Search

In the transition from traditional electrical energy generation with mainly linear sources to increasing inverter-based distributed generation, electrical power systems' power quality requires new monitoring methods. Integrating a high penetration of distributed generation, which is typically located in medium- or low-voltage grids, shifts the monitoring tasks from the transmission to distribution layers. Compared to high-voltage grids, distribution grids feature a higher level of complexity. Monitoring all relevant nodes is operationally infeasible and costly. State estimation methods provide knowledge about unmeasured locations by learning a physical system's non-linear relationships. This article examines a new flexible, close-to-real-time concept of harmonic state estimation using synchronized measurements processed in a neural network. A physics-aware approach enhances a data-driven model, taking into account the structure of the electrical network. An OpenDSS simulation generates data for model training and validation. Different load profiles for both training and testing were utilized to increase the variance in the data. The results of the presented concept demonstrate high accuracy compared to other methods for harmonic orders 1 to 20. [ABSTRACT FROM AUTHOR]

The growing integration of renewable energy sources, such as photovoltaic and wind systems, into energy grids has underscored the need for reliable control mechanisms to mitigate the inherent intermittency of these sources. According to the Brazilian grid operator (ONS), there have been cascading disconnections in renewable energy distributed systems (REDs) in recent years, highlighting the need for robust control models. This article addresses this issue by presenting the validation of an active power ramp rate control (PRRC) function for a PV plant coupled with a Battery Energy Storage System (BESS) using WECC generic models. The proposed model underwent rigorous validation over an extended analysis period, demonstrating good accuracy using the Root Mean Squared Error (RMSE) and an R-squared (R2) metrics for the active power injected at the Point of Connection (POI), PV active power, and BESS State of Charge (SOC), providing valuable insights for medium and long-term analyses. The ramp rate control module was implemented within the plant power controller (PPC), leveraging second-generation Renewable Energy Systems (RES) models developed by the Western Electricity Coordination Council (WECC) as a foundational framework. We conducted simulations using the Anatem software, comparing the results with real-world data collected at 100 ms to 1000 ms intervals from a PV plant equipped with a BESS in Brazil. The proposed model underwent rigorous validation over an extended analysis period, with the presented results based on two days of measurements. The positive sequence model used to represent this control demonstrated good accuracy, as confirmed by metrics such as the Root Mean Squared Error (RMSE) and R-squared (R2). Furthermore, the article underscores the critical role of accurately accounting for the power sampling rate when calculating the ramp rate. [ABSTRACT FROM AUTHOR]

Phasor-domain (RMS) simulations have become increasingly vital in modern power system analysis, particularly as the complexity and scale of these systems have expanded with the integration of renewable energy sources. ePHASORSIM, an advanced phasor-based simulation tool developed by OPAL-RT, plays a crucial role in this context by enabling real-time phasor-domain simulation and hardware-in-the-loop testing. To keep pace with these evolving needs, continuous efforts are being made to further improve the accuracy, efficiency, and reliability of ePHASORSIM-based simulations. These efforts include automating model conversion processes for enhanced integration with ePHASORSIM, extending ePHASORSIM's simulation range with custom models, developing hybrid co-simulation techniques involving ePHASORSIM and an EMT simulator, enhancing simulation scalability, and refining HIL testing to achieve more precise validation of control and protection systems. This paper provides a comprehensive review of these recent advances. Additionally, the paper discusses the conversion of models from PowerFactory—a widely used and comprehensive modeling environment—to ePHASORSIM through both automated tools and manual methods using Excel workbooks, which has been discussed little in the literature. Furthermore, as ePHASORSIM is a relatively new tool with limited cross-validation studies, the paper aims to contribute to this area by presenting a comparative validation against DIgSILENT PowerFactory, with a specific emphasis on its application in electric vehicle charging management systems. [ABSTRACT FROM AUTHOR]

With half-cut photovoltaic (PV) modules being the dominant technology on the market, there is an increasing necessity for accurate modeling of this module type. Circuit simulators such as Simulink are widely used to study different topics regarding photovoltaics, often employing a solar cell block available from the Simcape library. The purpose of this work is to validate this model against measurements for a partially shaded half-cut PV module. Diverse shading scenarios are created by varying the number of shaded substrings, the number of shaded solar cells in the substring, and the shading level. For every shading scenario, the PV module's I-V curve is measured, along with in-plane irradiance, air temperature, and module temperature. A comprehensive evaluation of simulation accuracy is presented. The results confirm a high accuracy of the model with mean nRMSE values of 2.2% for I-V curves and 2.8% when P-V curves are considered. It is found that the simulation errors tend to increase when increasing the number of shaded substrings. At the same time, no obvious dependency of simulation accuracy on the shading level or the number of shaded solar cells in the substring is found. [ABSTRACT FROM AUTHOR]

An experimental validation of a steady-state model for water-to-water heat pumps is conducted on a 10 kW test bench. The objective of the model is to predict the capacity and the required compressor power, based on the inlet conditions of the secondary fluids in the evaporator and condenser. Detailed manufacturer performance maps based on the AHRI 540-2020 standard are utilized to model the fixed-speed scroll compressor. A new semi-empirical model for the thermostatic expansion valve incorporates condensing temperature effects on superheating prediction. Sub-models for individual components, including detailed representations of the evaporator and condenser, are integrated into a global model, resulting in a set nonlinear equation solved using an equation solver with appropriate guess values. The validation of the model is conducted in an experimental test facility equipped with two precisely controlled secondary fluid loops. The heat pump is instrumented to measure condensation and evaporation pressures, the compressor discharge temperature, compressor power, superheating, and sub-cooling. The results are divided into three sub-sections: the first validates the complete heat pump model by comparing its power consumption and COPs in heating and cooling; the second compares the predicted and measured operational conditions; finally, it is shown how the model can be used to predict the non-operational conditions of the heat pump for specific scenarios. [ABSTRACT FROM AUTHOR]

The validation of aeroelastic load models used for load calculations on wind turbines substantially increases the confidence in the accuracy and correctness of these models. In this contribution, we introduce a framework for the validation of these models, integrating a normalized area metric as an objective, quantifiable validation metric that considers the entire statistical distribution of a model and a benchmark and additionally enables a comparison of model accuracy between sensors of different physical units. The framework is applied to test cases that evaluate varying synthetic turbulent wind fields. Two test cases with a focus on turbulence parameters and abnormal shear conditions based on comprehensive wind measurements at the Testfeld Bremerhaven are used to demonstrate the workflow with four different members using IEC-compliant and measurement-derived wind field parameters, respectively. Along with these measurements, an uncertainty model for synthetic wind fields is introduced to quantify propagated wind measurement uncertainties associated with the measured boundary conditions during a validation campaign. The framework is presented as a straightforward and concise methodology to not only find but also quantify mismatches of load models. Major mismatches are found for wind fields associated with larger uncertainties in the mean wind field due to a reduced spatial resolution of measurements. [ABSTRACT FROM AUTHOR]

