Inverted Model Research Articles

Synchronization Stability Analysis Based on Dual-Sequence Dynamic Coupling Model for Grid-Following Inverters Under Asymmetrical Grid Faults

Synchronization Stability Analysis Based on Dual-Sequence Dynamic Coupling Model for Grid-Following Inverters Under Asymmetrical Grid Faults

Novel Regulators and Their Epistatic Networks in Arabidopsis' Defence Responses to Alternaria alternata Infection.

Necrotrophic pathogens cause serious threats to agricultural crops, and understanding the resistance genes and their genetic networks is key to breeding new plant cultivars with better resistance traits. Although Alternaria alternata causes black spot in important leafy brassica vegetables, and leads to significant loss of yield and food quality, little is known about plant-A. alternata interactions. In this study, we used a unique and large collection of single, double and triple mutant lines of defence metabolite regulators in Arabidopsis to explore how these transcription factors and their epistatic networks may influence A. alternata infections. This identified nine novel regulators and 20 pairs of epistatic interactions that modulate Arabidopsis plants' defence responses to A. alternata infection. We further showed that the glucosinolate 4-methoxy-indol-3-ylmethyl is the only glucosinolate consistently responsive to A. alternata infection in Col-0 ecotype. With the further exploration of the regulators and the genetic networks on modulating the accumulation of glucosinolates under A. alternata infection, an inverted triangle regulatory model was proposed for Arabidopsis plants' defence responses at a metabolic level and a phenotypic level.

A Litz Wire-Based Inductor Model for a DC-DC Converter-Fed Single-Phase Inverter

Inductors play a major role in the power electronics domain, particularly in DC-DC converter design. The objective of this paper is to reach inductance value by means of fewer turns, using Litz wire wound on a ferrite core. In the manufacture of inductors, the key aspects of the design criteria include the choice of the core material, the type of copper coil and insulation materials, and their overall size. Taking into consideration the design parameters with no compromises on performance, Litz wire with the least turns is introduced into an inductor in certain DC-DC converters. Once the DC settled voltage is reached, it is given to a single-phase inverter for loading and application measures. This approach provides a small-level inductor design for maximized efficiency with improved thermal behavior. The hardware model for the proposed method has been developed using a DC-DC converter fed with a single-phase inverter model. The proposed DC-DC converter has been tested, performance-wise, by applying different load levels. It is observed, from the results, that the Litz wire-based approach achieves maximum efficiency with improved thermal behavior.

Likelihood Inference for Possibly Non-Stationary Processes via Adaptive Overdifferencing

We make an observation that facilitates exact likelihood-based inference for the parameters of the popular ARFIMA model without requiring stationarity by allowing the upper bound d ¯ for the memory parameter d to exceed 0.5: estimating the parameters of a single non-stationary ARFIMA model is equivalent to estimating the parameters of a sequence of stationary ARFIMA models. This allows for the use of existing methods for evaluating the likelihood for an invertible and stationary ARFIMA model. This enables improved inference because many standard methods perform poorly when estimates are close to the boundary of the parameter space. It also allows us to leverage the wealth of likelihood approximations that have been introduced for estimating the parameters of a stationary process. We explore how estimation of the memory parameter d depends on the upper bound d ¯ and introduce adaptive procedures for choosing d ¯ . We show via simulation how our adaptive procedures estimate the memory parameter well, relative to existing alternatives, when the true value is as large as 2.5.

Topology Construction, Modeling, and Control of Multi-level Inverters without shoot-through problem

Topology Construction, Modeling, and Control of Multi-level Inverters without shoot-through problem

Comprehensive Modeling and Simulation of Longitudinal Dynamics in Electric Vehicles with In-Wheel BLDC Motors: Integration of Chassis, Motor, Inverter, and Tire-Pacejka Model

Comprehensive Modeling and Simulation of Longitudinal Dynamics in Electric Vehicles with In-Wheel BLDC Motors: Integration of Chassis, Motor, Inverter, and Tire-Pacejka Model

Research on Fault Prediction and Health Management of Grid-Connected Inverter based on Data Drive

