Manufacturer Datasheet Research Articles

Modelling and characterization of photovoltaic modules using iterative and analytical methods

A major problem in analyzing a photovoltaic system is the modeling and extraction of its electrical parameters. Unfortunately, these parameters are inherently non-linear, which is difficult to solve. This article presents a comparative study of methods for estimating electrical parameters based on the manufacturer's datasheet for different PV module technologies, using the five-parameter single diode model. The paper investigates five models belonging to two different approaches, iterative methods and analytical methods, and presents the detailed mathematical analysis leading to the development of each technique. Furthermore, the performance of these methods is evaluated at STCs as well as varying climatic operation conditions, using different technologies, such as monocrystalline, polycrystalline, and thin-film models. In addition, a statistical analysis is performed to assess the quality of models fitted to the experimental data. The results indicate that the precision obtained varies in function of the model and the PV technology, hence the user's choice of the appropriate model according to the field of application. The present work aims to allow researchers and designers to opt for the best possible model for the extraction of the parameters according to the technology of the photovoltaic module.

Modeling and Performance Analysis of Simplified Two-Diode Model of Photovoltaic Cells

For a quick and consistent photovoltaic (PV) module design, an effective, fast, and exact simulator is crucial to examine the performance of the photovoltaic cell under partial or quick variation of temperature and irradiance. The most prevalent modeling strategy is to apply an equivalent (electrical) circuit that encompasses together non-linear and linear mechanisms. This work proposes the modeling and analysis for a four-parameter two-diode photovoltaic cell model based on the manufacturer's data-sheet. The proposed model needs only four parameters compared to the previously developed seven-parameter two-diode model to reduce the computational complexity. To develop a specific model of photovoltaic cells, the fundamental requirement is the data of temperature and irradiance. The variation of these variables totally affects the output constraints like current, voltage, and power. Thus, it is substantial to design a precise model of the photovoltaic cell module with a reduced computation period. The two-diode photovoltaic module with four constraints is identified to be more accurate and have improved performance compared to a one-diode model particularly at lower irradiance. To confirm the accuracy of the proposed model the method is applied on two different photovoltaic modules. The proposed model and modeling method are helpful for power electronic designers who require a fast, accurate, simple, and easy to implement method for use in photovoltaic system simulation. The electrical equivalent circuit and standard equations of photovoltaic cells are analyzed and the proposed two-diode model is simulated using MATLAB/Simulink software and validated for poly-crystalline and mono-crystalline solar cells under standard test conditions.

Maximum Power Tracking for a Wind Energy Conversion System Using Cascade-Forward Neural Networks

The demand for wind turbines has been ultimately increased over the last decades. Accordingly, the power converter controller plays the primary role in extracting energy out of the generator, using efficient and reliable techniques as Maximum Power Extraction (MPE) and delivering the power to the grid. This research pursues to present a Cascade-Forward Neural Network (CFNN) MPE that maintains the MPE's advantages besides providing the flexibility of limiting the output power at significantly lower complexity in the control loop. The proposed strategy uses the cascade-forward neural network to learn the wind turbine's aerodynamic nonlinear dynamics and achieves accurate power tracking. Additionally, it reformulates the machine d-q axes voltages equations to operate the wind energy conversion systems (WECS) in optimal condition by considering the wind speed, air temperature, power demand, and disturbances. Furthermore, it does not require any tuning procedure. The power tracking performance of the recommended CFNN MPE controller is evaluated through several experimental and simulation tests in different situations, and all the results are matched with the manufacturer's datasheets and another proven strategy to confirm its effectiveness.

The effect of the grain size distribution (GSD) on the light emission performance of phosphor-based X-ray detectors

