Direct Temperature Measurements Research Articles

Electrothermal Coupling Model With Distributed Heat Sources for Junction Temperature Calculation During Surges

High junction temperature is usually the main factor leading to device failures in high-power working conditions, such as surges or avalanches. It is of great significance to obtain the junction temperature quickly and accurately. Direct measurement of junction temperature is inconvenient, and usually indirect electrical measurement combined with model calculation is used. An electrothermal coupling junction temperature calculation model with distributed heat sources is proposed in this article. This model can accurately and quickly predict the device behavior during the surge process, as well as the voltage drop and temperature changes of each part of the device, without actually performing surge tests. This article describes the theoretical basis and calculation principles of the model. By taking a commercial SiC merged PiN Schottky diode as an example, this article also explains the details of the establishment of the electrical and thermal characteristic models of the device, as well as the calculation steps of the junction temperature by the thermal coupling model. The calculated device voltage drop curve of the device is in good agreement with the measured ones, and the calculated junction temperature curve is more consistent with the device failure mechanism than the one by the traditional RC thermal circuit model.

Noninvasive platinum thin-film microheater/temperature sensor array for predicting and controlling flow boiling in microchannels

Thermal sensors and actuators are usually introduced at/in micro-channels in two ways: first, in an invasive manner through drilled holes which can lead to leakage problems and a change in channel dimensions and second, mounted in a non-invasive manner outside the channel which reduces heat transfer, accuracy, precision and response time. These problems are multiplied as soon as microchannel boiling with associated rapid thermal effects is investigated. Therefore, in this work, a platinum microheater/temperature sensor array has been developed to provide non-invasive, but nevertheless direct heating and temperature measurement at several locations along microchannels. This array comes without the mentioned disadvantages, resulting in ultra-fast response times that are limited only by the measurement speed of the sensor resistance and linear temperature coefficient of resistance. The working platinum area of each element in the array is only 238 nm thick, 0.1 mm wide and 0.5–2 mm long. The structures can be operated in heating and temperature measurement mode simultaneously. They are integrated into microreactors with the working surface as a side wall of a microchannel and in direct contact with the flowing fluid. Since the structures are deposited on transparent Pyrex glass in a cleanroom process, optical observation of two-phase flow boiling processes is possible for flow regime identification. The maximum operating temperature of the Pt microstructures is 450 °C and the linear temperature coefficient of resistance is about 2.98 × 10−3 °C−1. The relative measurement error of temperature measurements is less than 0.05% due to 2.9 µm thick highly conductive electroplated gold pads which form the electrical contact to the Pt microheaters/T-sensors. The platinum heater structures are capable of generating stationary vapor bubbles with a defined size proportional to the applied heating power. They can also predict two-phase flow boiling regimes (e.g. slug flow), vapor bubble length and frequency via the periodic signal of the measured temperature. Furthermore, they allow accurate calculation of heat transfer coefficients using the exact fluid temperatures measured with the Pt structures at the inlet and outlet of the microchannel, rather than analytically calculated values from temperature measurements outside the channel.

Highly Time Resolved, Combined Temperature, and Heat Flux Measurement Technique Based on ALTP Sensors

Abstract This study demonstrates a new methodology for the simultaneous direct measurement of temperature and heat flux within the same sensing element of heat flux sensors. The methodology is demonstrated for fast-response atomic layer thermopile (ALTP) sensors and makes use of a temperature–resistance correlation. The new methodology enables an inherent comparison and validation of the heat flux density signal of ALTPs. Good agreement is found based on experiments in the stagnation point of a subsonic hot air jet. The results of the mainly convective heat flux densities are compared against a standard coaxial thermocouple, indicating good agreement of mean values and signal characteristics. The simultaneous direct measurement of the temperature and heat flux allows the time-resolved calculation of local heat transfer coefficients and Nusselt numbers. The spectral analysis of the Nusselt number exhibits an excellent signal-to-noise ratio.

