Search

Owing to its essential features, such as modularity and exceptional power quality, the modular multilevel converter (MMC) emerges as the optimal converter topology for high-voltage direct current (HVDC) applications. Traditionally, MMCs are controlled through a method called nearest level modulation (NLM), which generates N+1 AC output voltages, where N represents the number of sub modules (SMs) per arm. In this paper, we introduce a modified NLM technique designed to yield 2N+1 and 4N+1 levels, with a focus on efficiently controlling internal dynamics. The proposed MMC is evaluated using a hardware-in-the-loop (HIL) environment to obtain real-time simulation outcomes. This MMC topology demonstrates a reduction in circulating currents and capacitor voltage ripple. [ABSTRACT FROM AUTHOR]

This paper develops a multi agent system in real time for hybrid microgrids as advanced energy management (ADEM) protocol using a Java agent development environment (JADE) frame work. The proposed system is configured with two micro-grids, each having 1kw solar photo voltaic power, 1.5Kw wind power, 24 V, 150AH battery along with a local load, thus making it a hybrid Microgrid, modelled in MATLAB/Simulink. Due stability constraints while using MATLAB/Simulink, in a multi-threading environment, a middle ware called Multi agent Control Using Simulink with Jade Extension (MACSimJX) is adopted. The microgrid environment variables are captured through sensors, delivered to the agents operations in JADE, for the implementation of dynamic operation in hybrid microgrids. This results in maximizing operational efficiency of hybrid microgrids system. The simulation suggests that MAS can successfully manage dynamic loads, generated power in real time microgrids.

Hybrid electric vehicle (HEV) is one of the ideal transportation tools to face the challenge of ‘Carbon peak carbon neutralization’. The high complexity of the latest HEVs result to the difficulties in vehicle fault diagnostics, which is considered to be the main factors of vehicle durability. In this study, a multi-fault mode detection method of a P2 diesel HEV was investigated by using support vector machine(SVM). The HEV physical model was built and validated by using the experimental data under China typical urban driving cycle (CTUDC). The SVM algorithm was coded in Matlab/Simulink environment. The training data vectors for normal mode and fault mode were acquired from the HEV model. Through the analysis of failure mode, the OVO-SVM method was proved as the best accuracy, the success rate of diagnosis reaches 98%. Case studies of single fault mode and multi-fault mode fault detection were conducted. Offline and online level test were performed to show the effectiveness of the detection algorithm. The study may support the development of intelligent diagnostic methods for the different types of HEVs.

This article proposes a new method of modelling dynamic loads based on instantaneous p-q theory, to be employed in large powers system network simulations in a digital real-time environment. Due to the use of computationally heavy blocks such as phase-locked-loop (PLL), mean calculation,and coordinate transformation blocks (e.g., abc–dq0), real-time simulation of large networks with dynamic loads can be challenging. In order to decrease the computational burden associated to the dynamic load modelling, a p-q theory-based approach for load modelling is proposed in this paper. This approach is based on the well-known p-q instantaneous theory developed for power electronics converters, and it consists only of linear controllers and of a minimal usage of control loops, reducing the required computational power. This improves real-time performance and allows larger scale simulations. The introduced p-q theory-based load (PQL) model has been tested on standard networks implemented in a digital real time simulator, such as the SimBench semi-urban medium voltage network and the 118-bus Distribution System, showing significant improvement in terms of computational capability with respect to standard load models (e.g., MATLAB/Simulink dynamic load).

Micro‐grid islanding methods are gaining importance as the presence of renewable energy resources is becoming increasingly popular in power distribution. Among all the islanding methods, passive methods are easy to implement and applicable to all types of DERs provided the NDZ is minimized. This article presents a novel passive islanding detection method based on the CSoDoA of ellipse formed by the successive phase voltages to address the NDZ problem. The peak magnitude and phase angle difference of voltages are the parameters to be estimated to compute the area of the ellipse. State‐of‐the‐art passive methods consider the effect of either magnitude or phase angle or frequency as an islanding detection metric. The CSoDoA metric combines the effect of both magnitude and phase angle thereby reducing the NDZ. The proposed method is validated on both synchronous and inverter‐interfaced DERs. The test systems considered are both single‐DER based MG and modified IEEE 13 bus multi‐DER MG. The CSoDoA algorithm is implemented on a Raspberry‐Pi controller and validated using HIL workbench with real‐time simulator OP‐4510. Various islanding and non‐islanding events are simulated, tested and it is evident from the results that it has a very small NDZ. [ABSTRACT FROM AUTHOR]