The light emission performance of indirect, phosphor-based, X-ray detectors has significantly affected image quality and diagnostic validity of the medical imaging examinations. This issue has been investigated by examining and further understanding the optical anisotropy in optical diffusion mechanisms. One crucial parameter of phosphor's structural properties that remarkably changes light distribution is the size of the phosphor particles. Up to now, the vast majority of studies have been carried out considering phosphor materials consisted of grains of equal size. In the present article an attempt is made to investigate the influence of grain size distribution (GSD) on light emitting characteristics and compare it with the condition of mean values assumptions. Our investigation was based on LIGHTAWE Monte Carlo simulation code with purpose to examine the Gd2O2S:Tb phosphor layer extracted from a mammographic Kodak Min-R 2 Cassette. The GSD was determined via scanning electron microscopy (SEM). Three cases of mean values were taken into account: (i) 1.48 μm obtained calculations of the aforementioned GSD, (ii) 2.50 μm and 7.00 μm taken from previous articles and manufacturer datasheets. Light emission was performed under different irradiation conditions (i. e., light quanta are produced by light source or an X-ray beam) and in terms of light amount and distribution. Our investigation showed that the optical distribution in real GSD was found: (a) sharper than the calculated mean value of the GSD and (b) broader than the mean value taken from the manufacturer datasheet. In particular, the deviation of GSD was found significantly high compared to 7.00 μm mean value. Examining the spatial resolution properties of both conditions, the deviation was around 16.5%, 18.2%, 14.8% assuming that the light source is situated within the phosphor mass, an X-ray beam of 20 keV and X-ray beam of 30 keV, respectively.

Vortex Search Algorithm Applied to the Parametric Estimation in PV Cells Considering Manufacturer Datasheet Information

This paper addresses the problem of parametric estimation in solar cells considering manufacturer datasheet information regarding open-circuit, short-circuit, and maximum power points from the point of view of mathematical optimization. To represent this problem a single-objective function is formulated associated with the minimization of the mean square error of the single-diode model evaluated in the operational points reported by the manufacturer. The solution of this nonlinear non-convex optimization model is addressed with a metaheuristic optimization technique known in specialized literature as a vortex search algorithm (VSA). This metaheuristic optimization method works with Gaussian distribution functions and variable radius to explore and exploit the solution space by generating hyperspheres that move through the solution space as a function of the best current solution. The VSA is implemented in MATLAB environment by using commercial photovoltaic module information, where numerical results demonstrate the efficiency of this optimization method with objective functions lower than 1times10-25 and processing times around 6.13s.

Per-phase spatial correlated damage models of UD fibre reinforced composites using mean-field homogenisation; applications to notched laminate failure and yarn failure of plain woven composites

A micro-mechanical model for fibre bundle failure is formulated following a phase-field approach and is embedded in a semi-analytical homogenisation scheme. In particular mesh-independence and consistency of energy release rate for fibre bundles embedded in a matrix phase are ensured for fibre dominated failure. Besides, the matrix cracking and fibre-matrix interface debonding are modelled through the evolution of the matrix damage variable framed in an implicit non-local form. Considering the material parameters of both fibre and epoxy matrix phases identified from manufacturer data sheets, it is shown that the failure strength of a ply loaded along the longitudinal direction is in agreement with the reported values. Finally, the multi-damage homogenisation framework is applied to model, on the one hand, the failure of a notched laminate, in which case the failure modes are observed to be in good agreement with experiments, and, on the other hand, the failure of yarns in a plain woven composite unit-cell under uni-axial tension.

The effect of super-sized passenger vehicles on walking and cycling

BACKGROUND AND AIM: Passenger vehicles are putting on weight world-wide. We aim to estimate the effects of this trend on the safety and attractiveness of walking and cycling in cities, focussing especially on the spectacular rise of the light truck (known as a double cab ute in New Zealand). METHODS: Review of relevant literature, analysis of secondary data sets including new vehicle sales, the New Zealand Household Travel Survey and manufacturer data sheets, police crash data, thematic analysis of advertising and product promotion, ad hoc roadside survey. RESULTS:Light truck and SUV sales are increasing rapidly in most countries. Mostly these vehicles are promoted for carrying, towing and exploring off road. Travel surveys show that in fact most trips are not work-related and do not require special towing and carrying capacity. On the whole these vehicles seldom go off-road but are commonly used in cities for car-like trips, with higher emissions of NOx and CO2. With increasing mass and power, injury rates amongst occupants are falling, but the risk to other road users may be increasing: a pedestrian struck at ≥50 kph by a ute or SUV in New Zealand is 2.3 times more likely to be fatally injured than if struck by a car. The most popular ute in New Zealand (the Ford Ranger) occupies 30% more road space than the most popular car, and therefore more commonly obstructs footpaths and bike lanes and leaves a smaller gap when passing on narrow city streets. CONCLUSIONS:Passenger vehicles in New Zealand and many other countries are super-sizing: increased pollution, greater injury risk, and domination of road space make it even more difficult to promote walking and cycling in cities. KEYWORDS: active transport, physical activity, injury

