scholarly journals An efficient Capacitor Bank Operating System for Single Phase Power Factor Correction using Neural Network Estimations

2021 ◽  
Vol 3 (3) ◽  
pp. 169-183
Author(s):  
Subarna Shakya
Keyword(s):  
Neural Network ◽  
Operating System ◽  
Power Factor ◽  
Capacitor Bank ◽  
Motor Units ◽  
Industrial Applications ◽  
Energy Utilization ◽  
Electrical System ◽  
Electrical Loading ◽  
The Right

Wastage of electricity occurs in all places starting from a small house electrical loading to a heavy industrial electrical loading. KiloVolt-Ampere Reactive (KVAR) power metering devices are employed in industrial applications for measuring the energy utilization which measure the energy wastage along with it. This urges a consumer to pay for the unutilized or wasted energy as well. To avoid this, certain capacitor bank units are connected to the industrial application motor units. The right choice of capacitor rating are helpful in minimizing the wasted power observation in the KVAR meters. The selection of capacitor rating is analysed with respect to the power factor calculation. The power factor is a derivation of working power to the apparent power in an electrical system. An optimum power factor to be maintained in an electrical system is 1. The motive of the proposed work is to maintain the power factor by selecting an optimum capacitor bank on the operation of an electrical system at various load conditions. The requirement of capacitor bank values get changed with respect to the load given to an electrical system. A neural network based prediction model is employed in the work for estimating the right choice of capacitor bank. The efficiency of the proposed work is verified and found satisfied with a traditional capacitor bank operating system.

scholarly journals Pengaruh Penggunaan Kapasitor Bank pada Penyulang Kota di PT. PLN (Persero) Rayon Meulaboh Kota

2020 ◽  
Vol 1 (2) ◽  
pp. 21-28
Author(s):  
Haimi Ardiansyah
Keyword(s):  
Electric Power ◽  
Power Factor ◽  
Power Plants ◽  
Reactive Power ◽  
Capacitor Bank ◽  
Active Power ◽  
Electrical System ◽  
Capacitor Banks ◽  
Absolute Requirement ◽  
Electric Supply

Haimi Ardiansyah Akademi Komunitas Negeri Aceh Barat _________________________ Abstract Penelitian ini membahas tentang pengaruh penggunaan kapasitor bank pada penyulang kota di PT. PLN (Persero) Rayon Meulaboh Kota. Pendistribusian tenaga listrik yang stabil adalah syarat mutlak yang harus dipenuhi PT. PLN (Persero) dalam menjawab kebutuhan konsumen. Bertambahnya beban yang bersifat induktif akan berpengaruh pada penurunan nilai faktor daya pada sistem kelistrikan. Selanjutnya kondisi ini juga akan membutuhkan daya reaktif yang sangat besar sehingga pembangkit listrik harus menyalurkan daya yang lebih besar. Salah satu upaya untuk memperbaiki faktor daya adalah dengan menambahkan beban kapasitif. Perbaikan faktor daya pada penyulang kota dengan menggunakan kapasitor bank bertujuan untuk meningkatkan daya aktif sehingga mendekati dengan daya semu yang diproduksi PT. PLN. Penggunakan kapasitor bank ini diharapkan mampu menurunkan daya reaktif dan memperbaiki faktor daya pada penyulang kota. Keywords: Daya Listrik, Daya Reaktif, Faktor daya, Kapasitor Bank __________________________ Abstrak The study discusses the effect of installing bank capacitor on city electric feeder at PT. PLN (Persero) Rayon Meulaboh Kota. Stable electric supply is an absolute requirement that must be met by PT. PLN (Persero) in answering consumer needs. The increase of inductive loads will affect the decrease power factor value in the electrical system. Furthermore, this condition will also require a very large reactive power so that power plants have to supply more electric power. Installing capacitive loads is one of the best options in improving the power factor. The improvement of power factor in city feeders using capacitor banks aims to increase the active power to get close to the apparent power which is produced by PT. PLN (Persero). In short, the use of capacitor banks is expected to reduce reactive power and improve the power factor in city feeders. Kata Kunci: Electric Power, Reactive Power, Power Factor, Capacitor Bank __________________________

scholarly journals Analisis Injeksi Daya Reaktif Untuk Memperbaiki Faktor Daya Pada Line Instalasi Listrik Gedung Workshop AK-Manufaktur Bantaeng