Despite the existence of computationally efficient tools, the effort for parametric investigations is currently high in industry. In this paper, within the context of Li-Ion batteries, an efficient meta-modelling approach based on the Proper Generalized Decomposition (PGD) is considered. From a suitable design of experiments, a parametric model is trained and then exploited to predict, in real time, the system response to a specific parameter combination. In particular, two different methods are considered, the sparse PGD (sPGD) and the anchored-ANOVA based one (ANOVA-PGD). As a use case for the method the dynamic indentation test of a commercial lithium-ion pouch cell with a cylindrical impactor is selected. The cell model considers a homogenised macroscopic structure suitably calibrated for explicit finite element simulations. Four parameters concerning the impactor are varied, both non-geometric (mass and initial velocity) and geometric (diameter and orientation). The study focuses on multi-dimensional outputs, such as curves and contour plots. Inspired by earlier studies, the sPGD is used to predict the force-displacement curves. As a further development, the impactor kinetic energy curve and the displacement contours are both predicted using its recently developed variant ANOVA-PGD. Moreover, a novel curve alignment technique based on the Gappy Proper Orthogonal Decomposition (Gappy-POD) is suggested here. The meta-model is compared to the results of an FE simulation and the resulting deviations are then discussed.

The trend toward higher switching frequency and larger scale of power electronic systems poses challenges for real-time simulation. This article presents an event-driven hardware-in-the-loop (ED-HIL) simulation framework that does not rely on the small fixed simulation step-size related to the switching frequency. ED-HIL framework can improve the calculation efficiency by positioning switch events and using variable simulation step-size. Further, a parallel acceleration and circuit partitioning (PACP) solver is proposed based on this framework. The PACP solver partitions the circuit with energy storage elements and ensures that the partitioning does not introduce simulation distortion by using the higher order derivatives of the energy storage elements. Meanwhile, it achieves a process-level paralleling through a shared memory architecture in order to accelerate the simulation. As a result, the proposed PACP solver based on the ED-HIL framework can achieve about three times the simulation scale of a commercial FPGA-based real-time simulator at 1/16 the hardware cost under the same conditions. An accurate real-time HIL example of a power electronic transformer with 32 switches at a switching frequency of 20 kHz has been implemented on a personal computer. The simulation results are analyzed by comparing with experiment, offline software, and commercial real-time simulator. [ABSTRACT FROM AUTHOR]

Investigations of the dynamic behaviour of power electronic components integrated into electric networks require suitable and established simulation methodologies. Real-time simulation represents a frequently applied methodology for analyzing the steady-state and transient behavior of electric power systems. This work introduces a guideline on how to model power electronics converters in digital real time simulators, taking into account the trade-off between model accuracy and the required computation time. Based on this concept, possible execution approaches with respect to the usage of central processing unit and field-programmable gate array components are highlighted. Simulation test scenario, such as primary frequency regulation and low voltage ride through, have been performed and accuracy indices are discussed for each implemented real-time model and each test scenario, respectively. Finally, a run-time analysis of presented real-time setups is given and real-time simulation results are compared. This manuscript demonstrates important differences in real-time simulation modelling, providing useful guidelines for the decision making of power engineers.

The arrival of the energy transition to the global electricity scene has led to the implementation of new technologies in power systems and modified the way that the energy is generated, distributed and consumed. The analysis of the operation and the consequences of the inclusion of new technologies become a very important topic in the studies carried out by the utilities. Real-Time Digital Simulators (RTDS) have become a powerful modeling tool that allow to analyze power system models with a high level of fidelity, permitting to anticipate problems and the assessment of solution strategies. Due to the increase in the use of this technology and considering that there are no review articles on RTDS applications written in Spanish, this paper presents an explanation of the characteristics of RTDS along with an updated state of the art related to applications in Energy Transition as a theoretical framework with a large amount of information collected for future researches in Latin America. [ABSTRACT FROM AUTHOR]

