Numerical Assessment of the Thermal Efficiency of a Concentrated Photovoltaic/Thermal (CPV/T) Hybrid System Using Air as Heat Transfer Fluid

In this paper, we propose a thermal model of a hybrid photovoltaic/thermal concentration system. Starting from the thermal balance of the model, the equation is solved and simulated with a MATLAB code, considering air as the cooling fluid. This enabled us to evaluate some of the parameters influencing the electrical and thermal performance of this device. The results showed that the temperature, thermal efficiency and electrical efficiency delivered depend on the air mass flow rate. The electrical and thermal efficiencies for different values of air mass flow are encouraging, and demonstrate the benefits of cooling photovoltaic cells. The results show that thermal efficiency decreases air flow rate greater than 0.7 kg/s, whatever the value of the light concentration used. The thermal efficiency of the solar cell increases as the light concentration increases, whatever the air flow rate used. For a concentration equal to 30 sun, the thermal efficiency is 0.16 with an air flow rate equal to 0.005 kg/s;the thermal efficiency increases to 0.19 with an air flow rate equal to 0.1 kg/s at the same concentration. An interesting and useful finding was that the proposed numerical model allows the determination of the electrical as well as thermal efficiency of the hybrid CPV/T with air flow as cooling fluid.

Regulatable Orthotropic 3D Hybrid Continuous Carbon Networks for Efficient Bi-Directional Thermal Conduction

Vertically oriented carbon structures constructed from low-dimen-sional carbon materials are ideal frameworks for high-performance thermal inter-face materials(TIMs).However,improving the interfacial heat-transfer efficiency of vertically oriented carbon structures is a challenging task.Herein,an orthotropic three-dimensional(3D)hybrid carbon network(VSCG)is fabricated by depositing vertically aligned carbon nanotubes(VACNTs)on the surface of a horizontally oriented graphene film(HOGF).The interfacial interaction between the VACNTs and HOGF is then optimized through an annealing strategy.After regulating the orientation structure of the VACNTs and filling the VSCG with polydimethylsi-loxane(PDMS),VSCG/PDMS composites with excellent 3D thermal conductive properties are obtained.The highest in-plane and through-plane thermal conduc-tivities of the composites are 113.61 and 24.37 W m^(-1)K^(-1),respectively.The high contact area of HOGF and good compressibility of VACNTs imbue the VSCG/PDMS composite with low thermal resistance.In addition,the interfacial heat-transfer efficiency of VSCG/PDMS composite in the TIM performance was improved by 71.3%compared to that of a state-of-the-art thermal pad.This new structural design can potentially realize high-performance TIMs that meet the need for high thermal conductivity and low contact thermal resistance in interfacial heat-transfer processes.

Controllable large-scale processing of temperature regulating sheath-core fibers with high-enthalpy for thermal management

Temperature regulating fibers(TRF_(s)) with high enthalpy and high form stability are the key factors for thermal management. However, the enthalpies of most TRFsare not high, and the preparation methods are still at the laboratory scale. It remains a great challenge to use industrial spinning equipment to achieve continuous processing of TRF_(s) with excellent thermal and mechanical properties. Here, polyamide 6(PA6) based TRF_(s) with a sheath-core structure were prepared by bicomponent melt-spinning. The sheath-core TRF(TRF_(sc)) are composed of PA6 as sheath and functional PA6 as core, which are filled with the shape stable phase change materials(ssPCM),dendritic silica@polyethylene glycol(SiO_(2)@PEG). With the aid of the sheath structure, the filling content of SiO_(2)@PEG can reach 30 %, so that the enthalpy of the TRF_(s) can be as high as 21.3 J/g. The ultra-high enthalpy guarantees the temperature regulation ability during the alternating process of cooling and heating. In hot environment, the temperature regulation time is 6.59 min, and the temperature difference is 12.93℃. In addition, the mechanical strength of the prepared TRF_(sc) reaches 2.26 cN/dtex, which can fully meet its application in the field of thermal management textiles and devices to manage the temperature regulation of the human body or precision equipment, etc.

