Coast function parameters optimization for DC battery source inverter feeding three-phase inductive load

The commonly reported measures of the predictive accuracy are evaluated in this paper. Absolute, squared, percentage, and integral errors methods are implemented, to reduce the objective function, which employed in model predictive control. These methods are usually investigated for dc source inverter, which controlled by finite set model predictive current control system, with three phase induction motor load. In this paper, the evaluation includes different aspects, accuracy, complexity, system harmonics content, and execution time. A vital criterion in this process is the performance of the inverter, and the matching between the reference and the measured machine currents. The evaluation shows that for one term objective function, absolute and square errors give similar results with less execution time for the absolute error, but if multi terms objective function the square error is better.

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Finite Set Model Predictive Current Control of Three Phase Neutral Point Clamped Inverter with Reduced Leg Count

Lecture Notes in Electrical Engineering - Emerging Trends in Electrical, Communications and Information Technologies ◽

10.1007/978-981-10-1540-3_33 ◽

2016 ◽

pp. 319-326

Author(s):

Eedara Aswani Kumar ◽

K. Chandra Sekhar ◽

R. Srinivasa Rao

Keyword(s):

Current Control ◽

Neutral Point ◽

Three Phase ◽

Finite Set

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Design and Digital Implementation of Constant Frequency Hysteresis Current Controller for Three-Phase Voltage Source Inverter Using TMS320F2812

International Journal of Emerging Electric Power Systems ◽

10.1515/ijeeps-2013-0141 ◽

2014 ◽

Vol 15 (1) ◽

pp. 13-23 ◽

Cited By ~ 1

Author(s):

D. Kalyanraj ◽

S. Lenin Prakash

Keyword(s):

Current Control ◽

Control Technique ◽

Voltage Source ◽

Phase Voltage ◽

Inductive Load ◽

Constant Frequency ◽

Digital Implementation ◽

Hysteresis Current Control ◽

Current Controller ◽

Three Phase

Abstract A constant frequency hysteresis current control technique for a three-phase voltage source inverter (VSI) has been developed for AC drives, power quality and renewable energy applications. This paper presents a digital implementation of a constant frequency hysteresis current control technique for a three-phase VSI feeding an inductive load, using digital signal controller TMS320F2812. The limitations of variable frequency hysteresis control have been discussed and overcoming these limitations by means of digital implementation has been proposed. The complete design procedure of the proposed technique has been presented with an illustrative example. The three-phase VSI feeding an inductive load has also been simulated by using MATLAB and the simulation results have been presented. The hardware results of hysteresis current controlled three-phase VSI feeding an inductive load have been presented. Also the performance analysis of the hysteresis current controller has been presented. Operation of this controller has also been explained with a help of phase plane trajectory of hysteresis controller.

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New Three-Phase Current Control Methods Using Quasi-Current-Error for AC Motor Drives

IEEJ Transactions on Industry Applications ◽

10.1541/ieejias.134.821 ◽

2014 ◽

Vol 134 (9) ◽

pp. 821-832 ◽

Cited By ~ 3

Author(s):

Shinji Shinnaka

Keyword(s):

Current Control ◽

Motor Drives ◽

Control Methods ◽

Phase Current ◽

Ac Motor ◽

Three Phase ◽

Ac Motor Drives ◽

Current Error

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Inductor Saturation Compensation in Three-Phase Three-Wire Voltage-Source Converters via Inverse System Dynamics-I

10.36227/techrxiv.12378371 ◽

2020 ◽

Author(s):

Ziya Özkan ◽

Ahmet Masum Hava

Keyword(s):

Dynamic Model ◽

Dynamic Performance ◽

Current Control ◽

Inverse System ◽

Voltage Source ◽

Voltage Source Converter ◽

Two Phase ◽

Inverse Dynamic ◽

Three Phase ◽

Steady State Current

In three-phase three-wire (3P3W) voltage-source converter (VSC) systems, utilization of filter inductors with deep saturation characteristics is often advantageous due to the improved size, cost, and efficiency. However, with the use of conventional synchronous frame current control (CSCC) methods, the inductor saturation results in significant dynamic performance loss and poor steady-state current waveform quality. This paper proposes an inverse dynamic model based compensation (IDMBC) method to overcome these performance issues. Accordingly, a review of inductor saturation and core materials is performed, and the motivation on the use of saturable inductors is clarified. Then, two-phase exact modelling of the 3P3W VSC control system is obtained and the drawbacks of CSCC have been demonstrated analytically. Based on the exact modelling, the inverse system dynamic model of the nonlinear system is obtained and employed such that the nonlinear plant is converted to a fictitious linear inductor system for linear current regulators to perform satisfactorily.

