Typical Solar Radiation Research Articles

Spatiotemporal Variations in the Sensitivity of Vegetation Growth to Typical Climate Factors on the Qinghai–Tibet Plateau

Gaining knowledge about vegetation sensitivity in response to climate change is a current research priority in the context of accelerated shifts generated by global warming, especially for the Qinghai–Tibet Plateau (QTP), where vegetation is known to be highly sensitive to ongoing climate change. However, the temporal variability of vegetation sensitivity in response to climate change is still poorly understood on the QTP. Here, we articulate the interannual variability of the vegetation sensitivity in response to typical climate factors, including temperature, solar radiation, and water availability, on the QTP during 2000–2021, using a variety of indicators characterizing vegetation dynamics, including the Leaf Area Index (LAI), the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and solar-induced chlorophyll fluorescence (SIF) data. The results indicate that temperature exerted positive impacts on forests, grasslands, and barren or sparsely vegetated areas (BSVs). However, all the land-cover types showed decreasing sensitivity to temperature variability. Solar radiation had a positive impact on forests, while it had a negative impact on grasslands and BSVs. An increasing trend was observed for forests, while a decreasing trend was found for grasslands and BSVs regarding their sensitivity to solar radiation. Water availability exerted a positive impact on grasslands and BSVs, and no obvious impact direction could be determined for forests. Over the last two decades, forests and BSVs exhibited increasing sensitivity to water availability, and no obvious trend was observed for grasslands. Overall, temperature was the most important climate factor, followed by solar radiation and water availability, regarding the regulation of vegetation sensitivity on the QTP. Spatially, temperature and solar radiation jointly dominated the vegetation sensitivity in the central to eastern QTP. Conversely, water availability dominated the sensitivity of forests in the southeastern QTP and grasslands in the northeastern and southwestern QTP. This study provides theoretical support for the ecological conservation and management of the QTP in the context of ongoing climate change.

DEVELOPMENT OF INTELLIGENT CONTROL STRATEGY FOR POWER QUALITY IMPROVEMENT OF HYBRID RES

The major problem in renewable energy system is that the variation in power generation from time to time because of the intermittent nature of the renewable sources. In this paper presents the Artificial Neural Network (ANN) based intelligent control strategy for hybrid standalone microgrid system for varying wind, varying solar irradiation, varying load and symmetrical and asymmetrical fault conditions is presented. A dynamic model of hybrid standalone microgrid consisting wind and solar PV renewable sources with maximum power point tracking control algorithm is developed in MATLAB/Simulink software. A solar PV panel, wind energy conversion system and dynamic model of hybrid energy storage consisting Lithium-ion batteries (Li-Ion) and supercapacitor is connected with the DC Bus. The DC link is connected through the power electronic interfacing circuit and converters connected to a source for a diverse electricity generation. The main objective of this thesis is to improve the power quality of the hybrid microgrid system by solving the voltage sag and swell problem and reduce total harmonics distortion occurring due to various symmetrical and asymmetrical condition. The simulation studies have been carried out to determine system performance with different scenarios of the sources such as typical solar radiation, temperature, wind, battery and supercapacitor charge or discharge conditions The proposed strategy gives better performance characteristics and reduces the harmonics of the system compared to the conventional solution.