Radiative Blood-Based Hybrid Copper-Graphene Nanoliquid Flows along a Source-Heated Leaning Cylinder

Variant graphene,graphene oxides(GO),and graphene nanoplatelets(GNP)dispersed in blood-based copper(Cu)nanoliquids over a leaning permeable cylinder are the focus of this study.These forms of graphene are highly beneficial in the biological and medical fields for cancer therapy,anti-infection measures,and drug delivery.The non-Newtonian Sutterby(blood-based)hybrid nanoliquid flows are generalized within the context of the Tiwari-Das model to simulate the effects of radiation and heating sources.The governing partial differential equations are reformulated into a nonlinear set of ordinary differential equations using similar transformational expressions.These equations are then transformed into boundary value problems through a shooting technique,followed by the implementation of the bvp4c tool in MATLAB.The influences of various parameters on the model’s nondimensional velocity and temperature profiles,reduced skin friction,and reduced Nusselt number are presented for detailed discussions.The results indicated that Cu-GNP/blood and Cu-GO/blood hybrid nanofluids exhibit the lowest and highest velocity distributions,respectively,for increased nanoparticles volume fraction,curvature parameter,Sutterby fluid parameter,Hartmann number,and wall permeability parameter.Conversely,opposite trends are observed for the temperature distribution for all considered parameters,except the mixed convection parameter.Increases in the reduced skin friction magnitude and the reduced Nusselt number with higher values of graphene/GO/GNP nanoparticle volume fraction are also reported.Finally,GNP is identified as the superior heat conductor,with an average increase of approximately 5%and a peak of 7.8%in the reduced Nusselt number compared to graphene and GO nanoparticles in the Cu/blood nanofluids.

Functionally graded structure of a nitride-strengthened Mg_(2)Si-based hybrid composite

The ex-situ incorporation of the secondary SiC reinforcement,along with the in-situ incorporation of the tertiary and quaternary Mg_(3)N_(2) and Si_(3)N_(4) phases,in the primary matrix of Mg_(2)Si is employed in order to provide ultimate wear resistance based on the laser-irradiation-induced inclusion of N_(2) gas during laser powder bed fusion.This is substantialized based on both the thermal diffusion-and chemical reactionbased metallurgy of the Mg_(2)Si–SiC/nitride hybrid composite.This study also proposes a functional platform for systematically modulating a functionally graded structure and modeling build-direction-dependent architectonics during additive manufacturing.This strategy enables the development of a compositional gradient from the center to the edge of each melt pool of the Mg_(2)Si–SiC/nitride hybrid composite.Consequently,the coefficient of friction of the hybrid composite exhibits a 309.3%decrease to–1.67 compared to–0.54 for the conventional nonreinforced Mg_(2)Si structure,while the tensile strength exhibits a 171.3%increase to 831.5 MPa compared to 485.3 MPa for the conventional structure.This outstanding mechanical behavior is due to the(1)the complementary and synergistic reinforcement effects of the SiC and nitride compounds,each of which possesses an intrinsically high hardness,and(2)the strong adhesion of these compounds to the Mg_(2)Si matrix despite their small sizes and low concentrations.

Comprehensive Examination of Solar Panel Design: A Focus on Thermal Dynamics

In the 21st century, the deployment of ground-based Solar Photovoltaic (PV) Modules has seen exponential growth, driven by increasing demands for green, clean, and renewable energy sources. However, their usage is constrained by certain limitations. Notably, the efficiency of solar PV modules on the ground peaks at a maximum of 25%, and there are concerns regarding their long-term reliability, with an expected lifespan of approximately 25 years without failures. This study focuses on analyzing the thermal efficiency of PV Modules. We have investigated the temperature profile of PV Modules under varying environmental conditions, such as air velocity and ambient temperature, utilizing Computational Fluid Dynamics (CFD). This analysis is crucial as the efficiency of PV Modules is significantly impacted by changes in the temperature differential relative to the environment. Furthermore, the study highlights the effect of airflow over solar panels on their temperature. It is found that a decrease in the temperature of the PV Module increases Open Circuit Voltage, underlining the importance of thermal management in optimizing solar panel performance.

太阳能光伏光热PV/T组件在建筑设计中的应用

建筑领域“双碳”目标的提出,使得降低建筑能耗成为目前亟需解决的问题。可再生能源同建筑领域的有机结合被认为是解决建筑能耗的重要环节。通过对太阳能光伏光热技术的发展进行总结,研究太阳能光伏光热技术在建筑领域中的设计方法,提出了对未来光伏光热建筑一体化的设计思考,为以后太阳能光伏光热PV/T技术产业的发展提供参考。