Insights Into the Aerodynamic Versus Radiometric Surface Temperature Debate in Thermal‐Based Evaporation Modeling

AbstractGlobal evaporation monitoring from Earth observation thermal infrared satellite missions is historically challenged due to the unavailability of any direct measurements of aerodynamic temperature. State‐of‐the‐art one‐source evaporation models use remotely sensed radiometric surface temperature as a substitute for the aerodynamic temperature and apply empirical corrections to accommodate for their inequality. This introduces substantial uncertainty in operational drought mapping over complex landscapes. By employing a non‐parametric model, we show that evaporation can be directly retrieved from thermal satellite data without the need of any empirical correction. Independent evaluation of evaporation in a broad spectrum of biome and aridity yielded statistically significant results when compared with eddy covariance observations. While our simplified model provides a new perspective to advance spatio‐temporal evaporation mapping from any thermal remote sensing mission, the direct retrieval of aerodynamic temperature also generates the highly required insight on the critical role of biophysical interactions in global evaporation research.

Measuring Skeletal Muscle Thermogenesis in Mice and Rats.

Skeletal muscle thermogenesis provides a potential avenue for better understanding metabolic homeostasis and the mechanisms underlying energy expenditure. Surprisingly little evidence is available to link the neural, myocellular, and molecular mechanisms of thermogenesis directly to measurable changes in muscle temperature. This paper describes a method in which temperature transponders are utilized to retrieve direct measurements of mouse and rat skeletal muscle temperature. Remote transponders are surgically implanted within the muscle of mice and rats, and the animals are given time to recover. Mice and rats must then be repeatedly habituated to the testing environment and procedure. Changes in muscle temperature are measured in response to pharmacological or contextual stimuli in the home cage. Muscle temperature can also be measured during prescribed physical activity (i.e., treadmill walking at a constant speed) to factor out changes in activity as contributors to the changes in muscle temperature induced by these stimuli. This method has been successfully used to elucidate mechanisms underlying muscle thermogenic control at the level of the brain, sympathetic nervous system, and skeletal muscle. Provided are demonstrations of this success using predator odor (PO; ferret odor) as a contextual stimulus and injections of oxytocin (Oxt) as a pharmacological stimulus, where predator odor induces muscle thermogenesis, and Oxt suppresses muscle temperature. Thus, these datasets display the efficacy of this method in detecting rapid changes in muscle temperature.

Monitoring of shear heating effects during injection molding of rubber to improve the process control

This work aims to get new insights into the “process monitoring tool” proposed by the authors for the online monitoring of the shear heating phenomenon during injection molding of technical rubber parts. The online monitoring is based on direct measurement of the surface rubber temperature (shear heating temperature, TSH) by an infrared thermal camera of the rubber as it leaves the extruder barrel of the injection molding machine. The measured rubber temperature is a process indicator giving the thermal history of the rubber compound injection and process safety. Therefore, this fast process control is applied to industrial applications to investigate the processing behavior of ethylene acrylate (AEM) rubber compounds. In particular, the relationships between TSH vs injection pressure, vs injection speed, vs screw speed rotation and vs screw length over diameter ratio (L/D ratio) and vs AEM rubber compound properties variation due to exceeding the shelf life are investigated. The results show that TSH is manly influenced by the screw L/D ratio, followed by injection pressure and screw speed rotation (especially if are set to higher levels), whereas the injection speed is the least effective parameter to reduce TSH. Furthermore, a previously found robust correlation between the shear heating parameter (ηSH) and the minimum torque measured in rheometric laboratory tests (ML) is used to show the noteworthy deviation from the proportional trend when the AEM rubber compound exceeded it shelf life. Therefore, the coefficient of determination of {text{log}}eta_{{{text{SH}}}} vs ML curves provides a good indication of process stability, while it is running.

