Time-domain Simulation Method Research Articles

Mobileception-ResNet for transient stability prediction of novel power systems

Power system transient stability prediction (TSP) is particularly important as power systems change and evolve, including the rapid growth of renewable energy, the proliferation of electric vehicles, and the construction of smart grids. Traditional time-domain simulation methods are time-consuming and cannot achieve online prediction. Direct methods are poorly adapted and cannot be applied to complex power systems. Existing machine learning algorithms only classify the transient stability without providing the degree of transient stability of the system. Therefore, a fast and accurate power system TSP method is needed to assist operators in implementing timely measures to improve the stability of the power system running. This study proposes a Mobileception-ResNet network, Mobileception-ResNet is formed by Inception-ResNet-v2, MobileNet-v2, and a fully connected layer. In this study, Mobileception-ResNet and nine comparison models are experimented on two node systems, i.e., the IEEE 10–39 and 69–300 systems. In the IEEE 10–39 system, the root mean square error, mean absolute error, and mean absolute percentage error of Mobileception-ResNet are 44.13 %, 36.74 %, and 39.96 % lower, and the coefficient of determination is 0.04 % higher, respectively, when compared to the comparative model with the best evaluation indicator; in the IEEE 69–300 system, the corresponding values are 2.6 %, 12.83 %, 12.55 %, and 0.01 %, respectively.

Graphic processing unit accelerated time-domain harmonic balance method for multi-row turbomachinery flow simulation

Graphic processing unit accelerated time-domain harmonic balance method for multi-row turbomachinery flow simulation

A semi-empirical model for time-domain tower Vortex induced Vibration load simulations of wind turbines

A new method for simulating aeroelastic resonances between vortex shedding and structural eigenfrequencies of a wind turbine tower is presented in this publication. This aero-elastic effect of Vortex induced Vibrations (ViV) has the potential to disrupt installation processes and cause fatigue and extreme loads on the tower. Despite this issue, there are no established simulation methods available in literature, able and sufficiently efficient to predict the ViV in turbulent and site specific design load conditions. This state-of-the-art is extended by introducing an efficient semi-empirical, time-domain simulation method, which is capable of analyzing the tower ViV excitations and aeroelastic responses in wind turbine load simulations of the isolated tower or the full turbine for fatigue and extreme loads. The method is based on an adaptive harmonic equation, which is automatically tuned to the instantaneous tower motions.

Power System Transient Stability Preventive Control via Aptenodytes Forsteri Optimization with an Improved Transient Stability Assessment Model

Transient stability preventive control (TSPC), a method to efficiently withstand the severe contingencies in a power system, is mathematically a transient stability constrained optimal power flow (TSC-OPF) issue, attempting to maintain the economical and secure dispatch of a power system via generation rescheduling. The traditional TSC-OPF issue incorporated with differential-algebraic equations (DAE) is time consumption and difficult to solve. Therefore, this paper proposes a new TSPC method driven by a naturally inspired optimization algorithm integrated with transient stability assessment. To avoid solving complex DAE, the stacking ensemble multilayer perceptron (SEMLP) is used in this research as a transient stability assessment (TSA) model and integrated into the optimization algorithm to replace transient stability constraints. Therefore, less time is spent on challenging calculations. Simultaneously, sensitivity analysis (SA) based on this TSA model determines the adjustment direction of the controllable generators set. The results of this SA can be utilized as prior knowledge for subsequent optimization algorithms, thus further reducing the time consumption process. In addition, a naturally inspired algorithm, Aptenodytes Forsteri Optimization (AFO), is introduced to find the best operating point with a near-optimal operational cost while ensuring power system stability. The accuracy and effectiveness of the method are verified on the IEEE 39-bus system and the IEEE 300-bus system. After the implementation of the proposed TSPC method, both systems can ensure transient stability under a given contingency. The test experiment using AFO driven by SEMLP and SA on the IEEE 39-bus system is completed in about 35 s, which is one-tenth of the time required by the time domain simulation method.