Grid-connected inverter is the core component of photovoltaic power generation system, and its stable operation is very important to the overall performance of the system. However, the inverter is easily influenced by environmental factors and its own complexity, which leads to frequent failures and affects power generation efficiency and power grid stability. Firstly, an innovative fault prediction model of grid-connected inverter is constructed by using machine learning and deep learning technology. The prediction accuracy and robustness of the model are improved by integrating the prediction results of basic learners such as decision tree and support vector machine (SVM). The experimental results show that the integrated learning model achieves an accuracy of 0.95 and a F1 score of 0.94 under the optimal parameter configuration. At the same time, the Long Short Term Memory Network (LSTM) model is introduced to effectively capture the complex nonlinear relationship and time dependence in the data, which further improves the prediction performance, and the highest accuracy rate can reach 0.96. Based on the fault prediction model, a comprehensive health management strategy of grid-connected inverter is formulated in this paper. The strategy framework includes four links: data collection and monitoring, fault prediction and evaluation, preventive maintenance plan formulation, fault early warning and response. By monitoring the key parameters of the inverter in real time and comparing with the fault prediction model, the early warning and timely response of the fault can be realized. The experimental results show that after the implementation of health management strategy, the failure rate of inverter is significantly reduced, the response time of fault warning is significantly shortened, and the operation reliability is significantly improved.

Signatures and Mechanism Analysis of Converter-Grid Subsynchronous Oscillations

In the last decade, a rather new phenomenon related to subsynchronous oscillations (SSO) in a wide frequency range has emerged in modern power grids with power converters. The consequences of these oscillations can be severe system accidents, which have already occurred in various power systems. Taking into account the importance of studying such oscillations for effective mitigation and the existing gaps in understanding the mechanisms of SSO occurrence due to different combinations of used controllers in the inverter control system, as well as the grid parameters, a frequency analysis of simplified grid inverter models is performed. As a result, five different mechanisms of SSO occurrence, the affecting factors and the level of inverter model detail required for the adequate study of SSO are justified. The developed detailed state–space model allowed for verifying the obtained results, as well as identifying an additional sixth mechanism of SSO occurrence. The common condition for the occurrence of all the identified SSO mechanisms is a weak grid with a short-circuit ratio of less than two. The results of control hardware-in-the-loop testing confirmed the conclusions drawn. As a result, a classification of SSO occurrence mechanisms was formed, reflecting their causes and distinctive features.

A simple method for common-mode voltage optimization in three-level three-phase four-leg inverters

Abstract In response to the problem of large common-mode (CM) voltage magnitude and high-frequency variation under traditional modulation strategies for three-level three-phase four-leg (3L3P4L) inverters, this paper proposes a modulation strategy based on carrier combination and modulation wave splitting. Firstly, this paper establishes a CM model for the 3L3P4L inverter and derives mathematical expressions of the system’s CM voltage in terms of switch states and system parameters. Building upon this foundation, this paper explains the reasons for high-frequency variations in CM voltage under traditional schemes and provides a detailed introduction to the optimization process and principles of the proposed strategy. Finally, a simulation model is developed by using Matlab/Simulink software. Through comparison with traditional approaches, the effectiveness of the proposed strategy is validated.

Digital Twin Modeling and Multiparameter Monitoring Schemes of Three-Level ANPC Inverters

Digital Twin Modeling and Multiparameter Monitoring Schemes of Three-Level ANPC Inverters

Overload mitigation for grid-forming inverters in islanded microgrids with synchronous generators

Overload mitigation for grid-forming inverters in islanded microgrids with synchronous generators

Three-Dimensional Subsurface Model of Luk-Ulo Melange Complex, Karangsambung, Indonesia: Insights from Gravity Modeling

The Luk-Ulo Melange Complex (LMC) is characterized by a chaotic assemblage of mixed rocks with a block-in-matrix fabric. The exposed blocks consist of various scattered rock types, trending in an ENE-WSW direction. In the case of Mt. Parang, the origin of the diabase remains uncertain, with ongoing debate as to whether it is associated with in situ volcanic activity or represents an exotic block within the melange deposit. Subsurface data obtained through geophysical investigation can aid in modeling the geometry of intrusive bodies using inverse modeling techniques. In this study, we conducted a gravity survey and performed 3D inverse modeling to investigate the subsurface beneath Karangsambung. A total of 818 gravity data points and 28 rock density measurements were integrated with existing geological data to construct an a priori 3D geological model. To ensure the results align with geological concepts, the 3D inversion utilized a stochastic approach, allowing for the incorporation of multiple geological constraints over fifty million iterative procedures. Ultimately, the inversion successfully reduced the misfit between observed and calculated data from 2.71 to 0.55 mGal. Based on the inverted 3D model, the diabase rock in Mt. Parang is identified as having an intrusive origin. The intrusion model exhibited minimal changes in density, volume, and shape during the inversion process. Additionally, the model suggests the presence of a solidified magma reservoir at a depth of approximately 3 km, potentially related to Dakah volcanism. The inverted model also reveals the block-in-matrix structure of the Luk-Ulo Melange Complex in the northern area.

