Model Of Power Converter Research Articles

Active and reactive power control in transmission line with PSO optimized PI controlled five level UPFC

In this paper, particle swarm optimization (PSO) optimized PI controlled five level UPFC is proposed for a double circuit transmission line. To enhance UPFC performance, a different approach is considered here. It uses simplified power system models to derive the decoupled power controllers, but detailed modeling of the UPFC power converters improves their ride-through capability. This paper introduces decoupled linear UPFC power controllers to obtain the reference ac voltages and currents for the two back-to-back-connected three-phase five-level NPC converters that enforce active and reactive power control in the transmission line. This paper proposes three main contributions to increase the dc-link voltage steadiness of multilevel UPFCs under line faults: 1) decoupled active and reactive linear power controllers; 2) real-time PWM generation; and 3) balancing of dc capacitor voltages. The MATLAB/SIMULINK model for the proposed circuit with PSO-optimized PI controlled five level UPFC is shown here with the results.

Predictive model of cooling system for railway electric propulsion: validation of design choices and last mile analysis

For many years the most advanced railway propulsion systems have been based on the use of electric motors. Compared to the other available solutions, these are characterized by greater operating economy and less environmental pollution. In order to operate as efficiently as possible and to guarantee the high standards of electromechanical reliability, these propulsion technologies need adequate cooling systems to operate in controlled temperature conditions. Considering this, the implementation of increasingly accurate and performing simulation models can represent a significant advantage and provide great support in the optimization phase of cooling systems, in terms of reduction of dimensions and weight, rapid and low-cost experimentation, prediction of critical scenarios and choice of the best solution strategies to be taken. In this regard, in the context of the collaboration between the University of Naples Federico II, University of Sannio and the company Hitachi Rail STS S.p.A., several lumped parameter models of power converter cooling systems for railway electric propulsion were developed in the Simcenter AMESim environment. These models allowed to validate specific design choices from thermal and hydraulic perspectives, aimed at higher energy efficiency of the system, and to perform the so-called Last Mile predictive analysis, in order to evaluate the possibility of removing a vehicle from the railway line as consequence of a fault of specific components.

Black-box Modeling of Converters in Renewable Energy Systems for EMC Assessment: Overview and Discussion of Available Models

The development of renewable energy systems interfaced with the grid by power electronic converters leads to increasing issues of electromagnetic coexistence between power and communication lines, as well as severe power quality issues, such as total harmonic distortion at the consumer side. Therefore, high-frequency modeling of renewable energy systems is of great importance to guide the design and development of distribution networks involving renewable sources. Owing to system complexity, black-box modeling approaches offer more advantages than traditional circuit modeling, as far as electromagnetic compatibility (EMC) analysis and filter design are the targets. In this study, different black-box modeling techniques for power converters are introduced and systematically analyzed. First, the general theory of black-box modeling is explained. Subsequently, three different modeling approaches are compared in terms of accuracy and the required experimental setup. Finally, the possible limitations of black-box modeling of power converters are investigated and discussed.

Modeling, Analysis, and Reduction of Radiated EMI Due to the Voltage Across Input and Output Cables in an Automotive Non-Isolated Power Converter

This article investigates the radiated electromagnetic interference (EMI) due to the voltage between input and output cables in a non-isolated power converter. The radiated EMI model of a non-isolated power converter is first developed and quantified based on the circuit topologies, printed circuit board (PCB) parasitics, switching waveforms, and transfer functions. Second, an antenna model is developed for converter cables based on the antenna impedance and the antenna transfer function. Third, a complete radiated EMI model is developed based on the converter's EMI model and the cable's antenna model. Fourth, the radiated EMI is analyzed based on the developed model. Finally, two radiated EMI noise reduction techniques, optimizing PCB layout and adding a cross capacitor, are proposed. The developed radiated EMI model and the proposed radiated EMI reduction techniques are verified with both simulations and experiments. The techniques are also extended to other two non-isolated power converter topologies when the radiated EMI is caused by the voltage between the input and output cables.