A Structured Mesh Generation Based on Improved Ray-Tracing Method for Finite Difference Time Domain Simulation

A structured mesh generation method based on an improved ray-tracing technique is proposed for finite time difference domain (FDTD) simulation in this paper. This method converts the triangular faces provided by the STL file into the structured mesh required by the FDTD method. The size of the generated structured mesh is determined by the size of the triangular element, so it is non-uniform and can adapt to the shape of the target. In addition, this method proposes an improved ray-tracing technique to avoid the singularities of the object, so it has much better accuracy than the conventional method. Two representative electromagnetic objects, an Su-30 aircraft and a complex bow-tie antenna, representing a typical electrically large model and fine structure, respectively, are used to validate the accuracy of the mesh generation method. The results show that the presented method has high accuracy, regardless of whether it is used for large targets or fine structures such as a small hole, strip, thin layer, etc.

A Multi-Rate Simulation Strategy Based on the Modified Time-Domain Simulation Method and Multi-Area Data Exchange Method of Power Systems

Accurate modeling for power-electronic devices requires power systems to be simulated with considerably small step sizes (typically several microseconds), which causes unnecessary computational burden and reduces efficiency, especially for large-scale power systems. To achieve a balance between simulation precision and efficiency, this paper introduces an innovative multi-rate interface strategy based on the modified time-domain simulation (TDS) method and multi-area data exchange method. The modified TDS method transforms the initialization process into exchange of electric data among different subsystems, while the multi-area data exchange method is able to ensure numerical stability and simulation universality during the multi-rate simulation. The proposed strategy provides a robust interface that allows different subsystems to be engaged in simulations with different step sizes while exchanging data. To validate this strategy, simulations on an integrated system of IEEE 14-bus and 33-bus systems is conducted. In addition, the strategy is further applied to a real-world scenario of the subsystem in the Guangxi Power Grid in China. Analysis of the results indicates that the proposed multi-rate fast simulation strategy can significantly boost simulation efficiency while maintaining accuracy, which marks a notable improvement compared with the traditional single step size simulation.

Construction of smartphone-adapted signal visualization platform for dual-mode detection of H2S based on integrated metal-organic framework nanoprobes

Hydrogen sulfide (H2S) is a toxic contaminant and has great influence on many physiological processes. Due to various pathophysiological roles and environmental pollution problems, it is necessary to construct and develop simple and portable monitoring sensors for the precise detection of H2S. Herein, we developed a smartphone-adapted dual-mode detection platform by integrating the colorimetric and photothermal imaging analysis into a metal-organic framework-based chip (ZIF-8/Cu). Due to the nanoconfinement effect of ZIF-8, small-sized plasmonic CuS could be in-situ formed during the detection procedure of H2S and endowed the chips with excellent photothermal properties. By constructing a smartphone-adapted photothermal imager, the metal-organic framework-based chip could achieve a portable photothermal imaging analysis of H2S. Moreover, as the formed CuS was a good peroxidase-like nanozyme, the chips could also be used to trigger the enzymic catalytic reaction toward the chromogenic reaction of 3,3′,5,5′-tetramethylbenzidine (TMB)-H2O2, thus providing another colorimetric sensing mode by using a smartphone App. In this smartphone-adapted visualization platform, the portable chemosensors could simultaneously achieve double detection modes at one electrode, which provided a new pathway for the accurate detection of H2S and circumvented the false-positive or negative errors during the detection process. Besides, by using the finite difference time domain (FDTD) simulation method, the in-depth mechanism, including the plasmonic effect and spatial electromagnetic field distribution, was explored to provide a possible reason for the excellent sensing performance of the dual-mode visualization platform. This work provides a new insight into the construction of the accurate, portable and smart sensing platform in the visual screening of H2S.