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Optimal Selection of Conductors in Three-Phase Distribution Networks Using a Discrete Version of the Vortex Search Algorithm

Computation ◽

10.3390/computation9070080 ◽

2021 ◽

Vol 9 (7) ◽

pp. 80

Author(s):

John Fernando Martínez-Gil ◽

Nicolas Alejandro Moyano-García ◽

Oscar Danilo Montoya ◽

Jorge Alexander Alarcon-Villamil

Keyword(s):

Objective Function ◽

Power Flow ◽

Phase Distribution ◽

Search Algorithm ◽

Distribution Networks ◽

Discrete Version ◽

Optimal Selection ◽

Flow Method ◽

Three Phase ◽

Selection Of

In this study, a new methodology is proposed to perform optimal selection of conductors in three-phase distribution networks through a discrete version of the metaheuristic method of vortex search. To represent the problem, a single-objective mathematical model with a mixed-integer nonlinear programming (MINLP) structure is used. As an objective function, minimization of the investment costs in conductors together with the technical losses of the network for a study period of one year is considered. Additionally, the model will be implemented in balanced and unbalanced test systems and with variations in the connection of their loads, i.e., Δ− and Y−connections. To evaluate the costs of the energy losses, a classical backward/forward three-phase power-flow method is implemented. Two test systems used in the specialized literature were employed, which comprise 8 and 27 nodes with radial structures in medium voltage levels. All computational implementations were developed in the MATLAB programming environment, and all results were evaluated in DigSILENT software to verify the effectiveness and the proposed three-phase unbalanced power-flow method. Comparative analyses with classical and Chu & Beasley genetic algorithms, tabu search algorithm, and exact MINLP approaches demonstrate the efficiency of the proposed optimization approach regarding the final value of the objective function.

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Model-Free Predictive Current Control for Three-Phase Power Converters With LCL Filter

2020 IEEE Energy Conversion Congress and Exposition (ECCE) ◽

10.1109/ecce44975.2020.9236083 ◽

2020 ◽

Author(s):

Xiang Liu ◽

Yongchang Zhang ◽

Haitao Yang ◽

Jose Rodriguez

Keyword(s):

Power Converters ◽

Current Control ◽

Lcl Filter ◽

Model Free ◽

Three Phase

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EXPRESS: Baseline Correction Based on a Search Algorithm from Artificial Intelligence

Applied Spectroscopy ◽

10.1177/0003702820977512 ◽

2020 ◽

pp. 000370282097751

Author(s):

Xin Wang ◽

Xia Chen

Keyword(s):

Artificial Intelligence ◽

Objective Function ◽

Least Squares ◽

Least Squares Method ◽

Search Algorithm ◽

Absolute Error ◽

Search Problem ◽

Baseline Correction ◽

Current Spectrum ◽

Data Points

Many spectra have a polynomial-like baseline. Iterative polynomial fitting (IPF) is one of the most popular methods for baseline correction of these spectra. However, the baseline estimated by IPF may have substantially error when the spectrum contains significantly strong peaks or have strong peaks located at the endpoints. First, IPF uses temporary baseline estimated from the current spectrum to identify peak data points. If the current spectrum contains strong peaks, then the temporary baseline substantially deviates from the true baseline. Some good baseline data points of the spectrum might be mistakenly identified as peak data points and are artificially re-assigned with a low value. Second, if a strong peak is located at the endpoint of the spectrum, then the endpoint region of the estimated baseline might have significant error due to overfitting. This study proposes a search algorithm-based baseline correction method (SA) that aims to compress sample the raw spectrum to a dataset with small number of data points and then convert the peak removal process into solving a search problem in artificial intelligence (AI) to minimize an objective function by deleting peak data points. First, the raw spectrum is smoothened out by the moving average method to reduce noise and then divided into dozens of unequally spaced sections on the basis of Chebyshev nodes. Finally, the minimal points of each section are collected to form a dataset for peak removal through search algorithm. SA selects the mean absolute error (MAE) as the objective function because of its sensitivity to overfitting and rapid calculation. The baseline correction performance of SA is compared with those of three baseline correction methods: Lieber and MahadevanâJansen method, adaptive iteratively reweighted penalized least squares method, and improved asymmetric least squares method. Simulated and real FTIR and Raman spectra with polynomial-like baselines are employed in the experiments. Results show that for these spectra, the baseline estimated by SA has fewer error than those by the three other methods.

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