基于TRNSYS的学校建筑PV/T跨季节蓄热供暖研究

PV/T耦合地源热泵系统在多能互补、提高可再生能源利用率方面受到广泛的关注,针对南京市某小学工程应用PV/T耦合地源热泵系统实现跨季节供暖做模拟分析。应用TRNSYS软件针对系统的运行温度、集热效率、设备工况、能源利用率进行模拟。发现PV/T电池通过地埋管放热的冷却水具有较好的集热冷却效果;土壤蓄热体平均温度仅下降0.23℃,实现土壤热平衡,且该系统的跨季节蓄热率约为60%;热泵机组实际COP平均COP在5以上,具有良好的节能效果;系统跨季节可以提供建筑热负荷的73.17%,发电量可以满足63.2%的热泵能耗。

Numerical Modeling and Technico-Economic Analysis of a Hybrid Energy Production System for Self-Consumption: Case of Rural Area in the Comoros

This study aims to provide electricity to a remote village in the Union of Comoros that has been affected by energy problems for over 40 years. The study uses a 50 kW diesel generator, a 10 kW wind turbine, 1500 kW photovoltaic solar panels, a converter, and storage batteries as the proposed sources. The main objective of this study is to conduct a detailed analysis and optimization of a hybrid diesel and renewable energy system to meet the electricity demand of a remote area village of 800 to 1500 inhabitants located in the north of Ngazidja Island in Comoros. The study uses the Hybrid Optimization Model for Electric Renewable (HOMER) Pro to conduct simulations and optimize the analysis using meteorological data from Comoros. The results show that hybrid combination is more profitable in terms of margin on economic cost with a less expensive investment. With a diesel cost of $1/L, an average wind speed of 5.09 m/s and a solar irradiation value of 6.14 kWh/m2/day, the system works well with a proportion of renewable energy production of 99.44% with an emission quantity of 1311.407 kg/year. 99.2% of the production comes from renewable sources with an estimated energy surplus of 2,125,344 kWh/year with the cost of electricity (COE) estimated at $0.18/kWh, presenting a cost-effective alternative compared to current market rates. These results present better optimization of the used hybrid energy system, satisfying energy demand and reducing the environmental impact.

太阳能PV/T光储直驱热电联产系统性能

面对居民日益增长的生活热水和电能需求,光伏/光热(photovoltaic/thermal,PV/T)技术的应用可以降低建筑运行时的能源消耗。本文介绍了一种太阳能PV/T光储直驱热电联产(combined heat and power,CHP)系统,为了减少系统运行过程中的能量损失,采用直流压缩机和储能电池,并在兰州地区对系统的运行性能开展了实验测试。研究结果表明,PV/T系统的光伏板温度相比传统PV组件温度平均降低12.26℃,平均发电效率相对提升8.1%。在将24.4~27.2℃的水加热到50.1~50.7℃的过程中,平均性能系数(coefficient of performance,COP)可达到5.48,相比传统空气源热泵热水器提高82.1%~106.8%。平均集热效率和综合效率分别为37.30%和71.24%,PV/T系统的发电量和耗电量分别为3.33kWh和1.69kWh,发电量相比PV系统提高5.7%。太阳能PV/T光储直驱热电联产系统可以减少建筑部门的能源消耗,并提升PV/T系统的发电效率和综合效率,在晴天条件下可以实现离网运行。

An Explosive Organic/Inorganic Hybrid: Synthesis and Thermal Property of Octa(2,4-dinitrophenyl)silsesquioxane

Octaphenylsilsesquioxane(OPhS) was prepared by a modifying method and a new core-shell nanocomposite, octa(2,4-dinitrophenyl)silsesquioxane, [(R_2PhSiO_ 1.5)_8, R=—NO_2, ODNPhS], was synthesized by nitration of OPhS in a mixed acid solution of nitric and sulfuric acids at about 60 ℃. Their molecular structures were determined by DRIFTS, 1H NMR, 13C NMR spectra analysis. The thermal analysis shows that ODNPhS is an explosive that detonates at about 420 ℃.

Thermal conductivity of natural rubber nanocomposites with hybrid fillers

Natural rubber nanocomposites filled with hybrid fillers of multi-walled carbon nanotubes(CNTs) and carbon black(CB) were prepared. CNTs were ultrasonically modified in mixture of hydrogen peroxide(H2O2) and distilled water(H2O). The functional groups on the surface of CNTs, changes in nanotube structure and morphology were characterized by Fourier transform infrared spectroscopy(FT-IR), Raman Spectroscopy, and transmission electron microscopy(TEM). It shows that hydroxyl(OH·) is successfully introduced. The surface defects of modified CNTs were obviously higher than those of original CNTs, and the degree of agglomeration was greatly reduced. Thermal conductivity of the composites was tested by protection heat flow meter method. Compared with unmodified CNTs/CB filling system, the thermal conductivity of hybrid composites is improved by an average of 5.8% with 1.5 phr(phr is parts per hundred rubber) of hydroxyl CNTs and 40 phr of CB filled. A three-dimensional heat conduction network composed of hydroxyl CNTs and CB, as observed by TEM, contributes to the good properties. Thermal conductivity of the hybrid composites increases as temperature rises. The mechanical properties of hybrid composites are also good with hydroxyl CNTs filled nanocomposites;the tensile strength, 100% and 300% tensile stress are improved by 10.1%, 22.4% and 26.2% respectively.