System-Independent Irradiance Sensorless ANN-Based MPPT for Photovoltaic Systems in Electric Vehicles

The integration of photovoltaic systems (PVS) in electric vehicles (EV) increases the vehicle’s autonomy by providing an additional energy source other than the battery. However, current solar cell technology generates around 200 W for a 1.4 m2 panel (to be installed on the roof of the EV) at stable irradiance conditions. This limitation in production and the sudden changes in irradiance produced by shadows of clouds, buildings, and other structures make developing a fast and efficient maximum power point tracking (MPPT) technique in this area necessary. This article proposes an artificial neural network (ANN)-based MPPT, called DS-ANN, that uses manufacturer datasheet parameters as inputs to the network to address this problem. The Bayesian backpropagation-regularization performs the training, ensuring that the MPPT technique operates satisfactorily on different PVS without retraining. We simulated the response of 20 commercial modules against actual irradiance data to validate the proposed method. The results show that our method achieves an average tracking efficiency of 99.66%, improving by 1.21% over an enhanced P&O method.

PV Cell Parameters Modeling and Temperature Effect Analysis

With the wide acceptance of modeling a PV cell by a single diode, a series and parallel resistors; many researchers have discussed different mathematical forms and iterative techniques to extract the values of these model elements depending on the key parameters provided by the manufacturer datasheet. This paper avoids iterative techniques and obtains the values of the five parameters of the one diode model by developing closed form expressions. The maximum error produced by this technique is 10% when compared to the exact values of the one diode model circuit built by Spice. The 10% maximum error has occurred during the estimation of the reverse saturation current (Io) of the diode, nevertheless, it should be mentioned that even for this same parameter the model outperforms many iterative dependent works. Furthermore, this paper discusses the effect of temperature on the operation performance of PV cells. In particular, the temperature effect on the open circuit voltage, the short circuit current, the fill factor, the reverse saturation current, and the conversion efficiency was modeled and evaluated for different brand technologies

A separable nonlinear least squares approach for double-diode photovoltaic model parameter extraction

Parameter extraction of the double-diode photovoltaic model is a highly nonconvex optimization problem, and up until now, many metaheuristic methods have been proposed to try to avoid local minima. However, these metaheuristic methods will output different results in repeated tests and need to manually set lower and upper bounds for all parameters. In this work, a deterministic numerical method is proposed for the double-diode model parameter extraction through a separable nonlinear least squares approach. In this approach, the complexity of the optimization problem is greatly lowered by the reduction of independent parameters, and the solution can be easily obtained by deterministic search algorithms without manual preset or intervention. The proposed method is first validated on two commonly used case studies of curve data fitting, showing a comparable performance to the best reported metaheuristic methods. Then, the method is extended to parameter extraction from manufacturer datasheets, in which only three important I–V data points are available. Finally, the method is tested on a large-scale dataset containing more than one million I–V curves provided by the National Renewable Energy Laboratory (NREL). The result of the large-scale test proves the superiority of the double-diode model over the single-diode counterpart in precise modeling of photovoltaic modules.

Serum iPTH range in a reference population: From an integrated approach to vitamin D prevalence impact evaluation