Global distribution of the hydrocarbon Golden Zone

The presence of sedimentary sequences located at temperatures ranging between 60 and 120 °C has permitted the identification of hydrocarbon accumulation patterns of economic importance. This thermal range is identified as the “Golden Zone”, where there is a potential co-existence of the petroleum system elements that supports a minimal degree of degradation or transformation of hydrocarbons generated from source rocks, mainly in the hydrocarbon expulsion zone from approximately 120 °C–200 °C. The Golden Zone distribution can be represented on maps to help distinguish regions of relevant hydrocarbon potential.This work presents global Golden Zone distribution maps, estimated using a global geothermal gradient model obtained using the Curie Point Depth (CPD) distribution constrained with geothermal gradients from direct wells temperature measurements and a global model of sedimentary thicknesses obtained from data reported by a diverse array of institutions. The Golden Zone maps show the variations in different geotectonic environments. The depth interval for the Golden Zone varies between 500 m and 3000 m for the top and from 1000 m to 5000 m for the base, with thicknesses ranging between 5 and 3000 m.The Golden Zone distribution estimated shows that along active tectonic margins, the sedimentary sequences tend to be thin, located with abrupt contrasts of the basement, and where one or both isotherms that define the Golden Zone are below the basins, preventing its proper development. Exceptions to this trend are in the forelands and some intermountain basins. In contrast, the passive margins are characterized by Golden Zone regions in which the sedimentary sequences present a wide range of thicknesses within basins of diverse ages and extensions.

Chemical abundances in Seyfert galaxies – IX. Helium abundance estimates

ABSTRACT For the first time, the helium abundance relative to hydrogen (He/H), which relied on direct measurements of the electron temperature, has been derived in the narrow line regions (NLRs) from a local sample of Seyfert 2 nuclei. In view of this, optical emission line intensities [3000 < λ(Å) < 7000] of 65 local Seyfert 2 nuclei (z < 0.2), taken from Sloan Digital Sky Survey Data Release 15 and additional compilation from the literature, were considered. We used photoionization model grid to derive an Ionization Correction Factor (ICF) for the neutral helium. The application of this ICF indicates that the NLRs of Seyfert 2 present a neutral helium fraction of ∼50 per cent in relation to the total helium abundance. We find that Seyfert 2 nuclei present helium abundance ranging from 0.60 to 2.50 times the solar value, while ∼85 per cent of the sample present oversolar abundance values. The derived (He/H)–(O/H) abundance relation from the Seyfert 2 is stepper than that of star-forming regions (SFs) and this difference could be due to excess of helium injected into the interstellar medium by the winds of Wolf–Rayet stars. From a regression to zero metallicity, by using Seyfert 2 estimates combined with SFs estimates, we obtained a primordial helium mass fraction Yp = 0.2441 ± 0.0037, a value in good agreement with the one inferred from the temperature fluctuations of the cosmic microwave background by the Planck Collaboration, i.e. $Y_{\rm p}^{\rm Planck}=0.2471\pm 0.0003$.

A daily temperature rhythm in the human brain predicts survival after brain injury.