Current stratospheric airships generally employ photovoltaic cycle energy systems. Accurately calculating their power generation is significant for airships' overall design and mission planning. However, the power generation of solar arrays on stratospheric airships is challenging to model and calculate due to the dynamic nature of the airships' flight, resulting in continuously changing radiation conditions on the curved surface of the airships. The power generated by the airship solar array was modeled herein through a combination of the flight attitude, spatial position, time, and other influencing factors. Additionally, the model was modified by considering the variation in photovoltaic conversion efficiency based on the radiation incidence angle, as well as the state of charge and power consumption of the energy storage battery pack. This study compared the measurement data of power generation in real flight tests with the calculation results of the model. The comparison showed that the results of the calculated model were highly consistent with the actual measured data. An average normalized root-mean-square error of 2.47% validated the accuracy of the newly built model. The generalizability and rapidity of the model were also tested, and the results showed that the model performed well in both metrics. [ABSTRACT FROM AUTHOR]

Recently, there has been growing recognition of the significance of energy and environmental challenges. Utilization of lithium-ion batteries in electric vehicles has shown considerable potential and benefits for tackling these issues. The effective management of battery temperature has become a crucial factor in the advancement and widespread adoption of lithium-ion batteries in electric vehicles. In this study, a thermo-coupled pseudo-two-dimensional (P2D) electrochemical model is employed to simulate the heat generation of the NCM811-21700 cylindrical battery cell at various discharge rates at an ambient temperature of 25 °C, and is validated by experimental data. The validation results demonstrate that the thermo-coupled P2D model can effectively predict the battery voltage curve during the discharge process with less than 4% errors. Although there is a slightly larger error in the temperature prediction during the battery 2C and 3C discharge processes, the maximum error approaches 10%, which is still generally within an acceptable range. In addition, the battery's electrochemical and thermal characteristics during discharge are presented. The suggested thermo-coupled electrochemical model can be used for applications in the thermal management system of the NCM811-21700 battery. [ABSTRACT FROM AUTHOR]

In this work, a dynamic analysis describing the charge and discharge process of a supercapacitor for the DC-link between a photovoltaic source and a constant power load is presented. The analysis results in a complete nonlinear and dynamic model that can be used for simulation and control for DC–DC converters, achieving fast recharge times and accurate steady-state voltages in the DC link to avoid overcharging the supercapacitor during low power absorption scenarios. The proposed approach includes parasitic elements for the supercapacitor and efficiency effects on the conversion stage, proposing equations useful for design and control. Stability is also discussed for the charge process of the supercapacitor. Validation of the analytical model is performed by comparison with LTSpice simulation, confirming a good agreement between theory and simulation. [ABSTRACT FROM AUTHOR]

Wind turbine aerodynamic interactions within wind farms lead to significant energy losses. Optimizing the flow between turbines presents a promising solution to mitigate these losses. While analytical models offer a fundamental approach to understanding aerodynamic interactions, further development and refinement of these models are imperative. We propose a simplified analytical model that combines the Gaussian wake model and the cylindrical vortex induction model to evaluate the interaction between wake and induction zones in 3.5 MW wind turbines with 328 m spacing. The model's validation is conducted using field data from a nacelle-mounted LiDAR system on the downstream turbine. The 'Direction to Hub' parameter facilitates a comparison between the model predictions and LiDAR measurements at distances ranging from 50 m to 300 m along the rotor axis. Overall, the results exhibit reasonable agreement in flow trends, albeit with discrepancies of up to 15° in predicting peak interactions. These deviations are attributed to the single-hat Gaussian shape of the wake model and the absence of wake expansion consideration, which can be revisited to improve model fidelity. The 'Direction to Hub' parameter proves valuable for model validation and LiDAR calibration, enabling a detailed flow analysis between turbines. This analytical modeling approach holds promise for enhancing wind farm efficiency by advancing our understanding of turbine interactions. [ABSTRACT FROM AUTHOR]

This paper primarily focuses on the formulation and validation of mathematical and numerical models for a new electrolyte-supported solid oxide fuel cell stack. By leveraging numerical modeling, the main goal is to deepen the understanding of the operational aspects and transport phenomena within this system. The developed models are implemented in ANSYS, Inc., Fluent software, which enables a range of simulations. To validate the models, a stack fabrication methodology, a prototype construction, and conducted electrochemical tests were proposed. The simulated current-voltage characteristics for two different operating temperatures and three different fuel compositions were compared with the experimental measurements with satisfactory agreement. The counter-flow configuration was simulated and compared to the co-flow arrangement. The numerical simulation has demonstrated its efficacy in identifying possible design imperfections and enhancing the operational conditions of the prototype stack. Moreover, the developed model was further used, in Part 2 of this paper, to analyze the improvement options implementation for the next stage of the prototype. [ABSTRACT FROM AUTHOR]

The proliferation of inverter-based distributed energy resources (IBDERs) has increased the number of control variables and dynamic interactions, leading to new grid control challenges. For stability analysis and designing appropriate protection controls, it is important that IBDER models are accurate. This paper focuses on the accurate estimation and parameter calibration of DER_A, a recently proposed aggregated IBDER model. In particular, we focus on the parameters of the reactive power–voltage regulation module. We formulate the problem of parameter tuning as a non-linear least square minimization problem and solve it using the Levenberg–Marquardt (LM) method. The LM method is primarily chosen due to its flexibility in adaptively selecting between the steepest descent and Gauss–Newton methods through a damping parameter. The LM approach is used to minimize the error between the actual measurements and the estimated response of the model. Further, the computational challenges posed by the numerical calculation of the Jacobian are tackled using a quasi-Newton root-finding approach. The proposed method is validated on a real feeder model in the northeastern part of the United States. The feeder is modeled in OpenDSS and the measurements thus obtained are fed to the DER_A model for calibration. The simulation results indicate that our approach is able to successfully calibrate the relevant model parameters quickly and with high accuracy, with a total sum of square error of 3.57 × 10 − 7 . [ABSTRACT FROM AUTHOR]