Grating assisted temperature insensitive micro-ring resonator biosensor

A grating-assisted temperature-insensitive micro-ring resonator bio-sensor is reported using the finite-difference time-domain simulation method. In addition to choosing a negative thermo-optic coefficient (TOC) material, water, to nullify temperature-induced wavelength shift, optimization of the opto-geometric parameters provided a precisely zero-temperature sensitivity (TS) state of the structure. The negative TOC of water counterbalances the positive shift in resonance wavelength originating from Si waveguides. The grating structure delocalizes the core field into the analyte region, which enhances field–matter interaction to offer high bulk refractive index (RI) and affinity sensing. The advantage of incorporating grating structure in the ring has been demonstrated by comparing the bulk RI sensitivity and affinity sensitivity with and without the grating structure. Without the circular grating array, the bulk RI sensitivity is 214 nm RIU−1, and the affinity sensitivity is 0.139 nm nm−1. Using grating in the ring structure offers an improved bulk RI sensitivity of 525 nm RIU−1 and an adlayer sensitivity of 0.515 nm nm−1. We calculated the system limit of detection of the structure as ∼2 RIU. The fabrication tolerance of geometrical parameters, in the form of 10% variation in hole radius and 5% variation in other widths of our sensor, reveals a nominal TS of ∼6 pm ∘C−1. Changing the cladding analyte from pure water to other aqueous solutions, e.g. urine samples, also has a small impact on TS. The present work is useful in RI-dependent monitoring of the constituents present in aqueous medium-based bio-analytes samples in a variable ambient temperature environment.

A new pre-conditioned STDP rule and its hardware implementation in neuromorphic crossbar array

This paper proposes a new pre-conditioned spike-timing-dependent plasticity (STDP) learning rule as well as an efficient system-level time-domain circuit modeling and simulation method for the whole crossbar array structure. First, the new pre-conditioned STDP rule is conceived by exercising a slight perturbation to the conventional STDP curve. Software-wise, it can be described in spiking neural network (SNN) codes, while hardware-wise, it is realized by the memristor crossbar array in conjunction with specific spike signals, just as the conventional STDP. The new STDP rule enables the neural network in a neuromorphic chip to achieve better performance both in terms of software and hardware implementation compared with the conventional STDP rule. Second, a time-domain circuit modeling method is proposed for the simulation of the whole crossbar array. Numerical experiments demonstrate that the new pre-conditioned STDP is superior to the conventional STDP both in terms of accuracy and low power consumption. At the software level, a 784 × 100 spiking neural network, trained by the pre-conditioned STDP, for the MNIST handwritten digit recognition achieves an accuracy of 85.90%, which is 3.09% higher than that trained by the conventional STDP. At the hardware level, a downscaled 196 × 10 crossbar array is simulated and trained. The crossbar array trained by the new STDP consumes 21.5% less power than that trained by the conventional STDP. Moreover, it does not compromise the original robustness when subject to non-ideal characteristics such as variation of conductance and resistance of the interconnect in the crossbar array.

A critical analysis of classical severity-based knock control strategies

A common variant of classical knock control strategies replaces fixed magnitude control moves with control actions that depend on the knock severity of the prior cycle. Though appealing to notions of proportional control, it is unclear whether such strategies offer benefit given the random nature of knock events. In this paper a new generalized event-based framework is developed and used to extend both time domain simulation and stochastic analysis methods for analyzing the closed loop behavior of such systems. These tools are then used to perform a rigorous analysis and comparison between standard advance-retard and severity-based control strategies. The analysis is also repeated using a lower knock threshold definition. The results show that the performance of severity-based knock control differs minimally from a similarly tuned standard advance-retard controller, and there is little benefit to recompense the additional complexity of severity-based control.