The paper is focused on the development of the digital twin of the hydraulic control valve for continuous control of the oil flow -- servovalve or control valve -- and their use by the testing of the control system of the test rig for the measurement and evaluation of the characteristics of the valve. The structure of the mathematical model of the control valve enables to do the parameterisation for different types and sizes of the control valves only using the catalogue data delivered by the valve producers. In the next step the created and parameterized model is implemented into the dSpace MicroLabBox for the real time realisation of the digital twin. The MicroLabBox is equipped with the analogue inputs and outputs and allows the connection of the digital twin to the control system in the same way as the real servovalve. Finally, the characteristics of the valve are measured and evaluated using the HiL simulation of the digital twin. The digital twin of the servovalve allows the testing of the developed control system and software for the hydraulic test rig for the measurement of the valve characteristics without the need of the real valves different types. [ABSTRACT FROM AUTHOR]

Real Time Simulation (RTS) has long been used in the nuclear power industry for operator training and engineering purposes. And, Online Simulation (OLS) is based on RTS and with connection to the plant information system to acquire the measurement data in real time for calibrating the simulation models and following plant operation, for the purposes of analyzing plant events and providing indicative signs of malfunctioning. An OLS system has been developed to support PWR operations for CPR1000 plants. The OLS system provides graphical user interface (GUI) for operators to monitor critical plant operations for preventing faulty operation or analyzing plant events. Functionalities of the OLS system are depicted through the maneuvering of the GUI for various OLS functional modules in the system.

To determine the impact of emergent transition from in-person to remote learning on student performance within real-time objective structured clinical examinations (OSCEs). A university mandate, due to severe SARS-CoV-2, was issued requiring didactic courses to transition to remote learning in spring 2020. The third-year internal medicine elective had six remaining weekly OSCEs, accounting for 55% of course grades. Full credit was awarded for the first OSCE as students familiarized themselves with the new virtual format. The primary outcome was the overall average OSCE performance for the course's remaining five virtual simulations compared to the traditional in-person offering in 2019. Secondary outcomes included individual OSCE performance, OSCE performance with inclusion of the first OSCE, and overall course grades. There were no statistically significant differences in overall average OSCE performance between 2019 and 2020 cohorts for the five simulations (82.7% vs. 86.8%, P =.20). Secondary outcomes showed statistically significant differences favoring performance in the 2020 cohort for infectious diseases (78.3% vs. 89.4%, P <.001) and anticoagulation (74.4% vs. 90%, P =.002), while cardiology favored the 2019 cohort (91.1% vs. 82.8%, P =.03). There was no statistically significant difference in performance on the cumulative I (86.1% vs. 82.2%, P =.41) or cumulative II (83.3% vs. 89.4%, P =.29) simulations or in final overall course grades (86.6% vs. 90.2%, P =.06). An emergent transition to remote learning may not negatively impact student performance on real-time OSCE activities. [ABSTRACT FROM AUTHOR]

Economic dispatch in the presence of wind farms is of high interest in power system operational planning. Due to the uncertainty of wind speed and wind power, a probabilistic model is needed for application in economic dispatch solution. The weibull probability distribution function is a common tool to model wind speed probabilistic behavior, but the main challenge is the nonlinearity of wind power generation with respect to wind speed. This causes complexity in probabilistic economic dispatch, which can lead to numerical and time-consuming solution methods. Therefore, linearization of the wind power curve is in the interest of some methods by simply connecting the first point to end point of power curve by a straight line. In this paper, by developing a conventional objective function for ED solution, two main contributions are made to obtain a suitable method for fast and also good accuracy results in real time purposes. At first, an improved method for linearization of wind power curve with respect to previous works is introduced which increases the performance of modelling with respect to the nonlinear model as the base model. The second contribution is developing an analytical routine for economic dispatch by an acceptable time-consuming calculation suitable for real time purposes. The effectiveness of the new approach has been tested on two test systems. The results show the improvement in relative error in ED cost with respect to real nonlinear curve model which reduces the error about one fifth regard to the conventional linearization model.

Aircraft ground braking control is a complex time-varying dynamic problem, especially when there are unexpected disturbances from lateral wind or visual error. Therefore, under some extreme conditions, it is hard for the pilot to control aircraft braking as well as usual without assistant control. This paper solves this problem by proposing a novel assistant control for aircraft ground braking, mainly based on the pilot control model and the LPV theory. And in order to reflect the control characteristics of the pilot, the sensory and control-theoretic model were combined together for controller designing. To test the performance of proposed control method, a real time pilot-in-loop simulation system is constructed. According to experiment results, the proposed assistant control shows better performance than pilot control, for it not only help the pilot to resist disturbance, but also hardly run counter to the pilot's intent.