PV-based mini-grids are identified as a feasible and, often, only economically viable option for the electrification of Kenyan remote and scattered rural areas, where connection to the national grid is challenging, and the related costs are high, if not prohibitive. This paper presents the analysis of typical Kenyan PV mini-grids by using some results of the work in the project "Reliable, Efficient and Sustainable Mini-Grids for Rural Infrastructure Development in Kenya (RESILIENT)". After presenting average annual and seasonal daily load profiles of residential and small commercial mini-grid customers identified from the measured demands, the paper introduces the main mini-grid components and their models, including a simplified, but reasonably accurate, model of a mini-grid battery storage system based on the manufacturer's charge–discharge curves. All mini-grid components are assembled in a scalable and easily reconfigurable simulation model of an actual Kenyan PV mini-grid, and they are implemented for the evaluation of PV mini-grid performance and the potential for expansion and connection of additional residential and small commercial customers. During the validation of the developed simulation model using available measurement data, an empirical approach for adjusting the PV system output power is specified for a more accurate match with the measurements. The presented results indicate the importance of the information on the actual control algorithms and control settings of the mini-grid energy management systems, on the thermal dependencies and characteristics of both PV generation system and battery storage system, and on the availability of on-site measurements of temperature and input solar irradiance. The developed PV mini-grid model can be used for further analyses, such as to study the techno-economic performance of different mini-grid configurations, to identify the optimal sizing of mini-grid components, and to specify efficient control and operation schemes based on the locally available resources. [ABSTRACT FROM AUTHOR]

This paper presents an analysis and simulation of the mathematical model associated to the DC/DC Boost converter–full-bridge Buck inverter system to regulate the voltage output of the DC/DC Boost converter allowing bipolar voltages higher than the input voltage via the full-bridge Buck inverter. To validate the model, the differential flatness property is applied via the flat outputs of the system (energy for the DC/DC Boost converter and the voltage of the full-bridge Buck inverter) considering the complete dynamics, in conjunction with fixed and time-variant trajectory planning. In the simulation results, it is observed that the error signals of the states versus the reference trajectories are acceptable. Regarding the validation of the model, this is performed with open-loop simulations at the circuit level using the SimPowerSystems Toolbox of Matlab-Simulink. The simulation results validate the good performance of the system under study. In this way, the main contribution of this work is that for the first time in the literature, the analysis of a complete dynamics for a conversion system from DC to AC without the use of a transformer and taking advantage of differential flatness is reported; thus, the system analyzed could be represented as an alternative in applications of renewable energies that require conversion from DC to AC. [ABSTRACT FROM AUTHOR]

The automotive sector is greatly contributing to pollutant emissions and recent regulations introduced the need for a major control of, and reduction of, internal combustion engine emissions. Artificial intelligence (AI) algorithms have proven to hold the potential to be the thrust in the state-of-the-art for engine-out emission prediction, thus enabling tailored calibration modes and control solutions. More specifically, the scientific literature has recently witnessed strong efforts in AI applications for the development of nitrogen oxides (NOx) virtual sensors. These latter replace physical sensors and exploit AI algorithms to estimate NOx concentrations in real-time. Still, the calibration of the algorithms, together with the appropriate choice of the specific metric, strongly affects the prediction capability. In the present paper, a machine learning-based virtual sensor for NOx monitoring in diesel engines was developed, based on the Extreme Gradient Boosting (XGBoost) machine learning algorithm. The latter is commonly used in the literature to deploy virtual sensors due to its high performance, flexibility and robustness. An experimental campaign was carried out to collect data from the engine test bench, as well as from the engine electronic control unit (ECU), for the development and calibration of the virtual sensor at steady-state conditions. The virtual sensor has, since then, been tested throughout on an on-road driving mission to assess its prediction performance in dynamic conditions. In stationary conditions, its prediction accuracy was around 98%, whereas it was 85% in transient conditions. The present study shows that AI-based virtual sensors have the potential to significantly improve the accuracy and reliability of NOx monitoring in diesel engines, and can, therefore, play a key role in reducing NOx emissions and improving air quality. [ABSTRACT FROM AUTHOR]

A pneumatic radial piston motor is studied in this paper in order to establish a dynamic modelling and simulation method. As a result of using geometric parameters, the piston cylinder volume change was calculated, and the heat transfer equation, thermodynamic energy balance equation, and motion equation were combined in order to create a complete model of the piston cylinder. With the aid of compressed air, several experimental tests were conducted, and the results of rotational speed with varying inlet pressure were fed into the simulation to determine one of the critical unknown parameters, such as the overall friction coefficient of the system. For the studied piston motor, this coefficient was 0.0625 Nm. Computer simulations can be used to adjust design parameters in order to reach a higher rotation speed by using an accurate model. As a result, better efficiency and performance present several opportunities that would not be possible when running experimental tests in a lab. The mathematical model yielded higher rotational speeds of 50 RPM on average, with an increased piston diameter of 1.775 mm; by increasing the diameter of the cylinder to 25.8 mm, it was possible to achieve faster rotational speeds. The performed precise simulation could be used for further motor design and optimisation, and performance estimates under a broader range of operational conditions. Simulations should be conducted on multiple sets of experimental test results to determine the correct f overall value for each motor. In addition to guiding the design and optimisation of the motor, simulations could also predict its performance under a broader range of operating conditions by utilising effective parameters such as geometrical characteristics, flow conditions, and motion equations. [ABSTRACT FROM AUTHOR]

The Split-pi converter can suitably interface an energy storage system (ESS) with a DC microgrid when galvanic isolation is not needed. Usually, the ESS voltage is lower than the grid-side voltage. However, limitations in terms of the ESS current make the use of a high-voltage ESS unavoidable when high power levels are required. In such cases, the ESS voltage can be higher than the microgrid voltage, especially with low microgrid voltages such as 48 V. Despite its bidirectionality and symmetry, the Split-pi exhibits a completely different dynamic behavior if its input and output ports are exchanged. Thus, the present work aims to model the Split-pi converter operating with an ESS voltage higher than the grid-side voltage in three typical microgrid scenarios where the controlled variable is the converter's output voltage. The devised state-space model considers the parasitic elements and the correct load model for each scenario. Furthermore, it is shown that the presence of the input LC filter can make the design of the loop controllers more complicated than in the case of a lower ESS voltage than the grid-side voltage. Finally, the study is validated through simulations and experimental tests on a lab prototype, and a robustness analysis is performed. [ABSTRACT FROM AUTHOR]

This work presents a perspective on deterministic predictive modeling methodologies, which aim at extracting best-estimate values for model responses and parameters along with reduced predicted uncertainties for these best-estimate values. The two oldest such methodologies are the data-adjustment method, which stems from the nuclear energy field, and the data-assimilation method, which is implemented in the geophysical sciences. Both of these methodologies attempt to minimize, in the least-square sense, a user-defined functional that represents the discrepancies between computed and measured model responses. These two methodologies were briefly reviewed and shown to be inconsistent even to first-order in the sensitivities of the response to the model parameters. In contrast to these methodologies, it was shown that the "maximum entropy"-based predictive modeling methodology (called BERRU-PM) that was developed by the author not only dispenses with the subjective "user-chosen functional to be minimized" but is also inherently amenable to high-order formulations. This inherent potential was illustrated by presenting a novel, higher-order, MaxEnt-based predictive modeling methodology, labelled BERRU-PM-2+, which is complete and exact to second-order sensitivities and moments of both the a priori and posterior distributions of responses and parameters, while explicitly including third- and fourth-order sensitivities and correlations, thus indicating the mechanism for incorporating information of orders higher than second in predictive modeling. The presentation of this new predictive modeling methodology also aims at motivating a widespread application of predictive modeling principles and methodologies in the energy sciences for obtaining best-estimate results with reduced uncertainties. [ABSTRACT FROM AUTHOR]