Efficient multi-scale staggered coupling of discrete and boundary element methods for dynamic problems

This paper presents a novel and highly efficient approach for coupling the Discrete Element Method (DEM) and the Boundary Element Method (BEM) for time-domain simulations of dynamic problems, utilising multi-scale staggered time integration. While the DEM captures phenomena with discontinuous behaviours, such as fracturing and granular flow, the BEM excels in accurately modelling seismic wave propagation in infinite domains. By separately solving the governing equations of the DEM and BEM at different time instants, the proposed scheme considerably enhances computational efficiency compared to conventional monolithic coupling schemes. The incorporation of non-conforming interfaces enables larger time steps in the BEM, thereby reducing computational costs and memory usage. Moreover, an innovative coupling of DEM rotations with the BEM displacement field is introduced, leading to more accurate and realistic modelling of complex dynamics. Numerical experiments are conducted to demonstrate the superior accuracy and efficiency of the proposed method, establishing its potential for modelling a wide range of dynamic problems.

Fast Response Prediction Method Based on Bidirectional Long Short-Term Memory for High-Speed Links

There is a recognized need to evaluate the performance of high-speed links accurately and quickly with increasing clock frequency. To evaluate the performance of the systems, the transient simulation method and the fast time-domain simulation method are adopted. Unfortunately, neither method can guarantee both the efficiency and accuracy of the results at the same time. In this article, a modeling method that can overcome the shortcomings of both the transient simulation method and the fast time-domain simulation method is proposed for obtaining responses of high-speed links based on bidirectional long short-term memory (Bi-LSTM). Here, the pulse response and response of a certain number of bits are first simulated or measured, which are used to determine training datasets. Then, the Bi-LSTM-based model uses the generated training datasets to build a precise model. Next, the developed model predicts the response of the high-speed link. Compared to the transient simulation method and fast time-domain simulation method, the results show that the proposed method can consider both accuracy and efficiency. In addition, 33 simulation experiments are performed to demonstrate the robustness of the proposed method. Finally, the accuracy of the proposed method is validated by comparing the measured and predicted results of the high-speed links with different nonlinearities.

All-optical control of ultrafast plasmon resonances in the pulse-driven extraordinary optical transmission

Understanding ultrafast processes in their natural timescale is crucial for controlling and manipulating nanoscale optoelectronic devices under light–matter interaction. Here, we demonstrate that ultrafast plasmon resonances, attributed to the phenomenon of extraordinary optical transmission (EOT), can be significantly modified by tuning the spectral and temporal properties of the ultrashort light pulse. In this scheme, all-optical active tuning governs the spatial and temporal enhancement of plasmon oscillations in the EOT system without device customization. We analyze the spectral and temporal evolution of the system using two approaches. First, we develop a theoretical framework based on the coupled harmonic oscillator model, which analytically describes the dynamics of plasmon modes in the coupled and uncoupled states. Later, we compare the evolution of the system under continuous-wave and pulsed illumination. Further, we discuss the time-resolved spectral and spatial dynamics of plasmon modes using a 3D finite difference time-domain simulation method and wavelet transform. Our results show that optical tuning of the oscillation time, intensity, and spectral properties of propagating and localized plasmon modes yields a three-fold enhancement in the EOT signal. The active tuning of the EOT sensor through ultrashort light pulses paves the way for the development of on-chip photonic devices employing high-resolution imaging and sensing of abundant atomic and molecular systems.

Raw Data Simulation of Spaceborne Synthetic Aperture Radar with Accurate Range Model

Simulated raw data have become an essential tool for testing and assessing system parameters and imaging performance due to the high cost and limited availability of real raw data from spaceborne synthetic aperture radar (SAR). However, with increasing resolution and higher orbit altitudes, existing simulation methods fail to generate SAR simulated raw data that closely resemble real raw data. This is due to approximations such as curved orbits, “stop-and-go” assumption, and Earth’s rotation, among other factors. To overcome these challenges, this paper presents an accurate range model with a “nonstop-and-go” configuration for raw data simulation based on existing time-domain simulation methods. We model the SAR echo signal and establish a precise space geometry for spaceborne SAR. Additionally, we precisely identify the target illumination area based on elliptical beams through space coordinate transformation. Finally, the SAR raw data were accurately simulated using high-precision time-domain simulation methods. The accuracy of the proposed model was validated by comparing it with the traditional hyperbolic model and the curved orbit model with “stop-and-go” assumption through image processing of the generated raw data. Through the analysis of point target quality parameters, the errors of various parameters in our distance model compared with the other two models are within 1%. Furthermore, this simulation method can be adapted to simulate raw data of other modes and satellite orbits by adjusting beam control and satellite orbit parameters, respectively. The proposed simulation method demonstrated high accuracy and versatility, thereby providing a valuable contribution to the development of remote sensing technology.

