Erroneous branch parameters detection and correction in real time simulation of power systems

2016 ◽  
Vol 35 (5) ◽  
pp. 1656-1671
Author(s):  
Amin Helmzadeh ◽  
Shahram M. Kouhsari
Keyword(s):  
Simulation Model ◽  
State Estimation ◽  
Real Time ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Estimation Methods ◽  
Model Parameters ◽  
Content Type ◽  
Simulation Results ◽  
Correlated Parameters

Purpose The purpose of this paper is to propose an efficient method for detection and modification of erroneous branch parameters in real time power system simulators. The aim of the proposed method is to minimize the sum of squared errors (SSE) due to mismatches between simulation results and corresponding field measurements. Assuming that the network configuration is known, a limited number of erroneous branch parameters will be detected and corrected in an optimization procedure. Design/methodology/approach Proposing a novel formulation that utilizes network voltages and last modified admittance matrix of the simulation model, suspected branch parameters are identified. These parameters are more likely to be responsible for large values of SSE. Utilizing a Gauss-Newton (GN) optimization method, detected parameters will be modified in order to minimize the value of SSE. Required sensitivities in optimization procedure will be calculated numerically by the real time simulator. In addition, by implementing an efficient orthogonalization method, the more effective parameter will be selected among a set of correlated parameters to avoid singularity problems. Findings Unlike state estimation-based methods, the proposed method does not need the mathematical functions of measurements to simulation model parameters. The method can enhance other parameter estimation methods that are based on state estimation. Simulation results demonstrate the high efficiency of the proposed optimization method. Originality/value Incorrect branch parameter detection and correction procedures are investigated in real time simulators.

scholarly journals Experimental Verification of Real-Time Flow-Rate Estimations in a Tilting-Ladle-Type Automatic Pouring Machine

2021 ◽  
Vol 11 (15) ◽  
pp. 6701
Author(s):  
Yuta Sueki ◽  
Yoshiyuki Noda
Keyword(s):  
Real Time ◽  
Molten Metal ◽  
Flow Rate ◽  
Kalman Filters ◽  
Estimation Method ◽  
Estimation Methods ◽  
Liquid Volume ◽  
Model Parameters ◽  
Rate Estimation ◽  
Time Flow

This paper discusses a real-time flow-rate estimation method for a tilting-ladle-type automatic pouring machine used in the casting industry. In most pouring machines, molten metal is poured into a mold by tilting the ladle. Precise pouring is required to improve productivity and ensure a safe pouring process. To achieve precise pouring, it is important to control the flow rate of the liquid outflow from the ladle. However, due to the high temperature of molten metal, directly measuring the flow rate to devise flow-rate feedback control is difficult. To solve this problem, specific flow-rate estimation methods have been developed. In the previous study by present authors, a simplified flow-rate estimation method was proposed, in which Kalman filters were decentralized to motor systems and the pouring process for implementing into the industrial controller of an automatic pouring machine used a complicatedly shaped ladle. The effectiveness of this flow rate estimation was verified in the experiment with the ideal condition. In the present study, the appropriateness of the real-time flow-rate estimation by decentralization of Kalman filters is verified by comparing it with two other types of existing real-time flow-rate estimations, i.e., time derivatives of the weight of the outflow liquid measured by the load cell and the liquid volume in the ladle measured by a visible camera. We especially confirmed the estimation errors of the candidate real-time flow-rate estimations in the experiments with the uncertainty of the model parameters. These flow-rate estimation methods were applied to a laboratory-type automatic pouring machine to verify their performance.

scholarly journals LWD DATA INVERSION FOR STRUCTURE WITH ANGULAR UNCONFORMITY

2021 ◽  
Vol 2 (1) ◽  
pp. 336-344
Author(s):  
Anna S. Astrakova ◽  
Elena V. Konobriy ◽  
Dmitry Yu. Kushnir ◽  
Nikolay N. Velker ◽  
Gleb V. Dyatlov
Keyword(s):  
Real Time ◽  
Optimization Method ◽  
Parametric Model ◽  
Model Parameters ◽  
Time Inversion ◽  
Water Contact ◽  
2D Inversion ◽  
Angular Unconformity ◽  
Oil Water ◽  
2D Resistivity

Non-structural traps and reservoir flanks are characterized by angular unconformities. Angular unconformity between dipping formation and sub-horizontal oil-water contact is common in the North Sea fields. This paper presents an approach to real-time inversion of LWD resistivity data for the scenario with angular unconformity. The approach utilizes artificial neural networks (ANNs) for calculating the tool responses in parametric surface-based 2D resistivity models. We propose a parametric model with two non-parallel boundaries suitable for scenarios with angular unconformity and pinch-out. Training of ANNs for this parametric model is performed using a database containing samples with the model parameters and corresponding tool responses. ANNs are the kernel of 2D inversion based on the Levenberg-Marquardt optimization method. To demonstrate applicability of our approach and compare with the results of 1D inversion, we analyze Extra Deep Azimuthal Resistivity tool responses in a 2D synthetic model. It is shown that 1D inversion determines either the position of the oil-water contact or dipping layers structure. At the same time, 2D inversion makes it possible to correctly reconstruct the positions of non-parallel boundaries. Performance of 2D inversion based on ANNs is suitable for real-time applications.