The world is experiencing an accelerated energy transition that is driven by the climate goals to be met and that has driven the growth of different potential sectors such as electric mobility powered by electric motors, which continue to be the largest load globally. However, new needs in relation to power density, weight, and efficiency have led manufacturers to experiment with new technologies, such as rare earth elements (REEs). The permanent magnet motor is a candidate to be the substitute for the conventional induction motor considering the new editions of the IEC 60034-30-1, for which study and evaluation continue to be focused on identifying the weaknesses and benefits of its application on a large scale in industry and electric mobility. This work presents a FEM model to assess the line-start permanent magnet motor (LSPMM), aiming to simulate the behavior of the LSPMM under supply conditions with distorted voltages (harmonic content) and evaluate its thermal and magnetic performance. The model created in the FEM software is then validated by bench tests in order to constitute an alternative analysis tool that can be used for studies in previous project phases and even to implement predictive maintenance schemes in industries. [ABSTRACT FROM AUTHOR]

Thermochemical heat storage has attracted significant attention in recent years due to potential advantages associated with very high-energy density at the material scale and its suitability for long-duration energy storage because of almost zero loss during storage. Despite the potential, thermochemical heat storage technologies are still in the early stage of development and little has been reported on thermochemical reactors. In this paper, our recent work on the charging and discharging behavior of a fixed-bed thermochemical reactor is reported. Silica gels were used as the sorbent for the experimental work. An effective model was established to numerically study the effect of different charging conditions on the discharging behavior of the reactor, which was found to have a maximum deviation of 10.08% in terms of the root mean square error compared with the experimental results. The experimentally validated modelling also showed that the discharging temperature lift increased by 5.84 times by changing the flow direction of the air in the discharging process when the charging level was at 20%. At a charging termination temperature of 51.25 °C, the maximum discharging temperature was increased by 2.35 °C by reducing the charging flow velocity from 0.64 m/s to 0.21 m/s. An increase in the charging temperature and a decrease in the air humidity increased the maximum discharging outlet temperature lift by 3.37 and 1.89 times, respectively. [ABSTRACT FROM AUTHOR]

The aim of the study was to verify the impact of the location of a cyclically heated building on its energy needs and interaction with the environment. The model building was a large-scale broiler house located in southern Poland. In the examined facility, year-round measurements of selected parameters of the internal and external microclimate were carried out. The tests also covered the temperature of the soil in three measurement columns. The obtained measurement results were used for further computer analyses. A geometric model of the building was made and a calculation model specification was introduced, supported by specialized software for the physics of WUFI®plus structures. The numerical analysis included validation. The validation results were assessed on the basis of the Coefficient of Determination method (R2) and the Goodness of Fit (GOF) method. Due to the lack of normality of the data distribution, a Rang-Spearman correlation analysis was carried out, which showed a very strong data correlation (0.94). The analysis of the R2 coefficient of determination confirmed the high reliability of the model (83%). In the case of the GOF method, a compliance value of 87% was obtained. Differentiated locations were adopted for further analysis, while maintaining the structure of the examined building in reality. Six European locations were selected: Kraków (Poland), Málaga (Spain), Brest (France), Visby (Sweden), Umea (Sweden), and Kiruna (Sweden). The analysis included three variants, in which the length of the technological break was adopted accordingly. A technological break between production cycles was assumed, the three variants of which lasted 3, 7, and 14 days. The analysis of the obtained results showed that the external microclimate significantly determines the energy interaction between the building and the ground. The length of the technological break is very important in a climate dominated by low temperatures (Northern Scandinavia). The south-western part of Europe allows the technological break to be extended without significant differences for heating purposes. The length of the technological break in the range of 3 to 14 days does not significantly affect the intensity of heat exchange with the ground on a yearly basis, regardless of the location of the building. There were differences of no more than 2% between the technological break lasting 3 days and the 14-day break. [ABSTRACT FROM AUTHOR]

The evolution of fracture zone controls the safety of underground coal gasification (UCG) in terms of gas emission and water leakage. In order to understand the fracture propagation in the confining rock of a UCG cavity with various influence factors, this paper implemented a set of numerical models based on different geological and operating conditions. Analysis was implemented on the mechanism of fracture propagation and its evolution characteristics, suggesting that (a) continuum expansion of the cavity leads a near-field fracture circle in confining rock initially, followed by the roof caving and successive propagation of shear band. (b) The key observed influence factors of fracture propagation are the grade of confining rock, overburden pressure, dimension of the cavity and gasifying pressure, the linear relationships between them, and the fracture height. Additionally, the fracture depth in the base board was mainly caused by tensile fracture. (c) A model was proposed based on the evolution of fracture height and depth in roof and base board, respectively. Validation of this model associated with orthogonal tests suggests a good capacity for predicting fracture distribution. This paper has significance in guiding the design of the gasifying operation and safety assessment of UCG cavities. [ABSTRACT FROM AUTHOR]

A particle-scale surface tension force model (STF) is proposed here to be incorporated in the smoothed hydrodynamics particle (SPH) method. This model is based on the identification of interface geometry and the gradient of densities across the interface. A square bubble of single-phase and a square bubble immersed in fluids are simulated by the STF model accompanied with a combined kernel in SPH to validate their suitability to simulate the immersed bubble motion. Two cases of rising bubbles, i.e., a single rising bubble and a pair of rising bubbles, are simulated for demonstration. The rising velocity, density, surface tension force, interfacial curvature, the power of the STF, and the smoothing length of the rising bubble and surrounding fluids are all computed by the current STF model to study the characteristics of immersed bubble's motion and coalescence. The current model provides a way to capture the interfacial interactions in two-phase flows at particle scales. [ABSTRACT FROM AUTHOR]

This paper investigates the model development of the state-of-power (SoP) estimation for a 43 Ah large-capacity prismatic nickel-manganese-cobalt oxide (NMC) based lithium-ion cell with a thorough aging investigation of the cells' internal resistance increase. For a safe operation of the vehicle system, a battery management system (BMS) integrated with SoP estimation functions is crucial. In this study, the developed SoP model used for the estimation of power throughout the lifetime of the cell is coupled with a dual-polarization equivalent-circuit model (DP_ECM) for achieving the precise estimation of desired parameters. The SoP model is developed based on the pulse-trained internal resistance evolution approach, and hence the power is estimated by determining the rate of internal resistance increase. Hybrid pulse power characterization (HPPC) test results are used for extraction of the impedance parameters. In the DP_ECM, Coulomb counting and extended Kalman filter (EKF) state estimation methods are developed for the accurate estimation of the state of charge (SoC) of the cell. The SoP model validation is performed by using both dynamic Worldwide harmonized Light vehicles Test Cycles (WLTC) and static current profiles, achieving promising results with root-mean-square errors (RMSE) of 2% and 1%, respectively. [ABSTRACT FROM AUTHOR]

