scholarly journals A Genetic-Algorithm-Based DC Current Minimization Scheme for Transformless Grid-Connected Photovoltaic Inverters

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 746 ◽  
Author(s):  
Lei Song ◽  
Lijun Huang ◽  
Bo Long ◽  
Fusheng Li
Keyword(s):  
Genetic Algorithm ◽  
Back Propagation ◽  
The Novel ◽  
Proof Of Concept ◽  
Three Phase ◽  
Suppression Process ◽  
Dc Current ◽  
Three Phase Inverter ◽  
Minimization Scheme

Transformerless grid-connected inverters are of great industrial value in photovoltaic power generation. However, the direct current (DC) induced into the inverter’s output degrades the power quality of the grid. Recently, a back-propagation neural work proportional–integral–derivative (BP-PID) scheme has proven helpful in solving this problem. However, this scheme can be improved by reducing the suppressing time and overshoot. A genetic algorithm (GA)-based DC current minimization scheme, namely the genetic-algorithm-based BP-PID (GA-BP-PID) scheme, was established in this study. In this scheme, GA was used off-line to optimize the initial weights within the BP neural network. Subsequently, the optimal weight was applied to the online DC current suppression process. Compared with the BP-PID scheme, the proposed scheme can reduce the suppressing time by 59% and restrain the overshoot. A prototype of the proposed scheme was implemented and tested on experimental hardware as a proof of concept. The results of the scheme were verified using a three-phase inverter experiment. The novel GA-PB-PID scheme proposed in this study was proven efficient in reducing the suppressing time and overshoot.

Direct Current Deadbeat Predictive Controller for BLDC Motor Using Single DC-Link Current Sensor

2020 ◽  
Vol 38 (8A) ◽  
pp. 1187-1199
Author(s):  
Qaed M. Ali ◽  
Mohammed M. Ezzalden
Keyword(s):  
Control System ◽  
High Speed ◽  
Fast Response ◽  
Bldc Motor ◽  
Current Controller ◽  
Three Phase ◽  
Predictive Controller ◽  
Two Phases ◽  
Dc Current ◽  
Three Phase Inverter

BLDC motors are characterized by electronic commutation, which is performed by using an electric three-phase inverter. The direct control system of the BLDC motor consists of double loops; including the inner-loop for current regulating and outer-loop for speed control. The operation of the current controller requires feedback of motor currents; the conventional current controller uses two current sensors on the ac side of the inverter to measure the currents of two phases, while the third current would be accordingly calculated. These two sensors should have the same characteristics, to achieve balanced current measurements. It should be noted that the sensitivity of these sensors changes with time. In the case of one sensor fails, both of them must be replaced. To overcome this problem, it is preferable to use one sensor instead of two. The proposed control system is based on a deadbeat predictive controller, which is used to regulate the DC current of the BLDC motor. Such a controller can be considered as digital controller mode, which has fast response, high precision and can be easily implemented with microprocessor. The proposed control system has been simulated using Matlab software, and the system is tested at a different operating condition such as low speed and high speed.

scholarly journals Optimization and comparative analysis of PID and FOPID controller for BLDC motor

2019 ◽  
Vol 8 (3) ◽  
pp. 174
Author(s):  
P. Vimala ◽  
C. R. Balamurugan ◽  
A. Subramanian ◽  
T. Vishwanath
Keyword(s):  
Genetic Algorithm ◽  
Comparative Analysis ◽  
Input Signal ◽  
Pid Controller ◽  
Input Voltage ◽  
Bldc Motor ◽  
Phase Inverter ◽  
Three Phase ◽  
The Stability ◽  
Three Phase Inverter

The FOPID and PID controller are designed to control the speed of <br /> the BLDC motor. The parameters , , , λ and µ of these controller are optimized based on genetic algorithm. The optimized coefficients keep in track with zero error signals. The output of the controller is given to the variable dc source which varies the input voltage to the three phase inverter depending on the input signal. The three phase inverter gives the voltage to the BLDC motor which enhances the stability of the system. <br /> The effectiveness of the controller is demonstrated by simulation.