The discrete element method (DEM) is widely used to tackle problems associated with granular material processing. Its applications are diverse, ranging from powder mixing to transport and fluidized beds. Computational costs are a major issue with regard to DEM. Long process times combined with a large numbers of particles require simulations that can last months. In this paper we apply an extrapolation method based on pseudo-steady state DEM bulk behavior to allow for the long repetitive process to be completed. The extrapolation method is applied to two processes relevant to the pharmaceutical industry: continuous mixing and a tablet press feed frame. The results of the extrapolation method are validated against full DEM simulations of the complete process in terms of residence time, travel distance, and velocity distributions. The DEM extrapolation for pseudo-steady state processes resulted in an enormous reduction of the simulation time, while retaining residence times, travel distance and velocity distributions. [Display omitted] • DEM extrapolation applied for continuous processes. • Comparison between conventional DEM and DEM extrapolation. • Analysis of residence time, distances travelled by particles and velocities. • Very good agreement between both DEM and DEM extrapolation. • Massive speed-up possible. [ABSTRACT FROM AUTHOR]

This paper develops a multi agent system in real time for hybrid microgrids as advanced energy management (ADEM) protocol using a Java agent development environment (JADE) frame work. The proposed system is configured with two micro-grids, each having 1kw solar photo voltaic power, 1.5Kw wind power, 24 V, 150AH battery along with a local load, thus making it a hybrid Microgrid, modelled in MATLAB/Simulink. Due stability constraints while using MATLAB/Simulink, in a multi-threading environment, a middle ware called Multi agent Control Using Simulink with Jade Extension (MACSimJX) is adopted. The microgrid environment variables are captured through sensors, delivered to the agents operations in JADE, for the implementation of dynamic operation in hybrid microgrids. This results in maximizing operational efficiency of hybrid microgrids system. The simulation suggests that MAS can successfully manage dynamic loads, generated power in real time microgrids. [ABSTRACT FROM AUTHOR]

The Quai des Trois Fontaines is a berthing area in Chooz, France, which was designed for 80 m long vessels (CEMT Class IV) plying the River Meuse. A turning basin is located in front of the Quai des Trois Fontaines to allow vessels to turn before loading at the quay. Real time simulations on a dedicated inland ship manoeuvring simulator at Flanders Hydraulics Research were carried out with experienced skippers to study how the safety of the turning manoeuvre could be improved and which measures are required for safe manoeuvres with longer vessels, i.e. vessels of 85 and 90 m in length. In the first phase of the study, turning manoeuvres of CEMT Class IV vessels of 80 m, 85 m and 90 m long were studied in the existing environment. The manoeuvres were evaluated based on different safety criteria and on the feedback of the pilots. The real time simulations have shown that the actual design of the turning basin is suitable for the 80 m long vessels in any hydro-meteorological condition. However, the manoeuvres become risky with 85 m long vessels under certain conditions and impossible with longer ships. Although the current can be very strong on the river Meuse, the local width turned out to be the most critical parameter. In the second phase of the study, measures were proposed to allow the safe turning of 85 m and 90 m long vessels. Local widening of the river to 100 m and to 105 m were proposed for 85 m and 90 m long ships respectively. A third proposed measure is to provide a fixed point near the end of the quay, to which the vessels can attach and around which they can then turn.

This article assesses the impact on the Power Quality produced by the interconnection of a microgrid to a transmission system, real-time simulation have been used to carry out the study, applying national and international power quality standards, IEEE 1547 of 2018, IEEE 519 of 2014 and NTC 5001 of 2008. The phenomena of voltage harmonics, current harmonics, flicker and DC injection were evaluated on a microgrid case study. The results show that the interconnection of the microgrid produces a high impact on the current harmonics and the DC injection of the local transmission system, while the flicker phenomena and voltage harmonics have a smaller impact.