The geomechanical behavior of methane hydrate bearing sediments (MHBS) is influenced by many factors, including temperature, fluid pressure, hydrate saturation, stress level, and strain rate. The paper presents a visco-elastoplastic constitutive model for MHBS based on an elastoplastic model that incorporates the effect of hydrate saturation, stress history, and hydrate morphology on hydrate sediment response. The upgraded model is able to account for additional critical features of MHBS behavior, such as, high-dilatancy, temperature, and rate effects. The main components and the mathematical formulation of the new constitutive model are described in detail. The upgraded model is validated using published triaxial tests involving MHBS. The model agrees overly well with the experimental observations and is able to capture the main features associated with the behavior of MHBS. [ABSTRACT FROM AUTHOR]

The safety case for a radioactive waste repository relies heavily on results obtained by numerical models that assess the long-term performance of the engineered and natural barrier systems. Given that important engineering and public policy decisions are based on these models, it is essential that we critically evaluate their abilities and limitations, and thus justify the level of confidence we have in the inferences drawn from the modeling. In this article, we discuss some of the issues surrounding the modeler's attempts to test, corroborate, confirm, and verify numerical models—a process sometimes referred to as model validation. This wide-ranging topic is approached by first examining its deep roots in the philosophy of science and hypothesis testing. However, the application of these principles to radioactive waste isolation calls for a more pragmatic approach, which has the narrower goal of corroborating site-specific models and their usefulness for a specific purpose. We focus on the practical aspects of validating hydrogeological models that are used to understand the evolution of the repository system. We will make the case that the responsible use of numerical models requires a sufficient understanding of the quality and robustness of the simulation results, with direct implications for how these results need to be interpreted, and how they can (or cannot) be used in support of important policy decisions. [ABSTRACT FROM AUTHOR]

A recent expert elicitation showed that model validation remains one of the largest barriers for commercial wind farm control deployment. The Gaussian-shaped wake deficit model has grown in popularity in wind farm field experiments, yet its validation for larger farms and throughout annual operation remains limited. This article addresses this scientific gap, providing a model comparison of the Gaussian wind farm model with historical data of three offshore wind farms. The energy ratio is used to quantify the model's accuracy. We assume a fixed turbulence intensity of I ∞ = 6 % and a standard deviation on the inflow wind direction of σ w d = 3 ° in our Gaussian model. First, we demonstrate the non-uniqueness issue of I ∞ and σ w d , which display a waterbed effect when considering the energy ratios. Second, we show excellent agreement between the Gaussian model and historical data for most wind directions in the Offshore Windpark Egmond aan Zee (OWEZ) and Westermost Rough wind farms (36 and 35 wind turbines, respectively) and wind turbines on the outer edges of the Anholt wind farm (110 turbines). Turbines centrally positioned in the Anholt wind farm show larger model discrepancies, likely due to deep-array effects that are not captured in the model. A second source of discrepancy is hypothesized to be inflow heterogeneity. In future work, the Gaussian wind farm model will be adapted to address those weaknesses. [ABSTRACT FROM AUTHOR]

With the continuous increase of grid-connected photovoltaic (PV) installed capacity and the urgent demand of synergetic utilization with the other power generation forms, the high-precision prediction of PV power generation is increasingly important for the optimal scheduling and safe operation of the grid. In order to improve the power prediction accuracy, using the response characteristics of PV array under different environmental conditions, a data driven multi-model power prediction method for PV power generation is proposed, based on the seasonal meteorological features. Firstly, through the analysis of PV power characteristics in typical seasons and seasonal distribution of the weather factors, such as solar irradiance and ambient temperature, the influences of different weather factors on PV power prediction are studied. Then, according to the meteorology characteristics of Beijing, different seasons can be divided. The historical data corresponding to different seasons are acquired and then the seasonal PV power forecasting models are established based on optimized multi-layer back propagation neural network (BPNN), realizing the multi-model prediction of PV power. Finally, effectiveness of the seasonal PV power forecasting method is compared and validated. The performance analysis of the neural network forecasting model under typical seasonal conditions shows that the multi-model forecasting method based on seasonal characteristics of PV power generation is better than that of single power forecasting model for the whole year. The results show that the proposed method can effectively improve the power forecasting accuracy of PV power. [ABSTRACT FROM AUTHOR]

A model based, energy focused, quasi-stationary waste heat driven, internal combustion engine (ICE) centred design methodology for cogeneration (heat and electricity) systems is presented. The developed parametric model could be used for system sizing, performance evaluation, and optimization. This paper presents a systematic approach to model the behaviour of the CHP system using heat recovery prediction methods. The modular, physics based modelling environment shows the power flow between the system components, with a special emphasis on the ICE subsystems, parameter identification, and model validation. [ABSTRACT FROM AUTHOR]

This paper analyzes the response under voltage dips of a Type 3 wind turbine topology based on IEC 61400-27-1. The evolution of both active power and rotational speed is discussed in detail when some of the most relevant control parameters, included in the mechanical, active power and pitch control models, are modified. Extensive results are also included to explore the influence of these parameters on the model dynamic response. This work thus provides an extensive analysis of the generic Type 3 wind turbine model and provides an estimation of parameters not previously discussed in the specific literature. Indeed, the International Standard IEC 61400-27-1, recently published in February 2015, defines these generic dynamic simulation models for wind turbines, but does not provide values for the parameters to simulate the response of these models. Thus, there is a pressing need to establish correlations between IEC generic models and specific wind turbine manufacturer models to estimate suitable parameters for simulation purposes. Extensive results and simulations are also included in the paper. [ABSTRACT FROM AUTHOR]

Underground coal gasification (UCG) converts coal to a high-calorific synthesis gas for the production of fuels or chemical feedstock. UCG reactors are generally operated below hydrostatic pressure to avoid leakage of UCG fluids into overburden aquifers. Additionally, fluid flow out of and into the reactor is also determined by the presence of the steam jacket, emerging in close reactor vicinity due to the high temperatures generated in UCG operation. Aiming at improving the understanding of the substantial role of the steam jacket in UCG operations, we employ numerical non-isothermal multiphase flow simulations to assess the occurring multiphase fluid flow processes. For that purpose, we first validate our modeling approach against published data on the U.S. UCG field trials at Hanna and Hoe Creek, achieving a very good agreement between our simulation and the observed water balances. Then, we discuss the effect of coal seam permeability and UCG reactor pressure on the dynamic multiphase flow processes in the reactor's vicinity. The presented modeling approach allows for the quantification and prediction of time-dependent temperature and pressure distributions in the reactor vicinity, and thus steam jacket dynamics as well as reactor water inand outflows. [ABSTRACT FROM AUTHOR]