BackgroundThe iPTH upper reference limit (URL) reported by our laboratory provider (Abbott Laboratories) at Tor Vergata University Hospital was evaluated by internal verification procedures as not representative of our population and resulting as underestimated. In this study, a new reference interval has been investigated and established by comparing a direct and an indirect method based on a statistical reduction from results stored in the laboratory database. MethodsFor reference interval calculation from the healthy population, we analyzed a cohort of 100 blood donors (84% males and 16% females) screened with no bone-related and malabsorption diseases. We analyzed a cohort of 495 patients retrieved from more than 800 iPTH results by excluding subjects with pathological measurement for calcium, phosphorus, and creatinine for the reference interval evaluation. Patients with vitamin D results were included in the analysis. Vitamin D sufficiency status during the period from January to September 2020 was also evaluated by investigating 3,050 patients. ResultsThe iPTH reference interval of a healthy blood donor population was measured as 25.2–109.1 pg/mL (2.7–11.6 pmol/L) at 2.5 and 97.5 distribution percentile. The iPTH reference interval from data stored in the laboratory database was 19.3–112.5 pg/mL (2.0–11.9 pmol/L). Furthermore, 60% of the whole population had prevalently insufficient vitamin D concentration (<30 ng/dL; <75 nmol/L).The impact of vitamin D concentration on the iPTH reference interval was measured for insufficient vitamin D (<30 ng/dL; <75 nmol/L) as 15.2–127.7 pg/mL (1.6–13.5 pmol/L), desirable vitamin D (30–40 ng/ml; 75–100 nmol/L) as 25.6–105 pg/mL (2.7–10.7 pmol/L) and optimal vitamin D (>40 ng/ml; >100 nmol/L) as 26.2–89.2 pg/mL (2.8–9.4 pmol/L), respectively. ConclusionsThe URL reported in manufacturer datasheets likely refers to a normal population with non-pathological vitamin D levels. On the contrary, the considered population was mostly vitamin D insufficient, resulting in a URL shift. On this basis, we suggest describing in medical reports the iPTH range for vitamin D deficiency for diagnosis of primary hyperparathyroidism even when a specific vitamin D request is lacking. On the other hand, reporting optimal vitamin D-based iPTH reference interval could be clinically relevant in supplemented patients as a marker of treatment efficacy.

A new emperor penguin optimisation‐based approach for solar photovoltaic parameter estimation

Mathematical model parameter estimation of solar photovoltaic (PV) cell, module and array represent a prodigious challenge in recent researches, where analytical, metaheuristic and hybrid techniques play a vital role for parameter extraction by using manufacturer's datasheet and experimental data, although the precise and highly reliable solution identification is still a complex problem to be solved. In this paper, a new Emperor Penguin Optimisation- (EPO) based parameter estimation approach for a single-diode Rp solar PV model is presented that is cohesively analysed under different sets of temperature and irradiance (G). Validation of the proposed technique is perceived on the analysis of performance characteristics, that is, current-voltage (I-V) and power-voltage (P-V) of KC200GT, PWP201, and STP6 120-36 PV modules under various simulation conditions. Moreover, estimated results are compared with the experimental data and several established estimation techniques in the literature for validation and demonstrate the proposed technique with highly precise outcomes having reduced computational cost for the PV model parameter extraction problem.

Impact of Test Conditions While Screening Lithium-Ion Batteries for Capacity Degradation in Low Earth Orbit CubeSat Space Applications

A wide variety of commercial cylindrical lithium-ion batteries are available for use in nanosatellites (CubeSats) that cycle in low Earth orbit (LEO). This space application differs greatly from the conditions used to create the manufacturer datasheets that CubeSat teams rely on to screen cell types and estimate performance lifetimes. To address this, we experimentally test three LIB cell types using a representative LEO CubeSat power profile in three progressively complex test representations of LEO. The first is “standardized” condition (101 kPa-abs, 20 °C), which uses only a power cycler; the second adds a thermal chamber for “low temperature” condition (101 kPa-abs, 10 °C); and the third adds a vacuum chamber for “LEO” condition (0.2 kPa-abs, 10 °C). Results indicate that general “standardized” and “low temperature” conditions do not yield representative results to what would occur in LEO. Coincidentally, the “LEO” condition gives similar capacity degradation results as manufacturer datasheets. This was an unexpected finding, but suggests that CubeSat teams use full experimental thermal-vacuum testing or default to the manufacturer datasheet performance estimates during the lithium-ion cell screening and selection process. The use of a partial representation of the LEO condition is not recommended.

DEVELOPMENT AND TESTING OF ELECTRO HYDRAULIC WAVE ENERGY SIMULATOR

The present work focuses on developing an experimental system that can generate mechanical simulation movement to the real waves. This developed system will facilitate the researchers within the lab testing unit for evaluating any developed point absorber WEC. Mathematical modeling, construction, and testing of Electro-Hydraulic Wave Simulator that emulates different waveforms are presented. This system provides a realistic way of testing replacing the more expensive methods used to test WECs such as large indoor water tanks or real sea. A low-speed oscillation motion with higher torque is successfully produced by the developed system that is coupled to an electrical generator with a grid frequency. Finally, the model is being validated with experimental data to evaluate model accuracy, where a maximum error of ±0.2% is achieved. A response time of 0.004 s was achieved by the valve model which matched with the manufacturer datasheet. The simulated cylinder position gives a good agreement with the measured position for a step input of 50 cm with a position error of less than 10 mm.