2021 ◽  
Vol 7 (1) ◽  
pp. 1-4
Author(s):  
Hermansyah Hermansyah
Keyword(s):  
Power Factor ◽  
Reactive Power ◽  
Capacitor Bank ◽  
Active Power ◽  
Analysis Method ◽  
Electrical System ◽  
Power Injection ◽  
Electrical Installation

This research is a case study, namely the electrical installation system for AK-Manufacturing Bantaeng fabrication workshops. This study aims to improve the value of cos φ (power factor) from 0.75 to 0.97 and to determine the capacity of the capacitor bank that will be installed on the electrical installation line of the AK-Manufacturing Bantaeng Fabrication Machine workshop building. The problem that occurs is the low value of cos φ (power factor) in the installed electrical system which causes the installed active power to be not maximal. For this reason, a capacitor bank with an adjusted capacity value is needed to provide reactive power injection so that the value of cos φ can be increased from 0.75 to 0.97. This study uses an analysis method to determine the value of reactive power to be injected into the electrical installation system. The results of this study indicate that the required reactive power injection capacity is 12 KVar or 12,000 Var. This value is sufficient to improve the power factor from 0.75 to 0.97. This means that the electrical installation system is more optimal.

scholarly journals Embedded operating system and industrial applications: a review

2021 ◽  
Vol 10 (3) ◽  
pp. 1687-1700
Author(s):  
Yew Ho Hee ◽  
Mohamad Khairi Ishak ◽  
Mohd Shahrimie Mohd Asaari ◽  
Mohamad Tarmizi Abu Seman
Keyword(s):  
Operating System ◽  
Embedded System ◽  
Industrial Applications ◽  
Influential Factors ◽  
Consumer Electronics ◽  
Embedded Operating System ◽  
Embedded Os ◽  
Working Principle ◽  
And Performance ◽  
The Right

The complexity of an embedded system is directly proportional to the requirements of industrial applications. Various embedded operating system (OS) approaches had been built to fulfil the requirements. This review aims to systematically address the similarities and differences of the embedded OS solutions and analyse the factors that will influence decision-making when choosing what solution to use in the applications. This paper reviews three standard solutions; super loop, cooperative, and real-time operating system (RTOS). These are commonly used in industrial applications. By grouping the tasks in the foreground and background execution region, the concept and working principle of each of them are reviewed. The unique feature of RTOS in the context of task switching was used to define the deterministic characteristic of meeting the deadlines. The importance and performance of this characteristic is addressed and compared among various solutions in this paper. Subsequently, this paper reviewed the internet of things (IoT) requirements, automotive, medical and consumer electronics industry. The influential factors on choosing the right embedded OS to be used are extracted based on the requirements. They are reviewed in the perspective of memory footprint, regulated standards, cost-effectiveness, time effectiveness, and scalability.

scholarly journals Capacitor bank controller using artificial neural network with closed-loop system

2020 ◽  
Vol 9 (4) ◽  
pp. 1379-1386
Author(s):  
Widjonarko Widjonarko ◽  
Cries Avian ◽  
Andi Setiawan ◽  
Moch. Rusli ◽  
Eka Iskandar
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Control System ◽  
Low Power ◽  
Power Factor ◽  
Closed Loop ◽  
Capacitor Bank ◽  
Industrial Equipment ◽  
Closed Loop System ◽  
Artificial Neural

The problem of power factor in the industry is critical. This is due to the issue of low power factor that can make the vulnerability of industrial equipment damaged. This problem has been resolved in various ways, one of which is the Automatic Power Factor Correction, with the most popular device called capacitor bank. There are also many methods used, but several methods require certain calculations so the system can adapt to the new plant. In this study, researchers proposed a capacitor bank control system that can adapt to plants with different capacitor values without using any calculations by using an Artificial Neural Network with a closed-loop controller. The system is simulated using Simulink Matlab to know the performance with two testing scenarios. The first is changing the value of the power factor on the system and changing the value of the capacitor power at each bank, the second comparing it with the conventional methods. The results show that the system has been able to adapt to different capacitor power values and has a better performance than the conventional method in power factor oscillation due to the extreme power factor interference