Empirically based modeling is an essential aspect of design for a wave energy converter. Empirically based models are used in structural, mechanical and control design processes, as well as for performance prediction. Both the design of experiments and methods used in system identification have a strong impact on the quality of the resulting model. This study considers the system identification and model validation process based on data collected from a wave tank test of a model-scale wave energy converter. Experimental design and data processing techniques based on general system identification procedures are discussed and compared with the practices often followed for wave tank testing. The general system identification processes are shown to have a number of advantages, including an increased signal-to-noise ratio, reduced experimental time and higher frequency resolution. The experimental wave tank data is used to produce multiple models using different formulations to represent the dynamics of the wave energy converter. These models are validated and their performance is compared against one another. While most models of wave energy converters use a formulation with surface elevation as an input, this study shows that a model using a hull pressure measurement to incorporate the wave excitation phenomenon has better accuracy. [ABSTRACT FROM AUTHOR]

Plane-of-array (PoA) irradiation data is a requirement to simulate the energetic performance of photovoltaic devices (PVs). Normally, solar data is only available as global horizontal irradiation, for a limited number of locations, and typically in hourly time resolution. One approach to handling this restricted data is to enhance it initially by interpolation to the location of interest; next, it must be translated to PoA data by separately considering the diffuse and the beam components. There are many methods of interpolation. This research selects ordinary kriging as the best performing technique by studying mathematical properties, experimentation and leave-one-out-cross validation. Likewise, a number of different translation models has been developed, most of them parameterised for specific measurement setups and locations. The work presented identifies the optimum approach for the UK on a national scale. The global horizontal irradiation will be split into its constituent parts. Divers separation models were tried. The results of each separation algorithm were checked against measured data distributed across the UK. It became apparent that while there is little difference between procedures (14 Wh/m2 mean bias error (MBE), 12 Wh/m2 root mean square error (RMSE)), the Ridley, Boland, Lauret equation (a universal split algorithm) consistently performed well. The combined interpolation/separation RMSE is 86 Wh/m2). [ABSTRACT FROM AUTHOR]

Considerable efforts are currently being made by several international working groups focused on the development of generic, also known as simplified or standard, wind turbine models for power system stability studies. In this sense, the first edition of International Electrotechnical Commission (IEC) 61400-27-1, which defines generic dynamic simulation models for wind turbines, was published in February 2015. Nevertheless, the correlations of the IEC generic models with respect to specific wind turbine manufacturer models are required by the wind power industry to validate the accuracy and corresponding usability of these standard models. The present work conducts the validation of the two topologies of variable speed wind turbines that present not only the largest market share, but also the most technological advances. Specifically, the doubly-fed induction machine and the full-scale converter (FSC) topology are modeled based on the IEC 61400-27-1 guidelines. The models are simulated for a wide range of voltage dips with different characteristics and wind turbine operating conditions. The simulated response of the IEC generic model is compared to the corresponding simplified model of a wind turbine manufacturer, showing a good correlation in most cases. Validation error sources are analyzed in detail, as well. In addition, this paper reviews in detail the previous work done in this field. Results suggest that wind turbine manufacturers are able to adjust the IEC generic models to represent the behavior of their specific wind turbines for power system stability analysis. [ABSTRACT FROM AUTHOR]

This paper deals with the empirical validation of a building thermal model of a complex roof including a phase change material (PCM). A mathematical model dedicated to PCMs based on the heat apparent capacity method was implemented in a multi-zone building simulation code, the aim being to increase the understanding of the thermal behavior of the whole building with PCM technologies. In order to empirically validate the model, the methodology is based both on numerical and experimental studies. A parametric sensitivity analysis was performed and a set of parameters of the thermal model has been identified for optimization. The use of the generic optimization program called GenOpt® coupled to the building simulation code enabled to determine the set of adequate parameters. We first present the empirical validation methodology and main results of previous work. We then give an overview of GenOpt® and its coupling with the building simulation code. Finally, once the optimization results are obtained, comparisons of the thermal predictions with measurements are found to be acceptable and are presented. [ABSTRACT FROM AUTHOR]

This work focuses on a steady-state model developed for an integrated planar solid oxide fuel cell (IP-SOFC) bundle. In this geometry, several single IP-SOFCs are deposited on a tube and electrically connected in series through interconnections. Then, several tubes are coupled to one another toform a full-sized bundle. A previously-developed and validated electrochemical model is the basis for the development of the tube model, taking into account in detail the presence of active cells, interconnections and dead areas. Mass and energy balance equations are written for the IP-SOFC tube, in the classical form adopted for chemical reactors. Based on the single tube model, a bundle model is developed. Model validation is presented based on single tube current-voltage (I-V) experimental data obtained in a wide range of experimental conditions, i.e., at different temperatures and for different H2/CO/CO2/CH4/H2O/N2 mixtures as the fuel feedstock. The error of the simulation results versus I-V experimental data is less than 1% in most cases, and it grows to a value of 8% only in one case, which is discussed in detail. Finally, we report model predictions of the current density distribution and temperature distribution in a bundle, the latter being a key aspect in view of the mechanical integrity of the IP-SOFC structure. [ABSTRACT FROM AUTHOR]

Switching overvoltages (SOV) are considered a possible source of component failures experienced in existing offshore wind farms (OWFs). The inclusion of sufficiently accurate and validated models of the main electrical components in the OWF in the simulation tool is therefore an important issue in order to ensure reliable switching operations. Transient measurement results in an OWF are compared with simulation results in PSCAD EMTDC and DigSILENT Power Factory. A user-defined model of the vacuum circuit breaker (VCB) is included in both tools, capable of simulating multiple prestrikes during the closing operation. An analysis of the switching transients that might occur in OWFs will be made on the basis of the validated model, and the importance of the inclusion of a sufficiently accurate representation of the VCB in the simulation tool will be described. The inclusion of the VCB model in PSCAD greatly improves the simulation results, whereas little improvement is found in DigSILENT. Based on the transient study it is found that the simulated SOV can be up to 60% higher at the sending end when using the detailed VCB representation compared to the built-in switch, which emphasises the need for accurate representation of the VCB for energisation studies. [ABSTRACT FROM AUTHOR]

In this paper, a gas-to-power (GtoP) system for power outages is digitally modeled and experimentally developed. The design includes a solid-state hydrogen storage system composed of TiFeMn as a hydride forming alloy (6.7 kg of alloy in five tanks) and an air-cooled fuel cell (maximum power: 1.6 kW). The hydrogen storage system is charged under room temperature and 40 bar of hydrogen pressure, reaching about 110 g of hydrogen capacity. In an emergency use case of the system, hydrogen is supplied to the fuel cell, and the waste heat coming from the exhaust air of the fuel cell is used for the endothermic dehydrogenation reaction of the metal hydride. This GtoP system demonstrates fast, stable, and reliable responses, providing from 149 W to 596 W under different constant as well as dynamic conditions. A comprehensive and novel simulation approach based on a network model is also applied. The developed model is validated under static and dynamic power load scenarios, demonstrating excellent agreement with the experimental results. [ABSTRACT FROM AUTHOR]

