED chamber system to measure barley and wheat gas exchanges in the field to quantify CO2 fluxes along a PAR gradient. This novel technology enables the determination of photosynthesis rates for various crops under diverse environmental conditions, in diverse ecosystems, and across long-term interannual changes, including those due to climate change.

Optimal insulation of underground spherical tanks for seasonal thermal energy storage applications

The literature deals specifically with compressed gas characteristics, solar radiation, storage volume and heat load fluctuation in aboveground storage and thermal energy storage (TES) applications. To prevent their negative effects, the use of underground insulated spherical tanks in the storage process has been overlooked. This study details the physical and economic aspects of using insulation in underground spherical tanks for seasonal TES systems. In determining the storage heat load, the degree-time method is recommended for the heat transfer mechanism between soil and storage temperature degrees. Using life cycle cost analysis, the insulation thickness, energy saving and payback period in the underground spherical tank are discussed in detail for hot and cold storage capacities. The results of the study indicated that the degree-hour method can be used in the design of hot and cold TES systems despite the temperature fluctuation. Insulation can be taken care of in hot fluid storage instead of cold alternative. With insulation in the underground spherical tank, it is observed than about 200 % energy savings is possible with approximately 50 % shorter payback period. For the hot fluid storage with insulation, as the storage fluid temperature, soil thermal conductivity and tank diameter rise and the depth falls, but the optimum insulation thickness value increases. As a result, this study is expected to be a guide for further seasonal TES applications using insulation in underground spherical tanks.

Effects of Extreme Temperature and Precipitation Events on Daily CO2 Fluxes in the Tropics

The effects of anomalous weather conditions (such as extreme temperatures and precipitation) on CO2 flux variability in different tropical ecosystems were assessed using available reanalysis data, as well as information about daily net CO2 fluxes from the global FLUXNET database. A working hypothesis of the study suggests that the response of tropical vegetation can differ depending on local geographical conditions and intensity of temperature and precipitation anomalies. The results highlighted the large diversity of CO2 flux responses to the fluctuations of temperature and precipitation in tropical ecosystems that may differ significantly from some previously documented relationships (e.g., higher CO2 emission under the drier and hotter weather, higher CO2 uptake under colder and wetter weather conditions). They showed that heavy precipitation mainly leads to the strong intensification of mean daily CO2 release into the atmosphere at almost all stations and in all types of study biomes. For the majority of considered tropical ecosystems, the intensification of daily CO2 emission during cold and wet weather was found, whereas the ecosystems were predominantly served as CO2 sinks from the atmosphere under hot/dry conditions. Such disparate responses suggested that positive and negative temperature and precipitation anomalies influence Gross Primary Production (GPP) and Ecosystem Respiration (ER) rates differently that may result in various responses of Net Ecosystem Exchanges (NEE) of CO2 to external impacts. Their responses may also depend on various local biotic and abiotic factors, including plant canopy age and structure, plant biodiversity and plasticity, soil organic carbon and water availability, surface topography, solar radiation fluctuation, etc.

Preparation, thermochromic properties and temperature controlling ability of novel pellets in ultra-thin wearing course

The performance of ultra-thin wear layer (UTWC) is sensitive to solar radiation and ambient temperature fluctuation. For the purpose of boosting the durability of thermochromic materials in service life as well as improving the function of temperature controlling of asphalt mixtures, a novel pellet was prepared by ion displacement method. The temperature control mechanism for asphalt ultra-thin wear layer with pellets was also investigated. The uniaxial compression experiment and differential scanning calorimetry were deployed to investigate the mechanical strength and phase change characteristics of the pellets. The results indicate that the pellet possesses the merits of high elastic strength and strong sensitivity to ambient temperature. The incorporation of pellets can alleviate thermal fluctuation and improve the high temperature performance of UTWC but reduce its low temperature performance. The specific UTWC with pellets exhibits a maximum temperature reduction of 5.5 °C. The incorporating of pellets in asphalt mixture provides the characteristics of phase change function, alters the thermal properties, thus possess the ability to control temperature of UTWC well.

Forecasting the Distortion in Solar Radiation during Midday Hours by Analyzing Solar Radiation during Early Morning Hours

Knowing the fluctuation of solar radiation is essential for reliable and safe operation of power systems with a high share of solar PV power plants. This paper introduces a novel method for forecasting the distortion in global solar radiation during the midday time (during the peak of solar radiation at which the generation of the PV plants is maximum), by analyzing the solar radiation during the very early hours. This paper shows that there is a strong relation between the condition of the solar radiation during the very early minutes of the day (when the generation of the PV plants is low) and the condition of the solar radiation during the midday hours (when the output of the PV plants is enormous). This relation can be utilized to help power systems operators in determining the safe share of PV plants that can be fed to power systems. We analyzed real data of one complete year for two sites in Saudi Arabia to approve this approach. The difference between each two readings was calculated for the hours 7 a.m. and 8 a.m. Then, the negative, zero, and amplitude of the difference was used to formulate a distortion index (DI) that predicts the distortion/fluctuation in the global radiation. It was concluded that the DI could classify the days into three categories: clean, distorted, and medium level according to the value of the DI. The accuracy of this approach was 85.2% and the error was 14.8%.

Multi-objective long-term expansion planning of electric vehicle infrastructures integrated with wind and solar units under the uncertain environment considering demand side management: A real test case

The penetration of electric vehicles and renewable resources as highly influenced components in global warming and greenhouse gasses emission has increased in recent years. This paper determines the optimal allocation of battery charging and swapping stations integrated with wind and solar units to minimize total cost and voltage deviation based on a long-term expansion planning. According to the presence of uncertain parameters and in order to simulate realistic conditions, a scenario generation/reduction approach is also performed to model the fluctuations of wind speed, solar radiation, electrical loads, incoming vehicles and market price. As well, a time-of-use strategy is implemented to show the impact of flexible loads on objective functions. It is noteworthy that simulations are implemented on a real distribution network with actual geographical data. The results for the proposed model in the deterministic state show an improvement equal to 283.33% for the voltage deviation, while a profit equal to 2.2 million dollars per model lifetime is achieved. The uncertainties deteriorate the voltage deviation by 12.12%, in return, the profit is increased by 8.63%. It is also concluded that responsive loads increase the profit and enhance the voltage deviation by 7.94% and 6.3%, respectively.

Experimental Investigation on Solar Water Heater Integrated with Thermal Battery Using Phase Change Material and Porous Media

Evacuated tube heat pipe solar collector as a passive solar water heating system is a simple, reliable, and cost-effective way to capture the sun’s thermal energy to supply hot water to homes. In the proposed system, the manifold is reshaped to a tank and filled with phase change materials (PCM) and porous media, which the PCM acts as a latent heat thermal energy storage medium. In order to increase the heat flux from the heat pipe to the PCM and overcome the low thermal conductivity of the PCM, porous media is used. The porous media is connected to the heat pipe condenser to collect the heat and distribute it uniformly throughout the PCM filling the pores. This design of the manifold acts as a heat storage tank or thermal battery. Another pipe in the tank transfers heat from the PCM to the water. Experiments were conducted in 2 modes: charging/discharging and periodic draw-off. The results demonstrated that this thermal battery design could provide homes with the hot water they require on sunny days, while it needs an auxiliary heater or larger solar collector to provide enough hot water on rainy/cloudy days. Considering the solar radiation fluctuation, the efficiency of the thermal battery is 50% ± 9.3%. The thermal battery can warm up the cold water higher than the operating temperature on a sunny day (more than 120 L per day at 38 °C). Using porous media provides better heat distribution in the PCM.