Optimization of energy storage based on floating charge lithium iron phosphate battery

Abstract Lithium iron phosphate batteries are often used as power supplies, power batteries and energy storage batteries for electronic equipment, and their charge and discharge cycle characteristics have been studied extensively. However, when it is used as a new battery power source in a substation, the battery pack must be hung on the charger in a fully charged state for a long time and run for float charging. In this operating mode, the choice of the float billing voltage of the lithium iron phosphate battery, the size of the float charging existing, and features of unexpected discharge and battery life under lasting float charging still need to be studied. For that reason, a simulation model of the lithium battery power storage space system was developed, and the control criteria were adapted to make the particular curve constant with the examination information. Based on the real control logic of the energy storage inverter, a simulation model of the power storage inverter is built. With simulation screening and comparison with the actual outside characteristics of the inverter, the control parameters of the simulation model are continuously optimized to make them regular with the outside attributes of the actual inverter. The actual battery access point substation operating mode data is collected and sorted out, an appropriate equivalence on the battery system is performed, and an equivalence model in MATLAB/SIMULINK and PSCAD/EMTDC is built, which forms a complete simulation model together with the battery system model[1].

Inferential study on lifetime performance index with generalized inverted exponential model under progressive first-failure censoring

Lifetime performance assessment is widely used in quality control of the manufacturing industry. This paper focuses on the progressively first-failure-censored data coming from the generalized inverted exponential distribution. We present the maximum likelihood estimate and the Bayesian estimate for the lifetime performance index (CL) for a given lower specification level L. The results are used to develop non-Bayesian and Bayesian inferences to determine whether the product performance meets the required level. A Monte Carlo simulation and two real data examples are discussed for illustration purposes.

Analysis of active impedance characteristics and harmonic deterioration of multiple grid connected inverters considering nonlinear factors

AbstractThe harmonic problems caused by non‐linear factors of the grid connected inverter (GCI) system are more complicated, including both non‐characteristic harmonics emitted by the dead‐time and the changes in harmonic impedance characteristics. Harmonics interact with the changing impedance, and even cause harmonic amplification and resonance. The harmonic deterioration of the multiple GCIs system is serious. To analyse the mechanism and way of harmonic deterioration in grid‐connected system caused by nonlinear factors, the active impedance models of single inverter and multiple GCIs system including dead‐time effect and digital control delay are established first. In view of this, the influence mechanism of non‐linear factors on system stability is explored. The improved modal analysis method is used to traverse the network series parallel resonance caused by nonlinear factors. The results show that both the dead‐time effect and digital control delay reduce phase margin of the system, resulting in the resonant frequency shift and the resonant peak increase. When the harmonic excitation source interacts with the complex network under the influence of nonlinear factors, it will lead to further deterioration of harmonics. Finally, based on the MATLAB and RT‐LAB hardware‐in‐the‐loop simulation platforms, a multiple GCIs system model is built to verify the correctness of the established active impedance model and harmonic deterioration analysis.

Extracting metal oxide redox thermodynamics from TGA measurements requires moving beyond the linearized van ‘t Hoff approach

Thermodynamic modeling of metal oxide reduction is crucial for optimizing chemical processes and materials in systems dependent on off-stoichiometric reduction/re-oxidation cycling. Two prevalent methods for extracting reduction thermodynamics from thermogravimetric data are linearized van ‘t Hoff (VH) analysis and the compound energy formalism (CEF). This work evaluates the accuracy of these methods by constructing invertible ground truth thermodynamic models, generating hypothetical thermogravimetric data, and determining the reduction thermodynamic using both VH and CEF methods. Our findings reveal that the VH method produces absolute errors 3–5 times higher than the CEF in kJ/mol O or J/mol O K for enthalpy and entropy of reduction, respectively. In contrast, the CrossFit CEF (CF-CEF) method yields errors often less than 10 kJ/mol O or J/mol O K. Moreover, the CF-CEF method provides models based on mole fraction, temperature, and extent of reduction, while a typical VH analysis provides thermodynamics of only the specific compositions measured. Although simple to implement, the VH method suffers from significant, non-systematic errors due to entropy/enthalpy compensation and defect modeling. Consequently, we recommend the more complex but robust, CF-CEF method for extracting redox thermodynamics from thermogravimetric measurements.