Deep Neural Network-Based Surrogate Model for Optimal Component Sizing of Power Converters Using Deep Reinforcement Learning

The optimal design of power converters often requires a huge number of simulations and numeric analyses to determine the optimal parameters. This process is time-consuming and results in a high computational cost. Therefore, this paper proposes a deep reinforcement learning (DRL)-based optimization algorithm to optimize the design parameters for power converters using a deep neural network (DNN)-based surrogate model. The surrogate model of power converters can quickly estimate the power efficiency from input parameters without requiring any simulation. The proposed optimization model includes two major steps. In the first step, the surrogate model is trained offline using a large dataset. In the second step, a soft actor-critic-based optimization model interacts with the surrogate model from step 1 to determine the optimal values of design parameters in power converters. Unlike deep Q learning-based methods, the proposed method is able to handle large state and action spaces. In addition, using entropy-regularized reinforcement learning, our proposed method can accelerate and stabilize the learning process and also prevent trapping in local optima. Finally, to show the effectiveness of the proposed method, the performance of different optimization algorithms is compared, considering over ten power converter topologies.

Hybrid Dynamic Phasor Modeling Approaches for Accurate Closed-Loop Simulation of Power Converters

Modelling the fast dynamics of power converters is of growing concern in power grids and Microgrids. Dynamic phasor (DP) concept has been widely applied to switched power converter for modelling fast transients efficiently due to the inherent frequency shift property of DPs. The dynamics introduced by the DC/AC power converters depend on the controllers, which are implemented either in the stationary frame or on the synchronous reference frame (SRF). Hybrid closed-loop modelling methods that consider DP-based power converter plant model are not established and the applicability and accuracy of such hybrid approaches are not fully understood. This paper attempts to address this gap by proposing two hybrid closed-loop modelling approaches: Hybrid DP-DQ and Hybrid DP-EMT and discusses the applicability and accuracy for various controller types. Furthermore, this paper presents a DP switched model of single and three phase two level power converter and discusses the selection of harmonics to reduce model complexity. The proposed hybrid approaches were validated against detailed switched power converter models and for a wide range of scenarios, the Hybrid DP-EMT method is found to be superior compared other methods. Finally, application dependent recommendations are made for the selection of suitable hybrid closed-loop model for the accurate simulation of single phase and three phase power converters.

A Mode-Based Averaged Power Converter Model for Large Transients

Power converters employ high-frequency switching between multiple switch states, each of which causes the system to exhibit a different dynamic behavior. Averaged models are a common simplification used for describing the behavior in one or two specific cycles of switch states, also called operating modes. In this context, we propose extending the method of Sun et al. (2001), which allows averaging in two operating modes, to a converter model with four operating modes. We show in simulations that our model results in a reasonable approximation of the true moving average of the original switching converter model during large transients that pass through multiple operating modes.

A New Approach to Steady-State Modeling, Analysis, and Design of Power Converters

Steady-state models of power converters that provide accurate closed-form expressions for converter waveforms are extremely valuable for converter analysis and design, and enable comparative evaluation of different converter topologies. An obstacle in the development of such models is the inherent nonlinearity of switching power converters. This article presents a systematic procedure to model a broad class of power converters using ordinary differential equations (ODEs) with periodic and discontinuous inputs, and provides an approach to determine closed-form expressions for their steady-state waveforms. The formal mathematical proof of the proposed approach to finding closed-form expressions for the steady-state solution of ODEs with periodic and discontinuous inputs, Laplace-based theorem (LBT), is also presented. The presented modeling procedure and LBT, collectively called Laplace-based steady-state modeling (LBSM), serves as an effective analysis and design tool for power converters. The value of LBSM is demonstrated by using it to obtain closed-form expressions for the steady-state waveforms of different types of converters. In particular, two commonly used topologies—the series resonant converter and the phase-shift converter—are analyzed and compared using LBSM and their optimum operating conditions and applications are discussed. The converter waveforms, soft switching ranges and other characteristics obtained using LBSM are also validated through simulations and experiments.