A Simplified Model of the HVDC Transmission System for Sub-Synchronous Oscillations

As the installed capacity of the power system is scaled up and the distance of transmission increases constantly, high-voltage direct current (HVDC) transmission technology has been widely applied across the power system. The HVDC system can lead to sub-synchronous oscillations (SSO) in the turbine and new energy generation systems. When the SSO caused by HVDC are studied through small signal analysis, it is usually necessary to establish the detailed state space model and electromagnetic transient model, which shows various disadvantages such as the high complexity of the model, the high order of the state space matrix, the complex calculation of eigenvalues, and the slow pace of simulation. In the present study, a simplified model intended for the HVDC transmission system is proposed, which can be used to simplify the calculation model and accelerate the simulation by omitting the high-frequency component and simultaneously keeping the sub-synchronous frequency component unchanged. The time domain simulation method is used to compare the dynamic response of the proposed simplified simulation model with that of the original detailed model, and the accuracy of the proposed model is demonstrated. The proposed simplified simulation model is applied to explore the SSO of wind-thermal power bundling in the HVDC transmission system. Additionally, the simulation results of SSO are compared by using the simplified model and the detailed model; the results of which demonstrate the effectiveness and rapidity of the simplified simulation model. The simplified model proposed can greatly improve the efficiency of SSO risk assessment. By selecting reasonable types and parameters of new energy units, SSO of the system can be avoided under risky operation mode, and the power grid operation mode can be monitored and adjusted to ensure the safe operation of the system. Finally, it can promote the sustainable development of the power system.

Global maximum flow based time-domain simulation method for evaluating power system resilience

With climate change, extreme weather is occurring frequently, which can cause serious damage to energy supply systems. It is of great significance to study the performance of power transmission system under extreme weather for prevention and reinforcement before and after disasters. This paper proposes a time-domain simulation model for quantifying power system resilience under extreme typhoon scenario. Firstly, the power system resilience assessment method based on global maximum flow (GMF) is presented, which is applied to map the overall system operation performance via creating a network indicator while considering component fragility, system topology, and power flow. A specific resilience expression (RES) is proposed to describe percentage improvement of each component in the resilience metrics by considering the overall system performance. Secondly, power system vulnerability model and time-domain simulation methodology are established. The proposed method is demonstrated by four case studies using the IEEE-30 node test system under specific typhoon scenarios. From the GMF based RES index, the component repair strategy is formulated accordingly. The proposed restoration strategy, compared with the traditional expert strategy can effectively measure the resilience contribution of each component to the whole power system, and minimizes the power system performance losses due to extreme typhoon. The proposed approach quantitatively evaluates real-time system resilience to extreme typhoons, and it can also identify the system critical areas and assess the benefits of different resilience enhancement strategies. The resilience assessment framework can also be applied to other extreme scenarios and contribute to planning and construction of strong smart grid in the future.

A transient stability analysis method for wind power system with thyristor controlled phase shifting transformer based on branch potential energy index