Hybrid MPPT approach using Cuckoo Search and Grey Wolf Optimizer for PV systems under variant operating conditions

Photovoltaic(PV)systems are adversely affected by partial shading and non-uniform conditions.Meanwhile,the addition of a bypass shunt diode to each PV module prevents hotspots.It also produces numerous peaks in the PV array’s power-voltage characteristics,thereby trapping conventional maximum power point tracking(MPPT)methods in local peaks.Swarm optimization approaches can be used to address this issue.However,these strategies have an unreasonably long convergence time.The Grey Wolf Optimizer(GWO)is a fast and more dependable optimization algorithm.This renders it a good option for MPPT of PV systems operating in varying partial shading.The conventional GWO method involves a long conversion time,large steady-state oscillations,and a high failure rate.This work attempts to address these issues by combining Cuckoo Search(CS)with the GWO algorithm to improve the MPPT performance.The results of this approach are compared with those of conventional MPPT according to GWO and MPPT methods based on perturb and observe(P&O).A comparative analysis reveals that under non-uniform operating conditions,the hybrid GWO CS(GWOCS)approach presented in this article outperforms the GWO and P&O approaches.

Thermal Conductivity Enhancement of Epoxy by Hybrid Particulate Fillers of Graphite and Silicon Carbide

This paper reports thermal conductivity studies carried out on room temperature cure (RT) epoxy resin (LY556 + HY951) containing three different particulate fillers such as Graphite (Gr) a soft material, Silicon carbide (SiC) a hard material and a hybrid graphite & silicon carbide (Gr-SiC). The weight fractions of three different fillers were varied from 10 wt% to 40 wt% in steps of 10%. Increased filler fraction increases the thermal conductivity of epoxy composites for all the three types of fillers. The results show that the synergic effect of hybrid filler (Gr-SiC) improves the thermal conductivity of epoxy composites compared to that of Graphite or Silicon carbide. The improvement in thermal conductivity for the epoxy hybrid composite containing 20% SiC, 20% Gr and 60% epoxy is 136% when compared with neat epoxy. Significant improvement in the thermal conductivity is observed for 40% filled epoxies. The experimental results were compared with analytical models such as Maxwell, Hashin, Hamilton-Crosser, Nielsen, and Cheng-Vachon. The predicted thermal conductivity by analytical models is in agreement with experimental results.

Design of Real Time Battery Management Unit for PV-Hybrid System by Application of Coulomb Counting Method

This paper presents a real-time battery management unit designed by applying the Coulomb counting method and intended for use in an integrated renewable energy system for PV-Hybrid power supply. Battery management is required to stabilize hybrid systems and extend battery lifetimes. The battery management unit is divided into three main stages. Firstly, analysis of the basic components of the battery type used in the system is considered. Secondly, the state of charge (SOC) estimation method and the deterioration factor of the battery are analyzed. Finally, the overall battery management system, including a computer-based measurement and control unit, is constructed. The control system displays real-time information through LabVIEW 8.5 by estimating the state of charge through various measurements. The system will issue alerts when malfunctions are detected, and the operator can analyze and react to the system in real time to stabilize the system and extend the battery lifetime.

Three thermal analysis models for laser, GMAW-P and Iaser＋GMAW-P hybrid welding

The temperature fields and the weld pool geometries for laser ＋ GMAW-P hybrid welding, laser welding and pulsed gas metal arc welding （GMAW-P） are numerically simulated in quasi-steady state by using the developed heat source models, respectively. The calculated weld cross-sectious of the three types of welding processes agree well with their respective measured results. Through comparison, it is found that the temperature distribution of laser＋GMAW-P hybrid welding possesses the advantages of those in both laser and GMAW-P welding processes so that the improvement of welding productivity and weld quality are ensured.