State estimation in bioheat transfer: a comparison of particle filter algorithms

2017 ◽  
Vol 27 (3) ◽  
pp. 615-638 ◽  
Author(s):  
Bernard Lamien ◽  
Leonardo A.B. Varon ◽  
Helcio R.B. Orlande ◽  
Guillermo E. Elicabe
Keyword(s):  
Particle Filter ◽  
State Estimation ◽  
The Body ◽  
Computational Time ◽  
Model Parameters ◽  
Hyperthermia Treatment ◽  
Content Type ◽  
Sampling Importance Resampling ◽  
Importance Resampling ◽  
Filter Algorithms

Purpose The purpose of this paper is to focus on applications related to the hyperthermia treatment of cancer, with heating imposed either by a laser in the near-infrared range or by radiofrequency waves. The particle filter algorithms are compared in terms of computational time and solution accuracy. Design/methodology/approach The authors extend the analyses performed in their previous works to compare three different algorithms of the particle filter, as applied to the hyperthermia treatment of cancer. The particle filters examined here are the sampling importance resampling (SIR) algorithm, the auxiliary sampling importance resampling (ASIR) algorithm and Liu & West’s algorithm. Findings Liu & West’s algorithm resulted in the largest computational times. On the other hand, this filter was shown to be capable of dealing with very large uncertainties. In fact, besides the uncertainties in the model parameters, Gaussian noises, similar to those used for the SIR and ASIR filters, were added to the evolution models for the application of Liu & West’s filter. For the three filters, the estimated temperatures were in excellent agreement with the exact ones. Practical implications This work may help medical doctors in the future to prescribe treatment protocols and also opens the possibility of devising control strategies for the hyperthermia treatment of cancer. Originality/value The natural solution to couple the uncertain results from numerical simulations with the measurements that contain uncertainties, aiming at the better prediction of the temperature field of the tissues inside the body, is to formulate the problem in terms of state estimation, as performed in this work.

A novel global harmony search method based off-line tuning of RFNN for adaptive control of uncertain nonlinear systems

2015 ◽  
Vol 8 (1) ◽  
pp. 69-98 ◽  
Author(s):  
Fouad Allouani ◽  
Djamel Boukhetala ◽  
Fares Boudjema ◽  
Gao Xiao-Zhi
Keyword(s):  
Nonlinear System ◽  
Nonlinear Systems ◽  
Control Method ◽  
Harmony Search ◽  
Optimization Method ◽  
Uncertain Nonlinear Systems ◽  
Content Type ◽  
Supervisory Controller ◽  
Fuzzy Neural ◽  
Simulation Results

Purpose – The two main purposes of this paper are: first, the development of a new optimization algorithm called GHSACO by incorporating the global-best harmony search (GHS) which is a stochastic optimization algorithm recently developed, with the ant colony optimization (ACO) algorithm. Second, design of a new indirect adaptive recurrent fuzzy-neural controller (IARFNNC) for uncertain nonlinear systems using the developed optimization method (GHSACO) and the concept of the supervisory controller. Design/methodology/approach – The novel optimization method introduces a novel improvization process, which is different from that of the GHS in the following aspects: a modified harmony memory representation and conception. The use of a global random switching mechanism to monitor the choice between the ACO and GHS. An additional memory consideration selection rule using the ACO random proportional transition rule with a pheromone trail update mechanism. The developed optimization method is applied for parametric optimization of all recurrent fuzzy neural networks adaptive controller parameters. In addition, in order to guarantee that the system states are confined to the safe region, a supervisory controller is incorporated into the IARFNNC global structure. Findings – First, to analyze the performance of GHSACO method and shows its effectiveness, some benchmark functions with different dimensions are used. Simulation results demonstrate that it can find significantly better solutions when compared with the Harmony Search (HS), GHS, improved HS (IHS) and conventional ACO algorithm. In addition, simulation results obtained using an example of nonlinear system shows clearly the feasibility and the applicability of the proposed control method and the superiority of the GHSACO method compared to the HS, its variants, particle swarm optimization, and genetic algorithms applied to the same problem. Originality/value – The proposed new GHS algorithm is more efficient than the original HS method and its most known variants IHS and GHS. The proposed control method is applicable to any uncertain nonlinear system belongs in the class of systems treated in this paper.