ENHANCE EFFICIENCY OF SOLAR ENERGY CONVERSION SYSTEM USING ANFIS WITH ISOLATED MODE

This paper shows performance investigation on enhance efficiency of standalone solar energy conversion system using ANFIS based MPPT controller. Now a days many researches are going in the field of renewable energy technologies to bridge the gap between supply and demand. Due to the Intermittent nature of renewable sources, operating standalone operation of them is highly unreliable causes interruption in power supply to the load. A solar photovoltaic system with MPPT based on Adaptive-Network-Based Fuzzy Inference System (ANFIS) is used for stable operation and to meet the supply with the load demand. The application of ANFIS based MPPT technique requires detailed study and analysis of the Solar Photovoltaic (SPV) system. Adaptive-Network-Based Fuzzy Inference System based MPPT technique is used along with Solar PV system as they can provide fast and accurate response to various environmental conditions. The Levenberg-Marquardt algorithm is used to train the neural network for MPPT in the photovoltaic system. This developed control strategy is able to control the devices and various power interface circuitry used therein. The main aim of this paper is to ensure a maximum power output coordinating appropriate control strategy with sources & compare the performance analysis of the ANFIS based MPPT with conventional incremental conductance based MPPT for the SPV system. The simulation studies have been carried out to find out the SPV system performance with different input conditions such as typical solar radiation and temperature. The Simulation test results show variable power generation and verifies that the performance of the integrated system with this control strategy is effective for the real-time installation. The simulation results shows that the performance of this developed control strategy for receiving maximum power output from the standalone SPV system is farfetched. Simulation test results show variable power generation and verify the performance of the integrated system with control strategy is overall effective for real-time installation. The developed system is essential in an isolated region where an existing grid is unable to supply secure power generation and system is beneficial with smartly feed ultimate power generation sources.

Thermal hysteresis analysis of finned-heat-pipe-assisted latent heat thermal energy storage application for solar water heater system

This work numerically investigates the performance of an innovative compact-design solar water heater (SWH) using evacuated tube heat pipe solar collectors (ETHPSCs) coupled with a latent heat storage tank (LHS tank). This system is thought to be an unwritten fourth generation of solar water heaters known as heat-pipe-assisted thermal batteries. The basic and explicit hypothesis is to store energy than a bulk of hot water, which is the key distinction in compared to the prior classical sorts. Using three phase change materials (PCMs) for high and low solar intensity categories in the tropical region of South East Asia, a computational effort is conducted to model the system and the given temperature headed for the supply output hot water. This research is validated by two interrelated experimental and analytical investigations. According to the results of 12-h charging (melting) process, the maximum mean temperature of the PCMs belongs to PCM C, Rubitherm (RT70HC), which indicates 101 °C during the defined typical high daily solar radiation. This value implies 2.02% error in compared to the reference study. Referring to the solid-liquid interface parameter, the maximum liquefied thickness is also for PCM C with 76 mm thickness. However, reaching the complete melting is required by further studies.

Numerical Simulation of Thermal Process in a Phase Change Material Exposed to Solar Heating in a Tropical Region

The capacity for phase change material (PCM) to absorb and release latent heat has led to its applications in heating/cooling strategies in solar heating systems, air-conditioning system, electronics cooling and food preservation. The use of PCM in building construction through micro/macro-encapsulation to passively cool/heat a living space has attracted a lot of experimental and simulation research work, especially after the turmoil caused due to worldwide energy crises. In this paper, the thermal behaviour of a PCM exposed to solar heating in a tropical climate is studied numerically over a 24-hour period using the ANSYS fluent Software. A grid dependency test is initially devised to establish the most appropriate grid sizes and time steps to be used for the subsequent simulations with acceptable accuracy. PCM is setup to be in contact with one side of a concrete block. The other side of the concrete is exposed directly to a typical daily solar radiation profile of a tropical region. Results, in terms of temperature distribution and liquid fraction, show that a two-layer of a commercially available PCM is sufficient to flatten the temperature fluctuations arising from solar heating in the tropical regions.

Method for solar resource assessment using numerical weather prediction and artificial neural network models based on typical meteorological data: Application to the south of Portugal