Adequacy Evaluation of an Islanded Microgrid

The reliability of power converters has been extensively examined in terms of component- and converter level. However, in case of multiple generation units, the evaluation of the performance of power systems requires system-level modeling. This paper aims to merge the prior art of reliability modeling of power converters with the adequacy evaluation of power systems through an extensive design and evaluation analysis of a microgrid based case study. The methodology proposed in the paper integrates the device-level analysis into the domain of the conventional power system reliability analysis while outlining the steps needed to deal with non-exponential distributed failures of power electronic-based generation units. A replacement policy of the power electronic-based units is adopted by means of evaluating the system risk of not supplying system loads, and, finally, an approach on how to ensure a desired replacement frequency is outlined.

Estimation of State Variables in the Ćuk Converter Mathematical Model with Partially Unknown Parameters

In this paper the solution was proposed for the state variables estimation problem in the mathematical model of the DC switch-mode power converter built according to the Ćuk scheme. Pulse converters are one of the main components of most modern electrical devices and the circuit proposed by Slobodan Ćuk in the 70s of the 20th century is still relevant and demanded. Traditionally, PI (proportional-integral) controllers or proportional-integral adaptive control algorithm (PI-PBC), based on passification methods and superior to standard PI controllers in accuracy, are used as the control algorithm for power converters. However, you need to know the entire vector of the state variables of the converter to build a PI-PBC controller, and moreover, all its parameters must be accurately known. Unfortunately, in practice, such assumptions are not fulfilled, since parametric drifting is possible, and measurements of the converter’s state require additional sensors, which in some cases does not justify itself. Thus, there is a need to develop additional observers or estimators that allow obtaining data on all variables of the converter, as well as its parameters. The solution is based on the GPEBO method (generalized parameter estimation-based observers). The problem was solved under assumption that only the output signal (the output voltage of the converter) is measurable and some of the mathematical model parameters are unknown. An important aspect of the observer design is the development of an algorithm for unknown parameters and the state vector of a mathematical model estimation that ensures convergence in a finite time. Finite-time convergence is extremely important when designing observers since transients in pulse converters occur very quickly.

Evaluation of the Different Numerical Formats for HIL Models of Power Converters after the Adoption of VHDL-2008 by Xilinx

Hardware in the loop is a widely used technique in power electronics, allowing to test and debug in real time (RT) at a low cost. In this context, field-programmable gate arrays (FPGAs) play an important role due to the high-speed requirements of RT simulations, in which area optimization is also crucial. Both characteristics, area and speed, are affected by the numerical formats (NFs) and their rounding modes. Regarding FPGAs, Xilinx is one of the largest manufacturers in the world, offering Vivado as its main design suite, but it was not until the release of Vivado 2020.2 that support for the IEEE NF libraries of VHDL-2008 was included. This work presents an exhaustive evaluation of the performance of Vivado 2020.2 in terms of area and speed using the native IEEE libraries of VHDL-2008 regarding NF. Results show that even though fixed-point NFs optimize area and speed, if a user prefers the use of floating-point NFs, with this new release, it can be synthesized—which could not be done in previous versions of Vivado. Although support for the native IEEE libraries of VHDL-2008 was included in Vivado 2020.2, it still lacks some issues regarding NF conversion during synthesis while support for simulation is not yet included.