Patients undergo interventions to achieve a ‘normal’ brain temperature; a parameter that remains undefined for humans. The profound sensitivity of neuronal function to temperature implies the brain should be isothermal, but observations from patients and non-human primates suggest significant spatiotemporal variation. We aimed to determine the clinical relevance of brain temperature in patients by establishing how much it varies in healthy adults.We retrospectively screened data for all patients recruited to the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) High Resolution Intensive Care Unit Sub-Study. Only patients with direct brain temperature measurements and without targeted temperature management were included. To interpret patient analyses, we prospectively recruited 40 healthy adults (20 males, 20 females, 20–40 years) for brain thermometry using magnetic resonance spectroscopy. Participants were scanned in the morning, afternoon, and late evening of a single day.In patients (n = 114), brain temperature ranged from 32.6 to 42.3°C and mean brain temperature (38.5 ± 0.8°C) exceeded body temperature (37.5 ± 0.5°C, P < 0.0001). Of 100 patients eligible for brain temperature rhythm analysis, 25 displayed a daily rhythm, and the brain temperature range decreased in older patients (P = 0.018). In healthy participants, brain temperature ranged from 36.1 to 40.9°C; mean brain temperature (38.5 ± 0.4°C) exceeded oral temperature (36.0 ± 0.5°C) and was 0.36°C higher in luteal females relative to follicular females and males (P = 0.0006 and P < 0.0001, respectively). Temperature increased with age, most notably in deep brain regions (0.6°C over 20 years, P = 0.0002), and varied spatially by 2.41 ± 0.46°C with highest temperatures in the thalamus. Brain temperature varied by time of day, especially in deep regions (0.86°C, P = 0.0001), and was lowest at night. From the healthy data we built HEATWAVE—a 4D map of human brain temperature. Testing the clinical relevance of HEATWAVE in patients, we found that lack of a daily brain temperature rhythm increased the odds of death in intensive care 21-fold (P = 0.016), whilst absolute temperature maxima or minima did not predict outcome. A warmer mean brain temperature was associated with survival (P = 0.035), however, and ageing by 10 years increased the odds of death 11-fold (P = 0.0002).Human brain temperature is higher and varies more than previously assumed—by age, sex, menstrual cycle, brain region, and time of day. This has major implications for temperature monitoring and management, with daily brain temperature rhythmicity emerging as one of the strongest single predictors of survival after brain injury. We conclude that daily rhythmic brain temperature variation—not absolute brain temperature—is one way in which human brain physiology may be distinguished from pathophysiology.

Multi-step ahead soil temperature forecasting at different depths based on meteorological data: Integrating resampling algorithms and machine learning models

Direct soil temperature (ST) measurement is time-consuming and costly; thus, the use of simple and cost-effective machine learning (ML) tools is helpful. In this study, ML approaches, including KStar, instance-based K-nearest learning (IBK), and locally weighted learning (LWL), coupled with resampling algorithms of bagging (BA) and dagging (DA) (BA-IBK, BA-KStar, BA-LWL, DA-IBK, DA-KStar, and DA-LWL) were developed and tested for multi-step ahead (3, 6, and 9 d ahead) ST forecasting. In addition, a linear regression (LR) model was used as a benchmark to evaluate the results. A dataset was established, with daily ST time-series at 5 and 50 cm soil depths in a farmland as models’ output and meteorological data as models’ input, including mean (Tmean), minimum (Tmin), and maximum (Tmax) air temperatures, evaporation (Eva), sunshine hours (SSH), and solar radiation (SR), which were collected at Isfahan Synoptic Station (Iran) for 13 years (1992–2005). Six different input combination scenarios were selected based on Pearson's correlation coefficients between inputs and outputs and fed into the models. We used 70% of the data to train the models, with the remaining 30% used for model evaluation via multiple visual and quantitative metrics. Our findings showed that Tmean was the most effective input variable for ST forecasting in most of the developed models, while in some cases the combinations of variables, including Tmean and Tmax and Tmean, Tmax, Tmin, Eva, and SSH proved to be the best input combinations. Among the evaluated models, BA-KStar showed greater compatibility, while in most cases, BA-IBK and -LWL provided more accurate results, depending on soil depth. For the 5 cm soil depth, BA-KStar had superior performance (i.e., Nash-Sutcliffe efficiency (NSE) = 0.90, 0.87, and 0.85 for 3, 6, and 9 d ahead forecasting, respectively); for the 50 cm soil depth, DA-KStar outperformed the other models (i.e., NSE = 0.88, 0.89, and 0.89 for 3, 6, and 9 d ahead forecasting, respectively). The results confirmed that all hybrid models had higher prediction capabilities than the LR model.