In this work a method for regional solar resource assessment based on numerical weather prediction (NWP) and artificial neural network (ANN) models is presented. The method was developed using typical meteorological and solar radiation data and applied to the location of Évora, Portugal with the goal of assessing solar global horizontal (GHI) and direct normal (DNI) irradiations with 1.25 km of horizontal resolution in the south of Portugal. The NWP model used was the research model Meso-NH and a site adaptation model was developed based in ANNs and using as inputs the simulated meteorological variables from Meso-NH and aerosol data from Copernicus Atmospheric Monitoring Services (CAMS) for the observation site. The resulting annual relative mean bias errors for GHI and DNI at Évora and typical meteorological year are of 0.55 % and 0.98 %, respectively, while the values for the original Meso-NH simulations are of 8.24 % for GHI and 31.71 % for DNI. The developed site adaptation model is applied to the region for the purpose of solar radiation assessment and validated using data from a network of solar radiation measuring stations scattered throughout the south of Portugal, showing relative mean bias errors of 2.34 % for GHI and 3.41 % for DNI, while the original Meso-NH simulations presents relative mean bias errors of 8.50 % and 29.54 %, respectively. These results allowed the generation of improved solar resource availability maps which are a very useful tool in solar resource assessment, the study of shortwave radiative climate, as well as project planning and solar system design and operation.

The potential effects of temperature on outpatient visits: a case study in Chiang Mai, Thailand.

Climate change is a crucial cause of health issues, as reported in many studies. Temperature is one of the important factors related to extreme weather. Chiang Mai, the center of the north of Thailand, is also affected by temperature changes that have led to many outpatient visits. Better information will help the health service to be well-prepared. This research applied typical meteorological data and solar radiation into the distributed lag nonlinear model and a quasi-Poisson regression model. The "hot effect" and "cold effect" on outpatient visits caused by respiratory diseases, dermatophytosis, and intestinal infectious diseases in a public Chiang Mai hospital between January 2015 and December 2019 were then investigated. Of the 185,202 cases, results showed that all of the diseases mentioned had more than 10% of relative risk (RR) in cold effects. However, the RR of dermatophytosis was found to be 114%, a very high risk. In the case of hot effects, the patients of the age 19-29 have relatively high RR over 20% for respiratory diseases and dermatophytosis. It was also observed that cold effects lasted longer than hot effects.

Methodology for determining the design radiation for a PTC heating system based on non-guaranteed days

Solar heating, as an alternative technology to coal-fired heating, could significantly alleviate the air pollution in China. The value of design radiation should be carefully determined when designing a solar system, as it would commonly affect the solar collector area, and then the economics and performance of the system. However, in the existing publications, most studies ignore the influence of the daily and seasonal variation of radiation, and commonly choose the fixed value of design radiation in some typical days, leading to a non-optimal performance of the system with unreasonable setting parameters. To solve this problem in the design stage, a method is proposed to determine the design radiation of a parabolic trough collector (PTC) heating system. In this method, the concept of non-guaranteed days is introduced to quickly and conveniently determine the system rated capacity. Additionally, the cost of unit heating supply is employed in this method as an optimized object of the heating system. Based on the proposed method, a case study for four typical solar radiation districts in China is conducted. Firstly, the design radiation values of each district are decided through the proposed method. Then, the relationship between non-guaranteed days and the initial investment of the system under the optimal design radiation is obtained. Finally, the economic analysis of the PTC system in Mentougou (suburbs of Beijing) is performed. This work could be a practical guide to select the design radiation for a PTC heating system without the auxiliary boiler. Moreover, the method could also be applied to more types of solar systems and regions.

Thermo-economic optimization of solar organic Rankine cycle based on typical solar radiation year

The thermo-economic optimization of a solar organic Rankine cycle (SORC) should consider the features of fluctuations in solar radiation based on local historical solar radiation. However, the use of historical solar radiation is inconvenient for thermo-economic optimization because it involves considerable computational effort for simulation. To overcome this inconvenience, we propose the thermo-economic optimization of SORC by using typical solar radiation year (TSRY). TSRY is a synthesis of typical solar radiation on the basis of historical solar radiation, indicating that TSRY can reflect the typical features of fluctuations in solar radiation in a specific area. Afterward, the multi-objective genetic algorithm (GA) is selected to optimize the dynamic performance of a small-scale SORC by using the TSRY. In GA, the evaporation temperature and capacity of thermal energy storage are taken as optimization parameters, and the power output and fluctuation in power output are optimization goals. Accordingly, Pareto frontiers that optimize the SORC performance can be obtained. The effect of different parameter combinations in the Pareto frontiers and the scale of the SORC on thermo-economic are further analyzed using annual net profit as an indicator. Our analysis shows that a minimum SORC scale for profitability is set for a given location, and the profit growth rate increases as the system scale increases.