This paper investigates the response to grid disturbances of the wind energy conversion system based on the doubly fed induction generator (DFIG-based WECS). It is proposed a new control termed as heightened state-feedback control structure (HSFC) with predictive behavior to regulate the rotor current loops, which is able to effectively counteract the back electromotive force surge oscillating dynamics that occur in the event of a disturbance in the grid voltage. The proposed method is able to mitigate oscillations in DFIG currents exempting the need to use low voltage ride-through current-modify (LVRT-CM) strategies during intermediate symmetrical and asymmetrical voltage sags or during the voltage recovery process, while provide the DFIG to contribute active and reactive current featuring bounded torque oscillations. During severe faults, the proposed structure is able to effectively track the required post-fault rotor current references as demanded by LVRT-CM, which allows the DFIG to ride-through the fault with constrained currents and torque. The proposed structure also employs a novel flux damping technique which accentuate the rotor d-axis current in order to significantly reduce stator flux settling time after faults, while the torque minimally oscillates during post-fault recovery. Real-time digital simulations and experimental results considering symmetrical and asymmetrical voltage sags due to faults show the proposed solutions advantages over classical and previous strategies. [ABSTRACT FROM AUTHOR]

This article presents the simulation of a BLDC motor and its closed control system in FPGA. The simulation is based on a mathematical model of the motor, including the electromagnetic torque, phase currents, back electromotive force, etc. In order to ensure calculation precision, the equations describing the motor were solved using a floating point representation of real numbers, and a small step of numerical calculations of 1 μs was assumed. The time step selection methodology has been discussed in detail. The motor model was executed with the use of Textual Programming Languages (with HDL codes).

Thirst for energy is increasing significantly with increase in economy around the world which burdens conventional grid (CG) due to peak demand, energy deficit, and carbon emission, but major part of continents has plentiful wind and solar energy which can be harnessed locally to minimize it. Major objective of this research is to reduce the peak power deficit present in CG system and to provide a reliable power supply even in case of grid failure or during blackout. In this paper, development and evaluation of a small scale grid interactive dc microgrid for residential houses, telecommunication systems, and data center has been proposed. The objective is being achieved by designing a comprehensive power flow control strategy and explored for different practical scenarios through real time simulation in RSCAD/RTDS platform. A prototype is developed to validate the simulation results presented during grid connected and isolated mode. [ABSTRACT FROM AUTHOR]

In this paper, modeling, analysis, design and simulation of a POSICAST controller are presented for application in a generator's excitation system. Simple structure is the most important characteristic of this controller. The controller is a feedforward compensator; it eliminates intensive over/undershoots in system dynamic response. Since changing the reference signal in the excitation system of the synchronous generator causes oscillations in the terminal voltage, the POSICAST controller (PC) is applied at the outset of the excitation system to mitigate these oscillations. The impact of the proposed controller on the stability of the studied power system is evaluated by both eigenvalues analysis and experimental results. In order to validate the theory, the performance of the designed controller is verified in OPAL-RT by experimental approach. [ABSTRACT FROM AUTHOR]

Microgrids today include more and more renewable sources both for environmental and economic reasons. The advantage of microgrids is their capacity of running isolated. The presence of largely uncontrollable sources (PV plants and wind farms) makes the grid control a complex task. During the design stage it is mandatory to consider the expected variations of both loads and sources to identify proper solution for stabilizing the Microgrid when it runs isolated. The paper presents a simulator that was developed to support the design of the Microgrid both in terms of power devices and control techniques. The main goal of this simulator is to test the automation system of the Microgrid before its site installation. The simulator calculates the dynamic behavior of conventional generators, renewable source, and loads. The model of renewable sources includes the expected power variations as well as the random profile of loads. If required, energy storage systems can be integrated in the simulator. All the control set-point of controllable equipment and the calculated frequency and voltage of the Microgrid are interfaced with the control system using a standard Ethernet-base fieldbus. Such a solution makes it possible to study different control logics and to tune the control parameters of the system using the real control system. The data exchange between the simulator and the control system is identical to the real data flow that will be found in the Microgrid. With the use of the simulator, the control system of the Microgrid is implemented during the design stage, with reduced development, testing, and commissioning times. [ABSTRACT FROM AUTHOR]