Kendali Sistem Tegangan Baterai Peralatan 20 kV PT PLN Bontang

The protection system is essential in the 20 kV distribution network system. The 20 kV equipment control system is supplied from 2 sources: PT (Potential Transformer) and DC voltage supply (Battery). If the protection relay and mechanics do not get a DC voltage supply, it will have an impact on the equipment not being able to trip when there is a disturbance in the network. There is no DC voltage supply due to battery failure or damage. For this reason, it is necessary to operate the tool manually, which results in the normalization process taking longer because it takes time and long distances, so the duration of outages is even greater. In this study, a monitoring system for the battery of the equipment will be made where previously observations were made about the need for this tool. The method used by the tool uses the blynk application as a receiver of direct voltage and temperature measurement reports that are connected to the gsm module. As a microcontroller processes, Arduino Nano commands from intelligent phones, generating a measurement report from the battery. GSM SIM 900 module as a data receiver and sender in the system. This tool is easy to apply to the system because it does not require a sufficient additional voltage source from the battery. The results of this study become a solution for companies to improve their 20 kV. distribution network system.

Fast Analytical Approaches for the Transient Axial Temperature Distribution in Single Wire Cables

In various technical areas, the requirements and the complexity of electrically conductive structures (cables and printed circuit board traces) and their insulating materials are increasing, which leads to higher demands on reliability. Therefore, better diagnosis and control functions are needed. Intelligent fusing strategies with electronic fuses, where the current flow can be switched by semiconductors, can play an important role. One approach is to monitor the insulation temperature in order to detect thermal overloads and switch off a current branch before the insulation is damaged. As especially in cables, a direct temperature measurement is troublesome, most approaches are based on current measurements. From a measured current, the cable insulation temperature can be derived using an electrothermal model. Those models can be very complex, especially when the transient and axial heat flow in a cable should be considered. The computational efforts for the commonly used numerical solution methods are high. Analytical approaches potentially reduce these efforts significantly. In this article, a new analytical approach for the calculation of the transient axial temperature distribution along an insulated single wire cable, considering the nonlinear temperature dependence of the cable parameters, is presented. It enables a precise and fast calculation of cable temperatures, e.g., for automotive cable harnesses. There it can be beneficial for the control of electronic fuses where computing resources are low. The cable insulation can be operated closer to the limits and the overload protection can still be guaranteed.

Spatially resolved direct gas-phase thermometry in chemical reactors using NMR

In the last decade, in-situ studies using nuclear magnetic resonance (NMR) showed the possibility to monitor local transport phenomena of gas-phase reactions inside opaque structures. While spatial species concentration is known to be accessible operando during heterogeneously catalyzed gas-phase reactions, the spatial acquisition of gas temperatures has proven to be challenging. So far, temperature information is gathered by auxiliary liquid-filled capillaries with temperature-dependent NMR-properties. Here, we present a method for spatially resolved temperature and density measurements of gases using the temperature dependence of the signal amplitude and the longitudinal relaxation time (T1). In order to support the proposed method, temperature measurements of methane-filled tubes are carried out and compared to state-of-the-art temperature measurements using glycerol-filled capillaries. To demonstrate the applicability of the method during heterogeneously catalyzed gas-phase reactions, we measured the temperature operando inside a catalytically active honeycomb structure at standard pressure. The results show that direct temperature measurements of gases are possible, even though the low pressure inside the methane-filled tubes led to a low signal-to-noise ratio which compromised the accuracy of the data yielding relative errors of up to 7 %. This study focusses on temperature measurements of pure methane only. When applied to mixtures of gases, however, the proposed method has the potential to measure gas temperature and concentration at the same time.