In this paper, the numerical model of a centrifugal compressor low-flow stage is verified. The gaps and labyrinth seals were simulated in the numerical model. The task was to determine the optimal settings for high-quality modeling of the low-flow stages. The intergrid interface application issues, turbulence and roughness models are considered. The obtained numerical model settings are used to validate seven model stages for the range of the optimal conditional flow coefficient with Φopt = 0.008–0.018 and the conditional Mach number Mu = 0.785–0.804. The simulation results are compared with the experimental data. The high pressure stage-7 (HPS-7) stage with Φopt = 0.010 and Mu = 0.60 at different inlet pressure of 4, 10 and 40 atm is considered separately. Acceptable validation results are obtained with the recommended numerical model settings; the modeling uncertainty for the polytropic pressure coefficient δη*pol < 4% for the efficiency coefficient δη*pol exceeds the limit of 4% only in the two most low-flow stages, U and V. [ABSTRACT FROM AUTHOR]

This paper presents a reversible heat pump based on CO2 as the refrigerant, able to provide heating, cooling, and domestic hot water to high energy demand buildings. The unit was developed and tested under the EU H2020 project MultiPACK, which has the main goal of assuring the market about the feasibility, reliability, and energy efficiency of CO2 integrated systems for heating and cooling and promoting a fast transition to low environmental impact solutions. Within the project, the confidence raising was performed by installation and monitoring of fully integrated state-of-the art CO2 systems in the Southern European Climate. With the aim of predicting the unit behaviour under variable load and boundary conditions, a dynamic model of the entire unit was developed with commercial software, considering actual components and the implemented control system and it was validated with experimental data, collected at the factory's lab before commissioning. The validation against experimental data collected during operation as a heat pump demonstrated a maximum percentage difference between the experimental and predicted value of gas–cooler heat flow rate equal to +5.0%. A preliminary comparison with the experimental data in chiller configuration is reported, however further development was required to achieve a satisfactory validation. Lastly, the numerical model was utilized to simulate a typical operation in heat pump configuration with the system coupled with a hot water tank storage for the production of domestic hot water and space heating; the model predicts higher COP when operating in domestic hot water operation due to the lower water inlet temperature. [ABSTRACT FROM AUTHOR]

A detailed analysis and validation of the DC-DC boost converter based on the three-state switching cell (3SSC) type-A are presented in this paper. The study of this topology is justified by the small amount of research that employs 3SSC-A and the advantages inherent to 3SSC-based converters, such as the division of current stresses between the semiconductors, the distribution of thermal losses, and the high-density power. Therefore, a complete static analysis of the converter is described, as well as the study of all voltage and current stresses in the semiconductors, the development of a loss model in all components, and a comparison with other step-up structures. Additionally, the small-signal model validation is accomplished by comparing the theoretical frequency response and the simulated AC sweep analysis. Finally, implementing a simple controller structure, the converter is experimentally validated through a 600 W prototype, where its overall efficiency is examined for various load conditions, reaching 96.8% at nominal load. [ABSTRACT FROM AUTHOR]

The aim of the article is to numerically model a two-dimensional multiphase flow based on the volume of fluid method (VOF) in a pulsating heat pipe (PHP). The current state of knowledge regarding the modeling of these devices was studied and summarised. The proposed model is developed within open source software, OpenFOAM, based on the predefined solver called interPhaseChangeFoam. The analyses were carried out in terms of the influence of four different mass transfer models between the phases, proposed by Tanasawa, Lee, Kafeel and Turan, and Xu et al. on the shape and dynamics of the internal flow structures. The numerical models were validated against data obtained from a specially designed experimental setup, consisting of three bends of pulsating heat pipes. The numerical calculations were carried out with ethanol being treated as a working medium and the initial and boundary conditions taken directly from the measurement procedures. The variable input parameter for the model was the heat flux implemented in the evaporation section and a fixed temperature applied to the condensation section. The flow structures obtained from the numerical analyses were compared and discussed with the flow structures gained from experimental studies by employing a high speed camera. In addition, to verify the quantitative results obtained from the numerical analyses with the experimental data, a technique called particle image velocimetry (PIV) was used for the velocity vector field. For the analysed velocity ranges, the relative error obtained was reached at the level of 10%. [ABSTRACT FROM AUTHOR]

Tire yaw marks deposited on the road surface carry a lot of information of paramount importance for the analysis of vehicle accidents. They can be used: (a) in a macro-scale for establishing the vehicle's positions and orientation as well as an estimation of the vehicle's speed at the start of yawing; (b) in a micro-scale for inferring among others things the braking or acceleration status of the wheels from the topology of the striations forming the mark. A mathematical model of how the striations will appear has been developed. The model is universal, i.e., it applies to a tire moving along any trajectory with variable curvature, and it takes into account the forces and torques which are calculated by solving a system of non-linear equations of vehicle dynamics. It was validated in the program developed by the author, in which the vehicle is represented by a 36 degree of freedom multi-body system with the TMeasy tire model. The mark-creating model shows good compliance with experimental data. It gives a deep view of the nature of striated yaw marks' formation and can be applied in any program for the simulation of vehicle dynamics with any level of simplification. [ABSTRACT FROM AUTHOR]

This article presents a numerical model of an aeronautical hybrid electric propulsion system (HEPS) based on an energy method. This model is designed for HEPS with a total power of 100 kW in a parallel configuration intended for ultralight aircraft and unmanned aerial vehicles (UAV). The model involves the interaction between the internal combustion engine (ICE), the electric motor (EM), the lithium battery and the aircraft propeller. This paper also describes an experimental setup that can reproduce some flight phases, or entire missions, for the reference aircraft class. The experimental data, obtained by reproducing two different take-offs, were used for model validation. The model can also simulate anomalous operating conditions. Therefore, the tests chosen for the model validation are characterized by the EM flux weakening ("de-fluxing"). This model is particularly suitable for preliminary stages of design when it is necessary to characterize the hybrid system architecture. Moreover, this model helps with the choice of the main components (e.g., ICE, EM, and transmission gear ratio). The results of the investigation conducted for different battery voltages and EM transmission ratios are shown for the same mission. Despite the highly simplified model, the average margin of error between the experimental and simulated results was generally under 5%. [ABSTRACT FROM AUTHOR]