Evaluation of Building Energy Saving Through the Development of Venetian Blinds’ Optimal Control Algorithm According to the Orientation and Window-to-Wall Ratio

As various studies focusing on building energy saving have been continuously conducted, studies utilizing renewable energy sources, instead of fossil fuel, are needed. In particular, studies regarding solar energy are being carried out in the field of building science; in order to utilize such solar energy effectively, solar radiation being brought into the indoors should be acquired and blocked properly. Blinds are a typical solar radiation control device that is capable of controlling indoor thermal and light environments. However, slat-type blinds are manually controlled, giving a negative effect on building energy saving. In this regard, studies regarding the automatic control of slat-type blinds have been carried out for the last couple of decades. Therefore, this study aims to provide preliminary data for optimal control research through the controlling of slat angle in slat-type blinds by comprehensively considering various input variables. The window area ratio and orientation were selected as input variables. It was found that an optimal control algorithm was different among each window-to-wall ratio and window orientation. In addition, through comparing and analyzing the building energy saving performance for each condition by applying the developed algorithms to simulations, up to 20.7 % energy saving was shown in the cooling period and up to 12.3 % energy saving was shown in the heating period. In addition, building energy saving effect was greater as the window area ratio increased given the same orientation, and the effects of window-to-wall ratio in the cooling period were higher than those of window-to-wall ratio in the heating period.

Photostability and influence of phthalocyanine pigments on the photodegradation of acrylic paints under accelerated solar radiation

Self-made and commercial acrylic paints containing phthalo blues (C. I. Name PB15:1, PB15:3, PB15:6, and PB16), and phthalo greens (PG7 and PG36) were exposed to artificial ageing in a Xenon Arc simulator (910 W/m2). The ageing conditions are reproducing the typical outdoor solar radiation, which artworks conceived for outdoor spaces might be exposed to. Complementary analytical techniques were employed in order to study the photodegradation process occurring on the paints. By means of micro-Raman spectroscopy the pigment component in the paints was investigated, while Py-GC/MS in double shot mode was employed for the characterization of photodegradation products of both binder and pigments. Furthermore, FTIR-ATR analyses allowed semi-quantitative considerations about the influence of each selected pigment on the degradation of the acrylic binder. Finally, UV-Vis spectroscopy allowed the discrimination of the pigments in the paints and the study of the colour changes.Raman spectra acquired on both, unaged and aged specimens did not show any difference concerning the pigment bands, whereas Py-GC/MS in double shot mode, revealed a decrease in the thermal stability of the pigments as well as of the acrylic binders identified (nBA/MMA, EA/MMA, nBA/Sty/2-EHA, and 2-EHA/MMA). Typical photooxidation products of acrylic binders, such as increased monomers and oligomers, related to side-chain scission as well as main-chain scission reactions, were characterized by means of Py-GC/MS and FTIR-ATR. Commercial paints revealed also whitening and chalking phenomena, mainly due to the presence of white fillers and additives in the paints formulations. These phenomena could be registered also by UV-Vis spectroscopy.

Temperature effects on the shear capacity of external bonded fiber reinforced polymer on concrete

The use of Fibre Reinforced Polymer (FRP) for the strengthening of concrete structures involves their exposure to temperature variations. This paper investigates the combined effect of the temperature and mechanical loads on FRP-concrete bonds. The investigation refers to a double lap shear test conducted in a controlled temperature chamber with temperature ranging from −40°C to 120°C. Both experimental and theoretical analyses are performed. The experimental results demonstrate (i) a decrease of the failure loads for temperatures higher than the Tg (40°C) of the adhesive matrix, (ii) an increase of the failure loads for temperatures lower than Tg which, however, decreases for very low temperatures (lower than −20°C), and (iii) the cohesive failure modes for temperatures ranging from −40°C to 40°C to de-cohesive failure modes for temperatures above 40°C. Analytical and finite element analysis helps to illuminate the experimental results and indicates that the difference in the coefficient of thermal expansions, as well as the mechanical loads, have an impact on the stress/strain distribution. Finally, the finite element model was used to analyse the typical solar radiation effects (during summer and winter days) on the reinforced systems. The cyclic variations of stress due to the sun thermal effects highlight the need of using an adhesive matrix with a high fatigue limit for FRP reinforcement.