Risk and Reward in Foraging Migrations of North Pacific Albacore Determined From Estimates of Energy Intake and Movement Costs

North Pacific albacore (Thunnus alalunga) is a commercially important tuna species known to undertake extensive migratory movements between nearshore waters of the California Current and offshore environments in the central Pacific. However, these migration behaviors are highly variable, with some individuals traveling thousands of kilometers within a season, and others largely resident in the southern California Current throughout the year. In this study, we use data from 33 archival-tagged albacore (released between 2003 and 2011) to examine the movements, physiology and ecology of tuna following different migratory pathways. We used direct measurements of body temperature and ambient water temperature from internal archival tags to estimate energy intake via the Heat Increment of Feeding (HIF), the increased internal heat production associated with digestion of a meal. Our results indicate that HIF was variable in space and time, but it was highest for individuals foraging in the offshore North Pacific Transition Zone and southern California Current during spring and summer, and lowest in the Transition Zone in fall. None of the migratory strategies examined appeared to confer consistently higher energetic benefits than the others. Fish remaining resident in the southern California Current year-round incurred lower migration costs, and could access favorable foraging conditions off Baja California in spring and summer. In contrast, fish which undertook longer migrations had much higher energetic costs during periods of faster transit times, but were able to reach highly productive foraging areas in the central and western Pacific. HIF was generally higher in larger fish, and when ambient temperatures were cooler, but was not strongly correlated with other environmental covariates. Our analyses offer new avenues for studying the physiology of wild tuna populations, and can complement diet and isotopic studies to further understanding of fish ecology.

Optical Hydrogen Nanothermometry of Plasmonic Nanoparticles under Illumination.

The temperature of nanoparticles is a critical parameter in applications that range from biology, to sensors, to photocatalysis. Yet, accurately determining the absolute temperature of nanoparticles is intrinsically difficult because traditional temperature probes likely deliver inaccurate results due to their large thermal mass compared to the nanoparticles. Here we present a hydrogen nanothermometry method that enables a noninvasive and direct measurement of absolute Pd nanoparticle temperature via the temperature dependence of the first-order phase transformation during Pd hydride formation. We apply it to accurately measure light-absorption-induced Pd nanoparticle heating at different irradiated powers with 1 °C resolution and to unravel the impact of nanoparticle density in an array on the obtained temperature. In a wider perspective, this work reports a noninvasive method for accurate temperature measurements at the nanoscale, which we predict will find application in, for example, nano-optics, nanolithography, and plasmon-mediated catalysis to distinguish thermal from electronic effects.

Experimental study of temperature change effect on distributed acoustic sensing continuous measurements

Distributed fiber-optic sensing is useful in geophysical exploration and monitoring applications. Distributed temperature sensing (DTS) is used for measuring and monitoring temperature and distributed acoustic sensing (DAS) for recording the seismic wavefield. However, DAS measurements also are sensitive to temperature changes. To understand and quantify the DAS signature of temperature changes during water injections at CO2CRC Otway site, a series of experiments have been conducted at the Curtin University/National Geosequestration Laboratory (NGL) well research facility and Curtin rock-physics laboratory. Overall, three DAS cables are examined. Two fibers are tested in the laboratory and one cable, which is installed behind the casing in the Curtin/NGL well, is examined in the well. Laboratory measurements and observations made during analysis of passive DAS and DTS field data recorded in four Otway wells demonstrate that DAS is sensitive to long-period temperature changes, and its response is proportional to the time derivative of temperature. Induced fiber strain is linearly related to slow temperature change, and this dependency can be estimated for a particular cable. Obtained proportionality constants between strain and temperature change indicate some dependency on the cable type/design and acquisition setup, but they are all of the same order of magnitude. DAS measurements also can be affected by low-frequency noise possibly associated with the effect of temperature on the DAS acquisition unit itself. The results can help compensate for the effect of temperature on low-frequency DAS signals and show that DAS can be used as a distributed temperature sensor if direct temperature measurements are not available.