Renewable integrated dc Microgrids (DCMGs) are gaining popularity by feeding remote locations in qualitative and quantitative manner. Reliability of autonomous dc microgrids depend on battery capacity and size due to stochastic behavior of renewables. Over charging and discharging scenarios compel the microgrid into insecure zone. Increasing the storage capacity is not an economical solution because of additional maintenance and capital cost. Thus, interconnecting neighbor microgrids increases virtual storing and discharging capacity when excess power and deficit scenario arises respectively in any of the DCMG. Control strategy plays vital role in regulating the power within and between microgrids. Power control and management technique is developed based on bus signaling method to govern sources, storages, and loads to achieve effective coordination and energy management between microgrids. Proposed scheme is simple and reliable since bus voltages are utilized in shifting the modes without having dedicated communication lines. Proposed scheme is validated through real time simulation of two autonomous dc grids in real time digital simulator (RTDS) and its results are verified by hardware experimentation. [ABSTRACT FROM AUTHOR]

This paper presents modeling and study of 12-pulse HVDC (High Voltage Direct Current) based on real time simulation where the HVDC inverter is connected to a weak AC system. In goal to study the dynamic performance of the HVDC link, two serious kind of disturbance are applied at HVDC converters where the first one is the single phase to ground AC fault and the second one is the DC link to ground fault. The study is based on two different mode of analysis, which the first is to test the performance of the DC control and the second is focalized to study the effect of the protection function on the system behavior. This real time simulation considers the strength of the AC system to witch is connected and his relativity with the capacity of the DC link. The results obtained are validated by means of RT-lab platform using digital Real time simulator Hypersim (OP-5600), the results carried out show the effect of the DC control and the influence of the protection function to reduce the probability of commutation failures and also for helping inverter to take out from commutation failure even while the DC control fails to eliminate them. [ABSTRACT FROM AUTHOR]

This study aims to construct a reduced thermodynamic cycle model with high accuracy and high model execution speed based on artificial neural network training for real-time numerical analysis. This paper proposes a method of constructing a fast average-value model by combining a 1D plant model and exhaust gas recirculation (EGR) control logic. The combustion model of the detailed model uses a direct-injection diesel multi-pulse (DI-pulse) method similar to diesel combustion characteristics. The DI-pulse combustion method divides the volume of the cylinder into three zones, predicting combustion- and emission-related variables, and each combustion step comprises different correction variables. This detailed model is estimated to be within 5% of the reference engine test results. To reduce the analysis time while maintaining the accuracy of engine performance prediction, the cylinder volumetric efficiency and the exhaust gas temperature were predicted using an artificial neural network. Owing to the lack of input variables in the training of artificial neural networks, it was not possible to predict the 0.6−0.7 range for volumetric efficiency and the 1000−1200 K range for exhaust gas temperature. This is because the mean value model changes the fuel injection method from the common rail fuel injection mode to the single injection mode in the model reduction process and changes the in-cylinder combustion according to the injection timing of the fuel amount injected. In addition, the mean value model combined with EGR logic, i.e., the single-input single-output (SISO) coupled mean value model, verifies the accuracy and responsiveness of the EGR control logic model through a step-transient process. By comparing the engine performance results of the SISO coupled mean value model with those of the mean value model, it is observed that the SISO coupled mean value model achieves the desired target EGR rate within 10 s. The EGR rate is predicted to be similar to the response of volumetric efficiency. This process intuitively predicted the main performance parameters of the engine model through artificial neural networks.

In order to systematically shift existing control and management paradigms in distribution systems to new interoperable communication supported schemes in smart grids, we need to map newly developed use cases to standard reference models like Smart Grid Architecture Model (SGAM). From the other side, any new use cases should be tested and validated ex-ante before being deployed in the real-world system. Considering various types of actors in smart grids, use cases are usually tested using co-simulation platforms. Currently, there is no efficient co-simulation platform which supports interoperability analysis based on SGAM. In this paper, we present our developed test platform which offers a support to design new use cases based on SGAM. We used this platform to develop a new scheme for wide area monitoring of existing distribution systems under growing penetration of Photovoltaic production. Off-the-shelf solutions of state estimation for wide area monitoring are either used for passive distribution grids or applied to the active networks with wide measurement of distributed generators. Our proposed distribution state estimation algorithm does not require wide area measurements and relies on the data provided by a PV simulator we developed. This practical scheme is tested experimentally on a realistic urban distribution grid. The monitoring results shows a very low error rate of about 1 % by using our PV simulator under high penetration of PV with about 30 % error of load forecast. Using our SGAM-based platform, we could propose and examine an Internet-of-Things-based infrastructure to deploy the use case.