scholarly journals Mitigation of DC Components Using Adaptive BP-PID Control in Transformless Three-Phase Grid-Connected Inverters

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2047 ◽  
Author(s):  
Long Bo ◽  
Lijun Huang ◽  
Yufei Dai ◽  
Youliang Lu ◽  
Kil To Chong
Keyword(s):  
Pid Control ◽  
Pulse Width Modulation ◽  
High Efficiency ◽  
Back Propagation ◽  
Power Transistors ◽  
Three Phase ◽  
The Subject ◽  
Dc Component ◽  
Driving Signal

Transformerless grid-connected inverters, due to their advantages of high efficiency, small volume and light weight, have been the subject of more research and interest in recent years. Due to the asymmetrical driving signal in pulse width modulation (PWM) caused by time-delay, zero-drift of the current sensors and imparities of the power transistors, output of the grid current contains dc component. As a result, power quality of the grid is degraded. In this paper, a dc (direct current) component suppression scheme with adaptive back-propagation (BP) neural network proportional-integral-differential (PID) control is proposed for dc component minimization. Moreover, sliding-window-double-iteration-method (SWDIM) is utilized for fast dc component extraction. Compared with the conventional method, the proposed scheme shows better performance, and the dc component can be attenuated to be within 0.5% of the rated current.

A Generic PWM Scheme Be Used for CSC

2012 ◽  
Vol 614-615 ◽  
pp. 1519-1523
Author(s):  
Tai Bin Cao ◽  
Man Lin Chen
Keyword(s):  
Phase Transfer ◽  
Switching Frequency ◽  
The Novel ◽  
Phase Line ◽  
Digital Implementation ◽  
Switching Patterns ◽  
Three Phase ◽  
Modulation Signal ◽  
Current Utilization ◽  
Dc Current

In order to overcome the drawbacks of the conventional SPWM for three-phase CSC, this paper presents a generic novel PWM scheme. In the novel PWM scheme, one line cycle is divided into six 60° intervals, and during each interval, only two references are used to compare with the carriers to directly generate the required switching patterns. Because of the optional modulation signal, the modulation technique has the advantages of flexible and easy digital implementation. It is shown that, compared with the conventional SPWM, the novel PWM scheme has lower switching frequency, higher dc current utilization ratio and in-phase transfer between the three-phase line currents and the reference signals. Finally, the propositions are verified by the experimental results.

Novel Compact Genetic Algorithm for WTA Problem

2012 ◽  
Vol 239-240 ◽  
pp. 1437-1441 ◽  
Author(s):  
Zhen Liu ◽  
Yun An Hu
Keyword(s):  
Genetic Algorithm ◽  
Experimental Results ◽  
The Novel ◽  
Simple Genetic Algorithm ◽  
Exchange Information ◽  
Compact Genetic Algorithm ◽  
Two Populations ◽  
Novel Algorithm ◽  
Better Than

The paper proposed a novel compact genetic algorithm which is named as pseudo-parallel compact genetic algorithm. There are two populations in the process of evolution, and the two subpopulation can exchange information between each other. The experimental results show that the novel algorithm performs better than simple genetic algorithm. Then it is used to solve weapon target allocation (WTA) problem, and the simulation result shows that it is more efficient comparing with other methods. Because the compact genetic algorithm is easy to operate and take up less memory, so the algorithm exhibit a better quality of solution and the required less time than before.