Joule-heating induced phase transition in 1T-TaS2 near room temperature probed by thermal imaging of power dissipation

Electrically induced phase transition in 1T-TaS2 at room temperature has various applications, including efficient oscillators and broadband photodetectors. However, the physical mechanism behind the electrically induced phase transition is still not clear due to the lack of direct temperature measurements during the transition. To shed light on this problem, in this Letter, we directly image the spatially resolved temperature of a 1T-TaS2 device by IR thermal microscopy. Combining this method with pulsed electrical transport measurements, Raman spectroscopy, and a simple resistor network model, we show that the transition is a result of Joule-heating. More broadly, we show that thermal imaging is important to determine the power dissipation in electronic devices due to the inhomogeneous nature of the temperature distribution.

Microwave background temperature at a redshift of 6.34 from H2O absorption

Distortions of the observed cosmic microwave background provide a direct measurement of the microwave background temperature at redshifts from 0 to 1 (refs. 1,2). Some additional background temperature estimates exist at redshifts from 1.8 to 3.3 based on molecular and atomic line-excitation temperatures in quasar absorption-line systems, but are model dependent3. No deviations from the expected (1 + z) scaling behaviour of the microwave background temperature have been seen4, but the measurements have not extended deeply into the matter-dominated era of the Universe at redshifts z > 3.3. Here we report observations of submillimetre line absorption from the water molecule against the cosmic microwave background at z = 6.34 in a massive starburst galaxy, corresponding to a lookback time of 12.8 billion years (ref. 5). Radiative pumping of the upper level of the ground-state ortho-H2O(110–101) line due to starburst activity in the dusty galaxy HFLS3 results in a cooling to below the redshifted microwave background temperature, after the transition is initially excited by the microwave background. This implies a microwave background temperature of 16.4–30.2 K (1σ range) at z = 6.34, which is consistent with a background temperature increase with redshift as expected from the standard ΛCDM cosmology4.

Vapor pressure and vapor-liquid equilibrium data for eugenol/caryophyllene binary system at low pressures by experimental and predictive methods

The main objective of this study was to determine the vapor-liquid equilibrium of the binary mixture eugenol/caryophyllene at reduced pressures and to obtain pure compounds vapor pressure data in the same low-pressure condition. Isobaric vapor–liquid equilibrium (VLE) data have been measured in a Fischer ebulliometer at 5.0, 10.0, and 20.0 kPa. The vapor pressure of the pure compounds was determined by direct measurement of the equilibrium temperature at different pressures. The extended Antoine equation and the Clarke and Glew equation were fitted to the experimental data and compared with a predictive method. The thermodynamic consistency of the VLE experimental data was checked using the Redlich-Kister area test and the Van Ness point test. The binary interaction parameters of NRTL, Wilson, and UNIQUAC activity coefficient models were fitted from regression of experimental data. The average absolute deviation of the temperature (AAD(T)) and vapor-phase molar fraction (AAD(y)) are less than 0.22 K and 0.0119, respectively, proving a good adherence of the models for the calculation of the VLE system. The COSMO-SAC model was used to predict activity coefficients, compared with classic thermodynamic models, and was able to represent the azeotrope presented by the mixture.

Power Ramp-Rate Control via power regulation for storageless grid-connected photovoltaic systems

Photovoltaic Power Ramp-Rate Control (PRRC) constitutes a key ancillary service for future power systems. Although its implementation through the installation of storage systems or irradiance sensors has been widely investigated, fewer studies have explored the power curtailment approach. The latter lacks efficiency, as it voluntarily produces power discharges, yet it is a cost-effective solution in terms of capital expenditures. This paper proposes a novel storageless and sensorless photovoltaic PRRC for grid-connected applications in which the photovoltaic power, rather than the voltage, is the controlled magnitude. The aforementioned contribution makes the effective tracking of the power ramp-rate limit possible compared to the existing methods in the literature. The method is assisted by a real-time curve-fitting algorithm that estimates the Maximum Power Point while operating suboptimally. Thus, no direct temperature or irradiance measurement systems are needed. The validation of the proposed PRRC strategy has been tested by simulation and compared to another approach available in the literature, considering real-field highly variable irradiance data. Experimental validation of the proposed strategy has been performed in real time via Controller Hardware-in-the-Loop.