FEA Simulation of Clinching Process Based on GTN Damage Model

2013 ◽  
Vol 652-654 ◽  
pp. 2254-2260 ◽  
Author(s):  
Bai Jun Shi ◽  
Shu Hui Liao ◽  
Song Peng ◽  
Hang Li
Keyword(s):  
Simulation Model ◽  
Sheet Material ◽  
Damage Model ◽  
Model Parameters ◽  
Material Damage ◽  
Gtn Damage Model ◽  
Fea Simulation ◽  
Simulation Results ◽  
Clinch Joining ◽  
Joining Process

In this work, the Gurson-Tvergaard-Needleman (GTN) damage model is adopted to depict the material damage during the clinch joining process in a simulation-based theoretical model. The parameters of the GTN model which influence the void nucleation, growth and coalescence are identified. Their values of a specific material, C45E4 (ISO) steel, have been determined after carefully comparing the simulation results with the real sheet material tensile test. The established GTN damage model parameters are then imported into the simulation model to investigate the material damage during the mechanical clinch joining process. The Finite Element Analysis (FEA) simulation results show promising, because the material’s initial damage position can be located and analyzed. For a given design, the initial fracture point was predicted which is located on the inner side of the clinched joint neck of the upper sheet, which matches with the results of the experimental test very well. It can be concluded that the incorporation of GTN damage model has extend the capability of the simulation model.

Real-Time Battery Model Identification Using a Two Time-Scaled Approach

2013 ◽  
Author(s):  
Yiran Hu ◽  
Yue-Yun Wang
Keyword(s):  
Parameter Identification ◽  
Least Squares ◽  
State Estimation ◽  
Real Time ◽  
Recursive Least Squares ◽  
Model Parameters ◽  
Identification Algorithm ◽  
Model Parameter ◽  
Battery Model ◽  
Model Parameter Identification

Battery state estimation (BSE) is one of the most important design aspects of an electrified propulsion system. It includes important functions such as state-of-charge estimation which is essentially for the energy management system. A successful and practical approach to battery state estimation is via real time battery model parameter identification. In this approach, a low-order control-oriented model is used to approximate the battery dynamics. Then a recursive least squares is used to identify the model parameters in real time. Despite its good properties, this approach can fail to identify the optimal model parameters if the underlying system contains time constants that are very far apart in terms of time-scale. Unfortunately this is the case for typical lithium-ion batteries especially at lower temperatures. In this paper, a modified battery model parameter identification method is proposed where the slower and faster battery dynamics are identified separately. The battery impedance information is used to guide how to separate the slower and faster dynamics, though not used specifically in the identification algorithm. This modified algorithm is still based on least squares and can be implemented in real time using recursive least squares. Laboratory data is used to demonstrate the validity of this method.

Simulation study on evolutionary cycle to cycle time control of exposure controlled projection lithography

2016 ◽  
Vol 22 (3) ◽  
pp. 456-464 ◽  
Author(s):  
Xiayun Zhao ◽  
David W. Rosen
Keyword(s):  
Real Time ◽  
Exposure Time ◽  
Simulation Study ◽  
Closed Loop ◽  
Control Method ◽  
Estimation Methods ◽  
Content Type ◽  
Process Dynamics ◽  
Time Control ◽  
Projection Lithography

Purpose Exposure controlled projection lithography (ECPL) is an additive manufacturing process based on controlled UV photopolymerization. This paper aims to explore an advanced closed-loop control methodology to ECPL. Design/methodology/approach This paper proposes an evolutionary cycle to cycle (EC2C) control method, and started with a reduced order EC2C time control to control only the exposure time for given DMD bitmaps, which correspond to target 3D part cross-sections. A preliminary EC2C time control scheme was developed and followed by two types of EC2C time controllers based on two different parameter estimation methods, recursive least squares and L1 norm minimization (L1Min). Both algorithms were in an exponential weighted form, resulting in EWRLS and EWL1Min, to weight more on recent data to reflect the current process dynamics. Findings EWRLS was found to outperform EWL1Min in terms of computation speed and stability. The simulation study demonstrated that the proposed EC2C time control method was capable of adaptively tracking the ECPL process dynamics and updating online the model parameters with real-time measurements. It could control perfectly the exposure time for each bitmap, achieving the desired height for each layer and resulting in a total cured height conforming to the target 3D part height. Research limitations/implications The accuracy of EC2C time control method relies heavily on fast and accurate measurement, and this research assumes availability of an adequate real-time metrology. Measurement errors are not considered in this paper and will be explored in future. Only simulation study was performed without physical experiments to verify the EC2C controller. Practical implications For implementation, a real-time measurement system needs to be developed and the EC2C control software needs to be programmed and interfaced with the physical system. Originality/value It concludes that EC2C control method is very promising for a physical implementation, and could be extended for the development of a more comprehensive closed-loop controller for both exposure time and intensity to improve the ECPL process precision and robustness.