Prediction for Air-Bending Springback Radius of Sheet Metal Using Back Propagation Neural Network and Micro Genetic Algorithm

2011 ◽  
Vol 219-220 ◽  
pp. 1174-1177
Author(s):  
Ze Min Fu ◽  
Guang Ming Liu
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Sheet Metal ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Accurate Prediction ◽  
Air Bending ◽  
Micro Genetic Algorithm ◽  
Bpnn Model

Springback radius is a very important factor to influence the quality of sheet metal air-bending forming. Accurate prediction of springback radius is essential for the design of air-bending tools. In this paper, a three-layer back propagation neural network (BPNN), integrated with micro genetic algorithm (MGA), is proposed to solve the problem of springback radius. A micro genetic algorithm is used for minimizing the error between the predictive value and the experimental one. Based on air-bending experiment, the prediction model of springback radius is developed by using the integrated neural network. The results show that more accurate prediction of springback radius can be obtained with the MGA-BPNN model. It can be taken as a valuable tool for air-bending forming of sheet metal.

scholarly journals Design of a New Duty Cycle Modulation to Improve the Energy Quality of an Insulated Production System

2021 ◽  
Vol 23 (4) ◽  
pp. 311-319
Author(s):  
Clément Kengnou Donfack ◽  
Charles Hubert Kom ◽  
Jean Jacques Mandeng ◽  
Félix Paune
Keyword(s):  
Duty Cycle ◽  
Pulse Width Modulation ◽  
Renewable Energy Sources ◽  
Control Technique ◽  
Three Phase ◽  
New Strategy ◽  
The One ◽  
Sinusoidal Pulse Width Modulation ◽  
Three Phase Inverter

In this article, we propose a new strategy for controlling three-phase inverters of renewable energy sources, based on the Duty Cycle Modulatiom (DCM) control using the Park and Fortescue transformation (DCM-dq-dih). Our goals in setting and using this strategy are, on the one hand, to induce a lower harmonic rate as compared to the SPWM (Sinusoidal Pulse Width Modulation) strategy and on the other hand, this control technique enables the inverter to deliver balanced voltages, be it in the event of load unbalance. Our design is built on the basis of the known mode of DCM control of single-phase inverters. Thus, the control of our three-phase inverter is carried out by three DCM modules whose set-points come from the direct, reverse and homopolar strings reconstructed in a Park landmark. This new strategy was tested on the MATLAB Simulink environment for a load of 160 kW. The test results show a reduced Total Harmonic Distorsion (THD) of 2.7 times compared to the THD produced by the SPWM control strategy. In addition, regulation of the symmetrical components during load unbalance is ensured so that the inverter always delivers constant and balanced voltages.

NOVEL APPROACH BASED ON ARTIFICIAL NEURAL NETWORKS (ANN) FOR CONTROLLING THE THREE-PHASE INVERTER OF A PHOTOVOLTAIC SYSTEM

2021 ◽  
Vol 3 (1) ◽  
pp. C21A09-1-C21A09-6
Author(s):  
Daouda Gueye ◽  
◽  
Alphousseyni Ndiaye ◽  
Amadou Diao ◽  
◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Back Propagation ◽  
Harmonic Distortion ◽  
Photovoltaic System ◽  
Unity Power Factor ◽  
Novel Approach ◽  
Three Phase ◽  
Artificial Neural ◽  
Three Phase Inverter

This paper is devoted to the study of a photovoltaic system connected to the grid. The objective is to provide a novel approach based on artificial neural networks for Controlling the three-phase invelter in order to ensure a flexible injection to unity power factor and low total harmonic dist01tion. A modeling system established mathematical models of the invener and the DC link. A control in the synchronous reference direct and quadratic frame by a neural proportional integral derivative based on back propagation of gradient descent is offered to regulate respectively the dc link voltage and the injected cunents in order to overcome the limitations ofthe experimental tuning (Ziegler-Nichols) of the classical PID controller parameters. Simulation results from the system under the Matlab / Simulink environment prove the efficiency of the proposed method and show that the currents injected have the best sinusoidal fonn with a cunent Total Harmonic Distortion of 0.96 % and a net followed of the dc link voltage.

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