Centralized System Identification of Multi-Rail Power Converter Systems Using an Iterative Decimation Approach

This paper presents an iterative decimation approach to significantly alleviate the computational burden of centralized controllers applying real-time recursive system identification algorithms in multi-rail power converters. The proposed approach uses an adaptive update rate as opposed to the fixed update rate used in conventional adaptive filters. Also, the step size/forgetting factors vary at different iteration stages. As a result, a reduced computational burden and faster model update can be achieved. Besides, recursive algorithms, such as Recursive Least Square (RLS), Fast Affine Projection (FAP) and Kalman Filter (KF), contain two important updates per iteration cycle; Covariance Matrix Approximation (CMA) update and Gradient Vector (GV) update. Usually, the CMA update requires the greater computational effort than the GV update. Therefore, in circumstances where the sampled data in the regressor does not experience significant fluctuations, re-using the CMA, calculated from the last iteration cycle for the current update can result in computational cost savings for real-time system identification. In this paper, both iteration rate adjustment and CMA re-cycling are combined and applied to simultaneously identify the power converter models in a three-rail power conversion architecture.

Suppression of Chattering in the Real-Time Simulation of the Power Converter

The achievement of the time-step below 500-ns in the field-programmable-gate-arrays (FPGAs)-based real-time simulation is of importance for the power converters having high switching frequencies. However, most of the existing focus on addressing the power converter modeling under the continuous conduction mode (CCM). Nevertheless, toward practical applications, the modeling of discontinuous conduction mode (DCM) with a light-load is of a greater challenge due to the “chattering” around zero point. In order to solve the chattering problem under the light-load, this article proposes a zero-regulation (ZR) method for FPGA-based real-time simulation. The proposed ZR method can not only represent CCM and DCM with a unified formula but also solve the chattering problem and improve accuracy and stability. In addition, results using different switch models are also given to demonstrate the feasibility and the generality of the proposed method. Finally, a case study of the series load resonant converter is presented. Simulation results are validated against a reference model at a 100-ns time step and a 10-kHz switching frequency.

Improved finite control set model predictive control for distributed energy resource in islanded microgrid with fault-tolerance capability

In this paper, improved finite control set model predictive voltage control (FCS-MPVC) is proposed for the distributed energy resource (DER) in AC islanded microgrid (MG). Typically, AC MGs have two or more power electronic-based DERs, which have the ability to maintain a constant voltage at the point of common coupling (PCC) as well as perform power sharing among the DERs. Though linear controllers can achieve above-mentioned tasks, they have several restrictions such as slow transient response, poor disturbance rejection capability etc. The proposed control approach uses mathematical model of power converter to anticipate the voltage response for possible switching states in every sampling period. The proposed dual-objective cost function is designed to regulate the output voltage as well as load current under fault condition. Two-step horizon prediction technique reduces the switching frequency and computational burden of the designed algorithm. Performance of the proposed control technique is demonstrated through MATLAB/Simulink simulations for single distributed generator (DG) and AC MG under linear and non-linear loading conditions. The investigated work presents an excellent steady state performance, low computational overhead, better transient performance and robustness against parametric variations in contrast to classical controllers. Total harmonic distortion (THD) for linear and non-linear load is 0.89% and 1.4% respectively as illustrated in simulation results. Additionally, the three-phase symmetrical fault current has been successfully limited to the acceptable range.

Word length selection method for HIL power converter models

Hardware in the Loop (HIL) allows one to emulate a system or part of it in real time, and it is, therefore, widely used for power electronics. Real-time simulations require high speed so FPGAs (Field Programmable Gate Array) in HIL are widely used. It is crucial to minimize the delay and area, without losing either resolution or accuracy. Therefore, the Word Length (WL) of signals in power converter models has a huge influence. There are complex WL determination procedures that require long-time simulations. This paper presents a simple and analytical WL selection method for the signals of HIL models of converters. Signal groups are distinguished, and the WL signal is selected depending on the group the signals belong to. The method is applied to a boost and a buck converter in fixed-point. Finally, several rules are given to calculate the optimized WL in the signals of a power converter.