In many applications, the solution of a linear system is computed with Gaussian elimination followed by back-substitution, or Gauss–Jordan elimination. The latter is intrinsically more parallel, enabling smaller computing latencies at the price of more complex hardware. However both methods require the division operator, which leads to a time-consuming resource in the critical path of the algorithms and impacts the global processing’s latency. Jordan was already aware of a division free algorithm. However, its implementation involves multiplications at each step and the size of the numbers rapidly becomes too big for an efficient implementation of large systems. In this work, we present a small modification to the division free algorithm in order to keep the size of the numbers in a reasonable range for standard floating point numbers. This is possible thanks to the special format of floating point numbers, which enables error free and hardware efficient divisions by powers of two. We also propose a parallel and pipelined architecture that best exploits the proposed algorithm, including partial pivoting. We specially focus on the global latency of the system as a function of its size, the latency of the floating point operators, and the number of operators that are available. Results demonstrate that current FPGAs can solve linear systems larger than hundred equations within ten microseconds. This represents a two order of magnitude improvement over previous implementations for relatively small systems. [ABSTRACT FROM AUTHOR]

Composites manufacturing processes usually involve multiscale models in both space and time, highly non-linear and anisotropic behaviors, strongly coupled multiphysics and complex geometries. In this framework, the use of simulation for real-time decision making directly in the manufacturing facility is still precluded nowadays, in spite of the impressive progresses reached in numerical analysis and computer science during the last decade. In this paper, a process-specific simulation tool based on reduced order modeling is introduced, the Simulation App. This concept is presented through a practical case involving a multi-physics and coupled problem describing the manufacturing process of a composite outlet guide vane. We show that several manufacturing settings can be simulated in few seconds with the Simulation App, thus enabling fast process optimization. Finally, the advantages over general-purpose simulation software, in the context of process simulation, are discussed. [ABSTRACT FROM AUTHOR]

This paper addresses the implementation of a real time simulator based on an existing electromagnetic simulating program called ATP-EMTP. The simulator is developed to stream sampled values on an Ethernet network using the protocol IEC61850-9-2. This implementation is done on a general purpose PC. The minimum simulation time step and the maximum sample rate achieved were 69 μs and 240 S/cycle respectively. The main components of the development as well as the evaluation of the performance of the simulator for different cases are described in this paper. [ABSTRACT FROM AUTHOR]

Solid State Transformers (SST) are attracting considerable attention due to their great application potential in future smart grids. It is an essential technology capable of promoting the modernization of the electric power distribution system and it is considered a key element for interfacing future microgrid systems to medium voltage utility grids, allowing plug-and-play integration with multiple renewable energy sources, storage devices and DC power systems. Its main advantages in relation to conventional transformers are substantial reduction of volume and weight, fault isolation capability, voltage regulation, harmonic filtering, reactive power compensation and power factor correction. A three-stage modular cascaded topology has been considered as an adequate candidate for the SST implementation, consisting of multiple power modules with input series and output parallel connection. The modular structure presents many advantages, e.g., redundancy, flexibility, lower current harmonic content and voltage stress on the power switches, however component tolerances and mismatches between modules can lead to DC link voltage imbalance and unequal power sharing that can damage the solid state transformer. This paper proposes a decentralized strategy based on adaptive droop control capable of promoting voltage and power balance among modules of a modular cascaded SST, without relying on a communication network. The behavior of the proposed strategy is assessed through a MATLAB/Simulink simulation model of an 100 kVA SST and shows that power and voltage balance are attained through inner power distribution of the SST modules, being transparent to elements connected to the transformer input and output ports. Besides that, real-time simulation results are presented to validate the proposed control strategies. The performance of embedded algorithms is evaluated by the implementation of the SST in a real-time simulation hardware, using a Digital Signal Processor (DSP) and high level programming.

The paper presents complex method of water areas optimisation withconsideration of navigational safety. The real time simulation method was implemented in presented study. The results were used as design guidelines for Ystad port development.

The core of this paper is the methodology of the dynamicalmodels’ simplification for the real time simulation. The simplified simulation models are based on neuro-fuzzymodelling approach, which was originally designed for predictive control-orientedmodelling of nonlinear dynamical systems. The two ways of the neuro-fuzzymodelling utilization are presented. First, the training of the predictive dynamical neuro-fuzzymodel and, second, the training of the statical approximation of the right-hand side of the system’s state space description. We demonstrate the results on the examples of nonlinear spring damper system and double pendulum.