Gradient-Based Optimizer for Parameter Extraction in Photovoltaic Models

Solar radiation is increasingly used as a clean energy source, and photovoltaic (PV) panels that contain solar cells (SCs) transform solar energy into electricity. The current-voltage characteristics for PV models is nonlinear. Due to a lack of data on the manufacturer's datasheet for PV models, there are several unknown parameters. It is necessary to accurately design the PV systems by defining the intrinsic parameters of the SCs. Various methods have been proposed to estimate the unknown parameters of PV cells. However, their results are often inaccurate. In this article, a gradient-based optimizer (GBO) was applied as an efficient and accurate methodology to estimate the parameters of SCs and PV modules. Three common SC models, namely, single-diode models (SDMs), double-diode models (DDMs), and three-diode models (TDMs) were used to demonstrate the capacity of the GBO to estimate the parameters of SCs. The proposed GBO algorithm for estimating the optimal values of the parameters for various SCs models are applied on the real data of a 55 mm diameter commercial R.T.C-France SC. Comparison between the GBO and other algorithms are performed for the same data set. The smallest value of the error between the experimental and the simulated data is achieved by the proposed GBO. Also, high closeness between the simulated P-V and I-V curves is achieved by the proposed GBO compared with the experimental.

Experimental and simulation investigations of CPV/TEG hybrid system

Concentrator photovoltaic (CPV) technology is a leading approach for increasing the utilization and deployment of PV systems. A major disadvantage is the need for cooling to maintain the performance of the solar cell. Active cooling is power-consuming and complex. A proposed passive cooling subsystem, uses a thermoelectric generator (TEG), besides cooling the solar cell, it generates power from waste heat. Three TEG modules with different sizes and numbers of junctions were tested. The performance of the TEGs was simulated using the finite element method and heat transfer analysis. The simulated model was validated for each TEG against the manufacturer datasheet and demonstrated good agreement between the simulated and measured performances. A CPV/TEG hybrid system was investigated experimentally and compared with the obtained simulation results. The proposed system was proven to deliver a net electrical power higher than obtained using the CPV system only. Compared to only a CPV cell on top of a heat sink, the generated power of the CPV/TEG hybrid system increased by 7.4%, 5.8%, and 3% corresponding to using the 30×30mm2, 40×40mm2 and the 62×62mm2 TEG modules, for which the number of junctions are 31, 127 and 49, respectively.

Estimation of the photovoltaic cells/modules parameters using an improved Rao-based chaotic optimization technique

One of the most important challenges issues while addressing the industrial applications of solar photovoltaic systems is to predict the performance of a photovoltaic system since the current–voltage and power-voltage characteristics are highly nonlinear. Note that the majority of manufacturer's data sheets do not provide full information about internal parameters of photovoltaic systems which are crucial to simulate an accurate photovoltaic module. As a major alternative for parameters' extraction of solar photovoltaic cells/modules, mathematical based optimization and global research techniques are more suitable compared with other methods. In this context, a new optimization method is proposed in this paper to extract the parameters of solar photovoltaic cells/modules of different technologies while providing an accurate representation of the current–voltage and power-voltage curves. For this purpose, the proposed optimization algorithm is based on a chaotic generator combined with the newly developed Rao-1 optimization algorithm to extract the photovoltaic parameters. A comparative performance analysis shows that the proposed optimization algorithm with a chaotic based search sequence has better performance in terms of robustness and accuracy while extracting the photovoltaic parameters than many recent well-known optimization algorithms. Further, comprehensive results show that the double diode model is more accurate to estimate the appropriate values of the model's parameters.

Equine influenza vaccination in the UK: Current practices may leave horses with suboptimal immunity.