Typical solar radiation year construction using k-means clustering and discrete-time Markov chain

Daily solar radiation (DSR) fluctuation and transition rules affect the design of the energy storage system and online control strategy of solar energy utilisation systems. However, the current synthesis methods for the typical meteorological year do not emphasise such features of DSR. To overcome this shortcoming, this study presents an innovative synthesis method for a Typical Solar Radiation Year (TSRY) based on k-means clustering and discrete-time Markov chain (DTMC). The historical distributions of clear-sky ratio (CSR) in four representative regions were analysed, and a six-dimensional feature vector that represents the DSR fluctuations based on CSR was defined. Then, based on the feature vector, k-means clustering was used to cluster the historical DSR into four types. Subsequently, a DTMC-based model was built for transition rule estimation among the four types of solar radiation. Finally, the TSRY was established based on the clustering categories and transition rules among them. The innovative synthesis method was also verified in this study. Results for the four regions showed that the average error of the synthesised TSRY has maximum and minimum values of 10% and 6% in all seasons, respectively, compared with historical data. The proposed method could represent DSR fluctuation and transition characteristics of certain regions and could also be extended to other regions.

A Hybrid Method for Generation of Typical Meteorological Years for Different Climates of China

Since a representative dataset of the climatological features of a location is important for calculations relating to many fields, such as solar energy system, agriculture, meteorology and architecture, there is a need to investigate the methodology for generating a typical meteorological year (TMY). In this paper, a hybrid method with mixed treatment of selected results from the Danish method, the Festa-Ratto method, and the modified typical meteorological year method is proposed to determine typical meteorological years for 35 locations in six different climatic zones of China (Tropical Zone, Subtropical Zone, Warm Temperate Zone, Mid Temperate Zone, Cold Temperate Zone and Tibetan Plateau Zone). Measured weather data (air dry-bulb temperature, air relative humidity, wind speed, pressure, sunshine duration and global solar radiation), which cover the period of 1994–2015, are obtained and applied in the process of forming TMY. The TMY data and typical solar radiation data are investigated and analyzed in this study. It is found that the results of the hybrid method have better performance in terms of the long-term average measured data during the year than the other investigated methods. Moreover, the Gaussian process regression (GPR) model is recommended to forecast the monthly mean solar radiation using the last 22 years (1994–2015) of measured data.

Optimal allocation and sizing of PV/Wind/Split-diesel/Battery hybrid energy system for minimizing life cycle cost, carbon emission and dump energy of remote residential building

In this paper, a Genetic Algorithm (GA) is utilized to implement a tri-objective design of a grid independent PV/Wind/Split-diesel/Battery hybrid energy system for a typical residential building with the objective of minimizing the Life Cycle Cost (LCC), CO2 emissions and dump energy. To achieve some of these objectives, small split Diesel generators are used in place of single big Diesel generator and are aggregable based on certain set of rules depending on available renewable energy resources and state of charge of the battery. The algorithm was utilized to study five scenarios (PV/Battery, Wind/Battery, Single big Diesel generator, aggregable 3-split Diesel generators, PV/Wind/Split-diesel/Battery) for a typical load profile of a residential house using typical wind and solar radiation data. The results obtained revealed that the PV/Wind/Split-diesel/Battery is the most attractive scenario (optimal) having LCC of $11,273, COE of 0.13 ($/kWh), net dump energy of 3MWh, and net CO2 emission of 13,273kg. It offers 46%, 28%, 82% and 94% reduction in LCC, COE, CO2 emission and dump energy respectively when compared to a single big Diesel generator scenario.