With the growing usage of renewable energy technologies like wind power and photovoltaics, and the increased integration of FACTS (Flexible Alternating Current Transmission System) devices into the power system, the transient characteristics of the evolving power system undergo changes that require appropriate analysis methods. As a new type of FACTS device, TCPST (Thyristor Controlled Phase Shifting Transformer) is introduced to facilitate the superior operation of renewable energy sources by controlling the power flow of access branches. From the perspective of branches, the dynamic characteristics of renewable energy sources and TCPST might be uniformly studied and simply calculated in the transient stability analysis. Therefore, the paper proposes a transient stability analysis method for wind power systems with TCPST based on the branch potential energy index. First, considering the variation characteristics of branch potential energy, this paper employed the stability index to analyze the transient stability of branches and the system by finding vulnerable lines. Then, based on the stability index, the paper investigates the influence of wind turbine removal, the installation and control parameter adjustment of TCPST on the transient stability of wind power systems. The simulation results in PSAT demonstrate that the removal of a proper amount of wind turbine post-fault and the installation of TCPST can improve the transient stability of the wind power system. Furthermore, it can also be improved by reasonably adjusting the TCPST control parameters. All simulation results are verified by the time domain simulation method.

Time-domain simulation of acoustic wave scattering and internal propagation from a gas bubble of various shapes.

Acoustic scattering and resonances of gas bubbles are computed using a time-domain simulation based on numerical solutions of the conservation laws. The time histories of scattered pressure and fluid velocity, outside and inside the bubble, are obtained simultaneously from an immersed-boundary method allowing for the investigation of exterior and interior fields for non-spherical geometries. The acoustic resonances of the bubble are investigated for various bubble sizes, shapes, and inner gas parameters and compared in limiting cases to the partial wave scattering solutions for spherical bubbles. The dynamics of the gas motion and its associated contribution to resonance response has received little attention in previous analytical and numerical formulations. In this study, the acoustic propagation and motion inside the interior gas is investigated with respect to the monopole resonance with the combined time-domain simulation and immersed-boundary method. For the non-spherical prolate and oblate shapes, the scattering and resonance behaviors are compared with the approximate analytical results based on the shape factor method. The simulation method can be extended to less-understood shapes relevant to underwater and physical acoustics, such as "pancake-shaped" or "cigar-shaped" bubbles, as well as to spatial and time-dependent forcing.

Wave resonances in the presence of current and the frequency and time-domain interconnection

The current work investigates the relationship between frequency and time domain problems associated with flexural gravity wave motion with oblique incidence and current. Different types of wave resonances such as buckling resonance, primary and secondary blocking resonance, Bragg resonance and interaction among them are discussed. Three propagating wave modes are observed between the primary and secondary blocking points, two of which are associated with positive group velocities and the third one is related to negative group velocities. Again, the Bragg resonance is analyzed for wave scattering problems. The complex porosity parameter is found to have a significant effect on the buckling and blocking resonance but does not affect Bragg resonance. The discontinuity of Bragg reflection is observed at primary and secondary blocking points and the peak values of Bragg reflection increase in the blocking zone. Again, we establish the interconnection between the frequency and time domain by deriving the time-domain solution from the frequency-domain solution and vice versa. The derivation of time-domain solutions using the dispersion relation and method of stationary phase is an intriguing finding. Wave energy and wave packets move faster in co-propagating waves than in counter-propagating waves and shallow water than in finite water depth. To validate the results, time-domain simulation and spectral methods are used.

Critical clearing time estimation of multi-machine power system transient stability using fuzzy logic

<span lang="EN-US">Studying network stability requires determining the best critical clearing time (CCT) for the network after the fault has occurred. CCT is an essential issue for transient stability assessment (TSA) in the operation, security, and maintenance of an electrical power system. This paper proposes an algorithm to obtain CCT based on fuzzy logic (FL) under fault conditions, for a multi-machine power system. CCT was estimated using a two-step fuzzy logic algorithm: the first step is to calculate Δt, which represents the output of the FL, while maximum angle deviation (δmax) represents the input. The second step is to classify the system if it is a stable or unstable system, based on two inputs for FL, the first mechanical input power (Pm), the second average accelerations (Aav). The results of the proposed method were compared with the time domain simulation (TDS) method. The results showed the accuracy and speed of the estimation using the FL method, with an error rate not exceeding 5%, and reduced the performance time by about half the time. The proposed approach is tested on both IEEE-9 bus and IEEE-39 bus systems using simulation in MATLAB.</span>