BackgroundVaccination is integral to preventive healthcare. Despite numerous guidelines on equine vaccination, evidence of current vaccination practices is lacking.ObjectivesTo describe current vaccination practices advised by vets treating horses in the United Kingdom (UK) and compare practices with manufacturer datasheets and current guidelines.Study designCross‐sectional survey.MethodsAn online questionnaire was distributed using email addresses acquired through professional registration listings and social media, targeting vets who treat horses in the UK. The questionnaire collected demographic data and information regarding vaccination practices and vaccine hesitancy. Descriptive statistical analysis was performed.ResultsQuestionnaires were completed by 304 UK vets working with horses used for leisure (97.4%, n = 296/304), competition (86.2%, n = 262/304), stud‐work (47.7%, n = 145/304) and racing (40.5%, n = 123/304). Variation was identified in vaccine protocols for competition and noncompetition horses. Fifty‐seven per cent (n = 170/298) of respondents reported variation in advised ‘booster’ frequency; most commonly (n = 118) advising a 6‐monthly vaccination in competition horses and annual vaccination in noncompetition horses. Most common vaccination guidelines volunteered were British Horseracing Authority (68.8%, n = 172/250) and Federation Equestre Internationale (66.4%, n = 166/250). Most vaccination practices were not consistent with datasheet guidance. Only 7.7% (n = 23/300) of respondents complied with datasheet timeframes between the second and third vaccination. Adverse events following vaccination in the previous year were encountered by 66% (n = 199/304) of respondents, representing 2760 adverse events; but only 526 (19.1%) cases were reported to the Veterinary Medicines Directorate. Most common reactions were transient, including stiffness (931), localised swelling (835), lethargy (559) and pyrexia (355). 86.4% respondents reported vaccine hesitancy from horse owners, most commonly due to perception of over‐vaccination, cost and concern regarding adverse events.Main limitationsPotential selection, respondent and recall bias. The recent Equine Influenza (EI) and Equine Herpes Virus (EHV) outbreaks in the UK may have altered responses.ConclusionsCurrent equine vaccination practices, although complying with competition rules, are mostly noncompliant with datasheet guidelines, potentially risking suboptimal immunity.

Comparative Study of Induction Motors of IE2, IE3 and IE4 Efficiency Classes in Pump Applications Taking into Account CO2 Emission Intensity

The high energy intensity of the modern industry and the threat of climate change determine the high urgency of increasing the energy efficiency of electric motors. In this paper, energy consumption, energy costs, payback periods, and CO2 emissions of 75 kW, 4 pole induction motors with direct grid supply in a fixed-speed pump unit are evaluated. Motors of the IE2, IE3, and IE4 efficiency classes according to IEC 60034-30-1 standard are compared in terms of life-time energy savings, payback period, and CO2 emissions. To carry out the analysis, polynomial interpolation of the data from the available manufacturer datasheets of the motors is used. It concluded that even though the initial investment cost of the IE4-motor is higher than that of IE3-motor, the IE4-motor is more profitable if more than 3 years of operation are considered and also provides significant reductions of CO2 emissions. The paper presents a calculation method of the aforementioned indicators which can be useful for companies, researchers, and engineers for quick assessment and selection of technical solutions.

TEG Cascaded Solar PV System with Enhanced Efficiency by Using the PSO MPPT Boost Converter

Thermoelectric generators (TEGs) are used in small power applications to generate electrical energy from waste heats. Maximum power is obtained when the connected load to the ends of TEGs matches their internal resistance. However, impedance matching cannot always be ensured. Therefore, TEGs operate at lower efficiency. For this reason, maximum power point tracking (MPPT) algorithms are utilized. In this study, both TEGs and a boost converter with MPPT were modeled together. Detailed modeling, simulation, and verification of TEGs depending on the Seebeck coefficient, the hot/cold side temperatures, and the number of modules in MATLAB/Simulink were carried out. In addition, a boost converter having a particle swarm optimization (PSO) MPPT algorithm was added to the TEG modeling. After the TEG output equations were determined, the TEG modeling was performed based on manufacturer data sheets. Thanks to the TEG model and the boost converter with PSO MPPT, the maximum power was tracked with a value of 98.64% and the power derived from the TEG was nearly unaffected by the load changes. The power outputs obtained from the system with and without MPPT were compared to emphasize the importance of MPPT. These simulation values were verified by using an experimental setup. Ultimately, the proposed modeling provides a system of TEGs and a boost converter having PSO MPPT.