Virtual process engineering (VPE) aims to redefine the roadmap for process scaling-up and optimization, from stepwise experiments to high-performance computer simulations. This is a long-cherished dream of chemical engineers, but requires high standards of Accuracy (the agreement between the simulation and the real process), Capability (the computational speed, scale, and resolution of the simulation), and Efficiency (cost-effective and easy to use), in short, ACE. For complex processes such as gas–solid fluidization, the gap between state-of-the-art simulations and VPE is still huge in terms of ACE. However, the work reported in this paper narrows this gap significantly. In this study, a coarse-grained discrete particle method (DPM) defined by the energy-minimization multi-scale (EMMS) model is deployed for high-resolution simulations of fluidized beds, with the gas- and solid-phase equations solved concurrently by CPUs and GPUs in a heterogeneous supercomputing system. With systematic optimization of the model, numerical method, software, and hardware, we are able to simulate lab- to pilot-scale fluidized beds at quasi-realtime speed, and conduct virtual experiments on such systems. This enables very-long-time simulations to obtain important engineering parameters such as the particle residence time distribution, attrition and deactivation indexes. This work demonstrates that the industrial application of VPE is almost on the horizon. [ABSTRACT FROM AUTHOR]

Classical Computational Fluid Dynamics (CFD) of long-time processes with strongly separated time scales is computationally extremely demanding if not impossible. Consequently, the state-of-the-art description of such systems is not capable of real-time simulations or online process monitoring. In order to bridge this gap, we propose a new method suitable to decouple slow from fast degrees of freedom in many cases. Based on the recurrence statistics of unsteady flow fields, we deduce a recurrence process which enables the generic representation of pseudo-periodic motion at high spatial and temporal resolution. Based on these fields, passive scalars can be traced by recurrence CFD. While a first, Eulerian Model A solves a passive transport equation in a classical implicit finite-volume environment, a second, Lagrangian Model B propagates fluid particles obeying a stochastic differential equation explicitly. Finally, this new concept is tested by two multiphase processes – a lab scale oscillating bubble column and an industrial scale steelmaking converter. Results of tracer distribution obtained by recurrence CFD are in very good agreement with full CFD simulations, while computational times are dramatically reduced. Actually, recurrence CFD is a promising candidate for online simulations of passive transport processes at full CFD resolution, which opens the door towards improved process monitoring. [ABSTRACT FROM AUTHOR]

A platform implemented with digital signal controllers (DSCs) developed for real time studies of the dynamic behavior of the air-gapped current transformers (CTs) used in power grid protection and measurement systems is presented. The implemented algorithms simulate the fault current in an electric power system as well as the transient response of the current transformer. A method for correcting the CT secondary current distortion is presented in the case of gapped core where residual flux is negligible. To estimate the flux, a tertiary winding must be available. The ratio and phase errors, as well as the distortions in secondary current due the core saturation in fault situations are properly corrected by the method. Several cases were tested and the results indicate that the proposed method is very effective in improving the performance of protection schemes based on the current measurement. [ABSTRACT FROM AUTHOR]

The VSC-based HVDC link between France and Spain (INELFE project: France-Spain ELectrical INterconnection) is currently the most powerful VSC link. This 2000 MW interconnection is composed of two parallel VSC links. For system studies and maintenance purposes, the replicas of the control systems have been acquired by the French (RTE) and the Spanish (REE) Transmission System Operators. This paper describes the hardware and software setup to perform Hardware In the Loop (HIL) simulations with the INELFE control system replicas. The converter and cable models used in the real-time simulation are presented. Modular Multilevel Converters present a major challenge for real-time simulation due to the large number of sub-modules and to the nonlinearities that shall be solved: transformer saturation and nonlinear characteristic of surge arresters that protect cables against switching transients. The paper presents how these issues have been solved in order to be able to test the control system with AC and DC faults. It is shown that iterative methods are used to provide accurate solutions in the presence of nonlinear devices but are not mandatory in this specific case. A complete setup has been developed in order to validate the modeling approach. HIL simulations have been performed with the real-time simulator connected to an external generic control system having the same interface than the replica. Real-time performance and simulation accuracy are fully achieved with the proposed solution. This solution has been used to interface the real-time simulator with the real control cubicles. The converter model is validated with on-site measurements. [ABSTRACT FROM AUTHOR]