An improved simulation model of switched reluctance motor including transient core losses for steady-state operation

2019 ◽  
Vol 38 (1) ◽  
pp. 477-499
Author(s):  
Wenju Yan ◽  
Hao Chen ◽  
Tong Xu ◽  
Kai Wang
Keyword(s):  
Steady State ◽  
Simulation Model ◽  
Real Time ◽  
Flux Density ◽  
High Speed ◽  
Content Type ◽  
Switched Reluctance ◽  
The Core ◽  
Core Losses ◽  
Steady State Simulation

Purpose An improved simulation model of switched reluctance motor (SRM) for steady-state operation that considers the core losses in the stator and rotor is established to obtain the steady performance of the high-speed SRM during the design, analysis and control of SRM driving system more accurately. Design/methodology/approach The transient core loss model for the material and SRM is presented. Then a new method for calculating the flux density of the motor in real time is introduced, and a steady-state simulation model of the SRM including real-time transient core losses calculation model is established according to the transient flux density. Because the transient core losses calculated by above method are the total core losses of the motor, a core losses distribution method is proposed and the steady-state simulation model of the SRM including the distributed core losses’ effect on the phase winding is established. Findings The comparison results show that the proposed model has higher accuracy than the traditional model, excluding core losses, especially at the moments when phase voltage is turn-on and turn-off. The proportion of the core losses to the motor losses increases with the increase in speed. So, the core losses’ effect on the steady-state performance of the high-speed SRM cannot be ignored. Originality/value The method to obtain flux density in the real time is presented and the improved steady-state simulation model of SRM that considering transient core losses is proposed.

Research on Automatic Controlling Method of TSC+TCR Typed Dynamic Reactive Power Compensation

2015 ◽  
Vol 1092-1093 ◽  
pp. 321-324 ◽  
Author(s):  
Ming Zhao ◽  
Shi Fu Zhang ◽  
Bin Yi ◽  
Xiao Qin Zhang ◽  
Dong Mei Zhang
Keyword(s):  
Control System ◽  
Power System ◽  
Simulation Model ◽  
Real Time ◽  
Power Factor ◽  
Reactive Power ◽  
Reactive Power Compensation ◽  
Primary System ◽  
Compensation Control ◽  
Simulation Results

A simulation model of 230kV substation primary system and TSC+TCR typed dynamic reactive power compensation control system was constituted with RTDS, and the feasibility of control system with a case was validated. The control system was to monitor the variation of power system equivalent susceptance with sampling the power system voltage, established the relationships between power system susceptance and the firing angle of TCR, adjusted TSC switch and TCR firing angle to dynamically compensate the reactive power of power system. The simulation results demonstrate that the control system can guarantee power system voltage stability and real-time adjust power factor.

Topology optimization of magnetostatic shielding using multistep evolutionary algorithms with additional searches in a restricted design space

2014 ◽  
Vol 33 (3) ◽  
pp. 894-913 ◽  
Author(s):  
Yoshifumi Okamoto ◽  
Yusuke Tominaga ◽  
Shinji Wakao ◽  
Shuji Sato
Keyword(s):  
Topology Optimization ◽  
Design Space ◽  
Random Search ◽  
Optimization Procedure ◽  
Optimization Method ◽  
General Purpose ◽  
Magnetic Flux Density ◽  
Target Domain ◽  
Content Type ◽  
Conventional Algorithm

Purpose – The purpose of this paper is to improve the multistep algorithm using evolutionary algorithm (EA) for the topology optimization of magnetostatic shielding, and the paper reveals the effectiveness of methodology by comparison with conventional optimization method. Furthermore, the design target is to obtain the novel shape of magnetostatic shielding. Design/methodology/approach – The EAs based on random search allow engineers to define general-purpose objects with various constraint conditions; however, many iterations are required in the FEA for the evaluation of the objective function, and it is difficult to realize a practical solution without island and void distribution. Then, the authors proposed the multistep algorithm with design space restriction, and improved the multistep algorithm in order to get better solution than the previous one. Findings – The variant model of optimized topology derived from improved multistep algorithm is defined to clarify the effectiveness of the optimized topology. The upper curvature of the inner shielding contributed to the reduction of magnetic flux density in the target domain. Research limitations/implications – Because the converged topology has many pixel element unevenness, the special smoother to remove the unevenness will play an important role for the realization of practical magnetostatic shielding. Practical implications – The optimized topology will give us useful detailed structure of magnetostatic shielding. Originality/value – First, while the conventional algorithm could not find the reasonable shape, the improved multistep optimization can capture the reasonable shape. Second, An additional search is attached to the multistep optimization procedure. It is shown that the performance of improved multistep algorithm is better than that of conventional algorithm.

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