Analysis of solar photovoltaic and wind power potential in Afghanistan

Afghanistan has a need for increased access to energy to enable development. In this paper we analyze the potential for large-scale grid-connected solar photovoltaic (PV) and wind power plants in two of Afghanistan's most populous provinces (Balkh and Herat) to meet a large fraction of growing electricity demand. The results presented here represent the first quantitative analysis of potential capacity factors and energy yields of power plants in the country using measured wind speed and typical solar radiation data. Variability of resources is also investigated by comparing temporal profiles with those of electricity demand, using residual load duration curves to determine penetration and curtailment levels for various demand scenarios. We show that solar PV and wind power plants in two provinces could achieve penetration levels of 65%–70% without significant curtailment, which in turn would mean less reliance on unpredictable and unstable power purchase agreements with neighboring countries, longer life of limited domestic fossil fuel resources, and lower imports of diesel fuel, thus avoiding rising costs and detrimental environmental impacts. Our results point to an alternative development pathway from that of previous recommendations for conventional thermal power plants, controversial hydroelectric projects, and a significant dependence on imported power.

Design and Analysis of Concentrated Solar-Energy Assisted Paddle Dryers

Paddle dryer, one kind of indirect dryers, is widely used in removing moisture content of many materials, such as brown coal, sewage sludge, and biomass. For many applications, the materials to be dried are low-valued or even wastes, so the drying energy consumption becomes the critical issue. One way to reduce the energy consumption is to introduce solar-drying technology. In this paper, firstly, we present a paddle dryer system configuration with concentrated solar energy (CSE) device, which consists of trough-type collectors, thermal storage tanks and auxiliary parts. Then a calculating model is developed to design the drying system. Examples with typical solar radiation conditions in Nanjing, China are illustrated. The energy-saving rate (η), i.e. the ratio of the provided solar energy to the total energy required by the drying process on one-day basis, is evaluated. The developed lab prototype is finally described in brief.

Optimistic / Normal / Pessimistic Limits of Global Solar Radiation in Urban Armidale NSW, Australia

The most common data for describing the local solar climate is through what is called Typical Meteorological Year data (TMY). Typical solar radiation data is very important for the calculations of many solar applications. In this study, typical solar radiation years for Armidale town in New South Wales in Australia are generated from the daily global solar radiation data measured for 23 years, utilising the Finkelstein-Schafer statistical method. The study outcome provides optimistic, normal and pessimistic expected global solar radiation in Armidale all over the year based on previous studies conducted based on meteorological historical measured data in Armidale's Airport Weather Automatic Weather Station. Such outcome presents a handy database of global solar radiation to be utilised by solar energy's specialists for detailed calculations and/or ordinary persons for initial assessment of solar energy in Armidale.

Distribution of Solar Diffuse Fraction in Taiwan

A simple polynomial model of the sky clearness index as predictor was proposed in this paper, for estimating the hourly solar diffuse fractions in Taiwan. The error analysis was performed through two statistical indicators, the mean bias error and the root-mean-square error. The out of database validation was also made to confirm the model generality. Next, regressions between monthly averaged conditions and geographical parameters of places (latitude, longitude, and elevation above sea level) were discussed, using the model's estimates and the updated data sets of typical solar radiation year. Based on the results, diffuse fraction maps for two observation periods were presented in 1-km resolution via an aid of linear interpolation.

A step-by-step application of Danish method for generation of typical meteorological years of China

Typical weather year files like typical meteorological year (TMY) are of utmost importance for calculations concerning many applications in the field of solar energy systems. They are also essential in many engineering utilizations such as agriculture, meteorology, and building simulations. A step-to-step procedure of the Danish method represented is proposed and applied in this paper. It would facilitate the development of TMYs for any region if enough data are available. By applying the measured weather data covering 10–16 yr, TMYs for 35 meteorological stations in China are generated using the simple step-to-step produce of the Danish method. The TMY data and typical solar radiation data are investigated and analyzed in this study. Moreover, the generated TMY data in this paper are compared with the data from Meteonorm software, SWERA, IWEC and RETScreen software.