The purpose of this work is to determine the values of electrical parameters of synchronous and induction machines to validate electrical interactions between an induction generator and a synchronous generator. The generators are connected in two ways: (i) isolated from the common bus and (ii) parallel to the common bus in steady state, subject to nonlinear load. They are old and refurbished machines; thus, the parametric regression methodology is used to determine the electrical parameter values. After the computational model validation, analyses are performed by various system configurations to confirm the repowering and to analyze the system harmonic current flow. The results obtained comparing the computer simulation and experimental tests prove that the validated model represents the real system. With an experimentally validated computational model, it is possible to verify the occurrence of system repowering and the increased value of harmonic distortions in the induction generator terminals, acting as a preferential path for harmonic currents. [ABSTRACT FROM AUTHOR]

Efficient and accurate estimations of unidentified parameters of photovoltaic (PV) models are essential to their simulation. This study suggests two new variants of the whale optimization algorithm (WOA) for identifying the nine parameters of the three-diode PV model. The first variant abbreviated as RWOA is based on integrating the WOA with ranking methods under a novel updating scheme to utilize each whale within the population as much as possible during the optimization process. The second variant, namely HWOA, has been based on employing a novel cyclic exploration-exploitation operator with the RWOA to promote its local and global search for averting stagnation into local minima and accelerating the convergence speed in the right direction of the near-optimal solution. Experimentally, RWOA and HWOA are validated on a solar cell (RTC France) and two PV modules (Photowatt-PWP201 and Kyocera KC200GT). Further, these proposed variants are compared with five well-known parameter extraction models in order to demonstrate their notable advantages over the other existing competing algorithms for minimizing the root mean squared error (RMSE) between experimentally measured data and estimated one. The experimental findings show that RWOA is superior in some observed cases and superior in the other cases in terms of final accuracy and convergence speed; yet, HWOA is superior in all cases. [ABSTRACT FROM AUTHOR]

A number of microeconomic choice models are currently applied to demonstrate systematic biases in energy consumer behavior. The models highlight the hidden potential of energy savings from policies that target the so-called behavioral anomalies. Nevertheless, whether these patterns are repeatable or not is not clear, because the efforts to determine the transferability or generalizability of these models are practically nonexistent. This paper uses a unique collection of empirical data from five EU countries collected within the CONSEED project to refine and develop further the standard consumer decision model, validate it for policy purposes, and elaborate on its transferability between countries. The pooled samples allow for a more reliable investigation of the relative importance of the factors influencing consumers' attitudes and beliefs towards energy investment decisions. Based on the statistical tests conducted to evaluate the "transferability" of the pooled models (i.e., the possibility of creating a "universal" model of EE from the pooled model), it can be argued that the models are transferable in specific cases since attitudinal factors and demographic characteristics play a significant role. Although the pooled models are validated, any extrapolation of the above-mentioned findings to specific populations in terms of "space" (i.e., country) and "target" (e.g., sectors and technologies) should be approached with caution from a policy perspective. [ABSTRACT FROM AUTHOR]

Electro-hydraulic compact drives (ECDs) are an emerging technology for linear actuation in a wide range of applications. Especially within the low power range of 5–10 kW, the plug-and-play capability, good energy efficiency and small space requirements of ECDs render this technology a promising alternative to replace conventional valve-controlled linear drive solutions. In this power range, ECDs generally rely on passive cooling to keep oil and system temperatures within the tolerated range. When expanding the application range to larger power classes, passive cooling may not be sufficient. Research investigating the thermal behaviour of ECDs is limited but indeed required for a successful expansion of the application range. In order to obtain valuable insights into the thermal behaviour of ECDs, thermo-hydraulic simulation is an important tool. This may enable system design engineers to simulate thermal behaviour and thus develop proper thermal designs during the early design phase, especially if such models contain few parameters that can be determined with limited information available. Our paper presents a lumped thermo-hydraulic model derived from the conservation of mass and energy. The derived model was experimentally validated based on experimental data from an ECD prototype. Results show good accuracy between measured and simulated temperatures. Even a simple thermal model containing only a few thermal resistances may be sufficient to predict steady-state and transient temperatures with reasonable accuracy. The presented model may be used for further investigations into the thermal behaviour of ECDs and thus toward proper thermal designs required to expand the application range. [ABSTRACT FROM AUTHOR]

In Thailand, Napier grass is expected to play an important role as an energy resource for future power generation. To accomplish this goal, numerous areas are required for Napier grass plantations. Before introducing crops, the land potential of the country and the impact of crops on the environment should be assessed. The soil and water assessment tool (SWAT) model is very useful in investigating crop impacts and land potential. Unfortunately, the crop growth parameters of Napier grass are yet to be identified and, thus, conducting effective analysis has not been possible. Accordingly, in this study, parameter calibration and SWAT model validation of Napier grass production in Thailand was carried out using datasets from eight sites with 93 samples. Parameter sensitivity analysis was performed prior to parameter calibration, the results of which suggest that the radiation use efficiency and potential harvested index are both highly sensitive. The crop growth parameters were calibrated in order of their sensitivity index ranking, and the final values were obtained by reducing the root mean square error from 10.77 to 1.38 t·ha−1. The validation provides satisfactory results with coefficient of determination of 0.951 and a mean error of 0.321 t·ha−1. Using the developed model and calibrated parameters, local Napier grass dry matter yield can be evaluated accurately. The results reveal that, if only abandoned area in Thailand is used, then Napier grass can provide roughly 33,600–44,900 GWh of annual electricity, and power plant carbon dioxide (CO2) emissions can be reduced by approximately 21.2–28.3 Mt-CO2. The spatial distribution of estimated yield obtained in this work can be further utilized for land suitability analysis to help identify locations for Napier grass plantations, anaerobic digesters, and biogas power plants. [ABSTRACT FROM AUTHOR]

The working capability of multi-stage pumps, such as electrical submersible pumps (ESPs) handling multiphase flow, has always been a big challenge for petroleum industries. The major problem is associated with the agglomeration of gas bubbles inside ESP-impellers, causing pump performance degradation ranging from mild to severe deterioration (surging/gas pockets). Previous literature showed that the two-phase performance of ESPs is greatly affected by gas involvement, rotational speed, bubble size, and fluid viscosity. Thus, it is necessary to understand which parameter is actually accountable for performance degradation and different flow patterns in ESP, and how it can be controlled. The present study is mainly focused on (1) the main parameters that impede two-phase performance of different ESPs; (2) comparison of existing empirical models (established for two-phase performance prediction and surging initiation) with our single-stage centrifugal pump results to determine their validity and working-range; (3) gas-handling techniques applied to enhance the multiphase performance of ESPs. Firstly, it aims at understanding the internal flow mechanism in different ESP designs, followed by test studies based on empirical models, visualization techniques, bubble-size measurements, and viscosity analysis. The CFD-based (computational fluid dynamics) numerical analysis concerning multiphase flow is described as well. Furthermore, gas-handling design methods are discussed that are helpful in developing the petroleum industry by enhancing the multiphase performance of ESPs. [ABSTRACT FROM AUTHOR]