Exploring the Nexus between Greenhouse Emissions, Environmental Degradation and Green Energy in Europe: A Critique of the Environmental Kuznets Curve

This study examines the intricate relationship between economic growth and European environmental degradation via the Environmental Kuznets Curve (EKC). Our results contest the traditional inverted U-shape model of the Environmental Kuznets Curve, indicating that the theory may not be consistently applicable across European countries. Utilizing CS-ARDL and MMQR modelling, we reveal substantial regional disparities. Western European nations demonstrate a typical Environmental Kuznets Curve (EKC) pattern in the short term, characterized by an initial increase in emissions alongside GDP development, followed by a subsequent fall. Conversely, Eastern and Balkan nations exhibit a U-shaped connection, described by an early decline in emissions followed by a subsequent increase as their development levels increase. The influence of renewable energy differs, as it decreases emissions in the short term in Western Europe. However, its long-term impacts are variable, especially when contrasted with its more pronounced effect on emissions in Eastern and Balkan countries. Furthermore, trade openness intensifies environmental degradation in the short-term across all regions, although its long-term impact diminishes, particularly concerning greenhouse gases (GHG). The relationship between renewable energy and trade openness is substantial for the short-term reduction of carbon dioxide emissions, but this effect declines with time. The results indicate that a uniform environmental policy throughout Europe may lack efficacy. Customized strategies to expedite the transition in Western Europe and more specific interventions in Eastern Europe are essential to harmonize economic progress with environmental sustainability. Future research should examine the determinants of the diminishing long-term effects of renewable energy and the interplay between trade and environmental policies.

2D Transdimensional Joint Inversion of Radio Magnetotelluric and Electrical Resistivity Tomography Data

Summary The joint inversion of radio magnetotelluric and electrical resistivity tomography data has the potential to reduce the uncertainties in the subsurface conductivity model. This is particularly beneficial when the datasets offer complementary information about the subsurface. However, the traditional gradient-based inversion methods pose challenges in quantifying uncertainty, as they yield a single model with limited appraisal of parameter uncertainty. The Bayesian inversion approach stands out for its capacity to provide quantitative assessments of uncertainty in the inverted model parameters. This is accomplished by generating an ensemble of models, leading to a posterior distribution that encapsulates both prior information concerning model parameters and the dataset information. We have implemented a transdimensional Markov chain Monte Carlo algorithm to perform the joint inversion of radio magnetotelluric and electrical resistivity tomography data. Through synthetic data studies, we illustrate how the inclusion of two complementary datasets can effectively reduce uncertainties in model parameters and how the model parameter uncertainties can be quantified. Subsequently, the developed algorithm is tested using exemplary field data from a waste site near Roorkee, India. Intensive prior geoelectric and transient electromagnetic as well as radio magnetotelluric studies investigated possible waste water seepage with a potential to contaminate the shallow aquifers. The derived subsurface structure from our transdimensional Bayesian results compare well with the deterministic results for the exemplary profile, but in addition provide comprehensive uncertainty estimates.

Modeling and Stability Analysis of the Three-Phase Grid-Connected Inverter Under DSOGI-PLL Considering Frequency-Adaptive Feedback

Modeling and Stability Analysis of the Three-Phase Grid-Connected Inverter Under DSOGI-PLL Considering Frequency-Adaptive Feedback

Locomotion Control of a Bipedal Wheeled Robot Using Virtual Model Control and Linear Quadratic Regulator Techniques

This paper aims to develop a balance control technique and investigates its impact on the stability and disturbance rejection capability of a bipedal wheeled robot. The bipedal wheeled robot is equivalent to a wheeled inverted pendulum nonlinear model with a legs-airframe centroid variable rod. The nonlinear model is linearized and decoupled into two subsystems: straight-line control using linear-quadratic regulator (LQR) for balance and speed, and steering control employing proportional integral derivative (PID). Height control adjusts the virtual force with PID-Feedforward, while hip torque is determined by virtual model control (VMC). MATLAB simulation confirms effective control of height, linear motion, and steering, with decoupling enhancing steering performance.