The Effects of Stacking Sequence on Dynamic Mechanical Properties and Thermal Degradation of Kenaf/Jute Hybrid Composites

This research focused on the dynamic mechanical and thermal properties of woven mat jute/kenaf/jute(J/K/J)and kenaf/jute/kenaf(K/J/K)hybrid composites.Dynamic mechanical analysis(DMA)and Thermo-gravimetric Analysis(TGA)were used to study the effect of layering sequence on the thermal properties of kenaf/jute hybrid composites.The DMA results;it was found that the differences in the stacking sequence between the kenaf/jute composites do not affect their storage modulus,loss modulus and damping factor.From the TGA and DMA results,it has been shown that stacking sequence has given positive effect to the kenaf/jute hybrid composite compared to pure epoxy composite.This is because kenaf and jute fibre has increased the Tg values of the composites,thus affect the thermal degradation.Results showed that the storage modulus for kenaf/jute hybrid composites increased compared with pure epoxy composites with increasing temperature and the values of remained almost the same at glass transition temperature(Tg),the hybrid composite perhaps due to the improved fibre/matrix interface bonding.The preliminary analysis could provide a new direction for the creation of a novel hybrid composite which offers unique properties which cannot be accomplished in a single material system.

Modeling of thermal conductivity and density of alumina/silica in water hybrid nanocolloid by the application of Artificial Neural Networks

In this research work, the thermal conductivity and density of alumina/silica(Al_2O_3/SiO_2) in water hybrid nanofluids at different temperatures and volume concentrations have been modeled using the artificial neural networks(ANN). The nanocolloid involved in the study was synthesized by the two-step method and characterized by XRD, TEM, SEM–EDX and zeta potential analysis. The properties of the synthesized nanofluid were measured at various volume concentrations(0.05%, 0.1% and 0.2%) and temperatures(20 to 60 °C). Established on the observational data and ANN, the optimum neural structure was suggested for predicting the thermal conductivity and density of the hybrid nanofluid as a function of temperature and solid volume concentrations. The results indicate that a neural network with 2 hidden layers and 10 neurons have the lowest error and a highest fitting coefficient o thermal conductivity, whereas in the case of density, the structure with 1 hidden layer consisting of 4 neurons proved to be the optimal structure.

Feasibility Study of a Hydro PV Hybrid System Operating at a Dam for Water Supply in Southern Brazil

Dams for water supply usually represent an untapped hydroelectric potential. It is a small energetic potential, in most situations, usually requiring a particular solution to be viable. The use of pumps as power turbines often represents an alternative that enables the power generation in hydraulic structures already in operation, as is the case of dams in water supply systems. This potential can be exploited in conjunction with the implementation of PV modules on the water surface, installed on floating structures, both operating in a hydro PV hybrid system. The floating structure can also contribute to reducing the evaporation of water and providing a small increase in hydroelectric power available. This paper presents a pre-feasibility study for implementation of a hydroelectric power plant and PV modules on floating structures in the reservoir formed by the dam of Val de Serra, in southern Brazil. The dam is operated to provide drinking water to about 60% of the population of the city of Santa Maria, in the state of Rio Grande do Sul, in southern Brazil. The pre-feasibility study conducted with Homer software, version Legacy, indicated that the hydroelectric plant with a capacity of 227 kW can operate together with 60 kW of PV modules. This combination will result (in one of the configurations considered) in an initial cost of USD$ 1715.83 per kW installed and a cost of energy of USD$ 0.059/kWh.

Hybrid model based on K-means++ algorithm, optimal similar day approach, and long short-term memory neural network for short-term photovoltaic power prediction

Photovoltaic(PV) power generation is characterized by randomness and intermittency due to weather changes.Consequently, large-scale PV power connections to the grid can threaten the stable operation of the power system. An effective method to resolve this problem is to accurately predict PV power. In this study, an innovative short-term hybrid prediction model(i.e., HKSL) of PV power is established. The model combines K-means++, optimal similar day approach,and long short-term memory(LSTM) network. Historical power data and meteorological factors are utilized. This model searches for the best similar day based on the results of classifying weather types. Then, the data of similar day are inputted into the LSTM network to predict PV power. The validity of the hybrid model is verified based on the datasets from a PV power station in Shandong Province, China. Four evaluation indices, mean absolute error, root mean square error(RMSE),normalized RMSE, and mean absolute deviation, are employed to assess the performance of the HKSL model. The RMSE of the proposed model compared with those of Elman, LSTM, HSE(hybrid model combining similar day approach and Elman), HSL(hybrid model combining similar day approach and LSTM), and HKSE(hybrid model combining K-means++,similar day approach, and LSTM) decreases by 66.73%, 70.22%, 65.59%, 70.51%, and 18.40%, respectively. This proves the reliability and excellent performance of the proposed hybrid model in predicting power.