A parameter-averaging approach to converter system order reduction

In this study, we propose a parameter-averaging-based modeling (PAM) method using the state-space theory for high-order power converters with multiple dynamic components, e.g., inductors and capacitors. With the proposed PAM method, we aim to reduce the order of converter models, and thus diminish diminishing the computational burden when obtaining the steady-state operating point and transfer function. To demonstrate the procedure and functionality of the proposed order reduction method, a fifth-order power converter model is employed as an example, which is reduced to second order and first order in continuous conduction mode (CCM) and discontinuous conduction mode (DCM), respectively. Simulation studies prove that the reduced-order model is able to produce comparable system responses as the original model. The stimulation responses of the acquired transfer functions for reduced-order state spaces in CCM and DCM are further validated by hardware experimentation.

Adaptive Control for Three-Phase Power Converters With Disturbance Rejection Performance

This paper presents voltage regulation and current tracking control strategies for three phase two-level grid-connected power converters. By using power-invariant Park's transformation, an averaged mathematical model of power converters is obtained in dq synchronous reference frame. Then a novel control strategy using adaptive control and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> technique is proposed to regulate the dc-link output voltage as well as track a desired current reference for three-phase power rectifiers. More specifically, an efficient adaptive controller is established in the external loop for regulating dc-link output voltage in the presence of external disturbances. A set of H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> controllers are designed in the internal loop to force the input currents track their desired values. Finally, simulation results obtained from the proposed control method are presented, analyzed, and compared with that of sliding mode control, and the superiority of the proposed control laws is verified.

Maximum Virtual Inertia From DC-Link Capacitors Considering System Stability at Voltage Control Timescale

In power electronics-dominant systems (PEDSs), the declining-inertia issue is one of the most significant challenges to tackle. The inertia emulation from DC-link capacitors is one cost-effective and application-friendly solution to enhance the system inertia. Although the virtual inertia control of the DC-link capacitor supports the grid frequency with a relatively long-term effect, it affects the dynamic of the power converter at multiple timescales. In turn, the maximum effective virtual inertia from the DC-link capacitor is limited by the operation condition of the converter. Thus, to properly design the virtual inertia control, the dynamics of the faster timescale than the inertia emulation should be addressed. With the above, this article analyzes the maximum virtual inertia of DC-link capacitors based on a multi-timescale model of power converters. First, the system stability considering virtual inertia control of DC-link capacitors is analyzed in the submodel at the voltage control timescale (VCT), where the virtual inertia control parameters are accordingly tuned on a pre-designed converter. Then, the maximum effective virtual inertia is identified in the submodel at the rotor motion timescale (RMT). The exploration and findings in this article are beneficial to the power converter design and future inertia placement optimization in PEDSs. Case studies on a hardware-in-the-loop platform are conducted to validate the proposed model and the analysis method.

Design of precise simulation model of power converter of energy storage system located within micro-grids

In this paper, the modeling procedure of the bidirectional power converter for energy storage systems located within microgrids is being described. The aim was to develop simulation model with accurate behavior compared to experimental sample, due to implementation of the model within system-level simulations of complex microgrid systems. Simulations have been performed with PLECS circuit simulator. Also experimental sample similar to circuit topology of simulation model was realized within reduced power ration of the target application (1:10). Simulation models have been optimized based on laboratory findings to obtain the maximum degree of operating property precision possible. As a result of this approach, high-accuracy simulation models of DC microgrid systems can be created, allowing any operating scenario to be investigated at the appropriate power delivery.

Fault Diagnosis for Power Converters Based on Optimized Temporal Convolutional Network

In this article, the fault diagnosis problem for power converters is considered. Given that the existing fault diagnosis models rarely address the problems of the data noise and the new faults that are never emerged in the database, thus, an optimized fault diagnosis model for power converters based on temporal convolutional network (TCN) is proposed. Our contributions include the following: 1) unknown faults can be efficiently distinguished with an optimized classifier; 2) the proposed model has good robustness and reliability under noisy environment without any subsidiary predenoising algorithm; and 3) it can realize adaptive feature extraction, and the parameters are small. Experimental results on a three-phase voltage inverter platform demonstrate that the proposed approach is efficient and can be adaptively applied to various real applications.