Valid Signature Detection and Verification for Security of Individual Person

2016 ◽  
Vol 1 (1) ◽  
pp. 50-53 ◽  
Author(s):  
Varun Sharma ◽  
Narpat Singh
Keyword(s):  
Neural Network ◽  
Comparative Analysis ◽  
Recent Work ◽  
Research Work ◽  
Early Research ◽  
Individual Person ◽  
Signature Detection ◽  
Online Signature ◽  
The Right ◽  
Handwritten Signature

In the recent research work, the handwritten signature is a suitable field to detection of valid signature from different environment such online signature and offline signature. In early research work, a lot of unauthorized person put the signature and theft the data in illegal manner from organization or industries. So we have to need identify, the right person on the basis of various parameters that can be detected. In this paper, we have proposed two methods namely LDA and Neural Network for the offline signature from the scan signature image. For efficient research, we have focused the comparative analysis in terms of FRR, SSIM, MSE, and PSNR. These parameters are compared with the early work and the recent work. Our proposed work is more effective and provides the suitable result through our method which leads to existing work. Our method will help to find legal signature of authorized use for security and avoid illegal work.

scholarly journals Hybrid Reference Current Generation Theory for Solar Fed UPFC System

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1527
Author(s):  
R. Senthil Kumar ◽  
K. Mohana Sundaram ◽  
K. S. Tamilselvan
Keyword(s):  
Neural Network ◽  
Power Factor ◽  
Reactive Power ◽  
Voltage Source ◽  
Unity Power Factor ◽  
Current Generation ◽  
Load Voltage ◽  
Reference Current Generation ◽  
Source Current

The extensive usage of power electronic components creates harmonics in the voltage and current, because of which, the quality of delivered power gets affected. Therefore, it is essential to improve the quality of power, as we reveal in this paper. The problems of load voltage, source current, and power factors are mitigated by utilizing the unified power flow controller (UPFC), in which a combination of series and shunt converters are combined through a DC-link capacitor. To retain the link voltage and to maximize the delivered power, a PV module is introduced with a high gain converter, named the switched clamped diode boost (SCDB) converter, in which the grey wolf optimization (GWO) algorithm is instigated for tracking the maximum power. To retain the link-voltage of the capacitor, the artificial neural network (ANN) is implemented. A proper control of UPFC is highly essential, which is achieved by the reference current generation with the aid of a hybrid algorithm. A genetic algorithm, hybridized with the radial basis function neural network (RBFNN), is utilized for the generation of a switching sequence, and the generated pulse has been given to both the series and shunt converters through the PWM generator. Thus, the source current and load voltage harmonics are mitigated with reactive power compensation, which results in attaining a unity power factor. The projected methodology is simulated by MATLAB and it is perceived that the total harmonic distortion (THD) of 0.84% is attained, with almost a unity power factor, and this is validated with FPGA Spartan 6E hardware.

scholarly journals Image Restoration by Learning Morphological Opening-Closing Network

2020 ◽  
Vol 4 (1) ◽  
pp. 87-107
Author(s):  
Ranjan Mondal ◽  
Moni Shankar Dey ◽  
Bhabatosh Chanda
Keyword(s):  
Neural Network ◽  
Image Restoration ◽  
State Of The Art ◽  
Source Code ◽  
Back Propagation ◽  
Image Features ◽  
Main Difficulty ◽  
The Right ◽  
Right Order ◽  
Morphological Opening

AbstractMathematical morphology is a powerful tool for image processing tasks. The main difficulty in designing mathematical morphological algorithm is deciding the order of operators/filters and the corresponding structuring elements (SEs). In this work, we develop morphological network composed of alternate sequences of dilation and erosion layers, which depending on learned SEs, may form opening or closing layers. These layers in the right order along with linear combination (of their outputs) are useful in extracting image features and processing them. Structuring elements in the network are learned by back-propagation method guided by minimization of the loss function. Efficacy of the proposed network is established by applying it to two interesting image restoration problems, namely de-raining and de-hazing. Results are comparable to that of many state-of-the-art algorithms for most of the images. It is also worth mentioning that the number of network parameters to handle is much less than that of popular convolutional neural network for similar tasks. The source code can be found here https://github.com/ranjanZ/Mophological-Opening-Closing-Net

Design of Neural Network Based on Rough Set

2012 ◽  
Vol 263-266 ◽  
pp. 3378-3381
Author(s):  
Xue Min Zhang ◽  
Zhen Dong Mu
Keyword(s):  
Neural Network ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Neural Network Classification ◽  
The Neural Network ◽  
Sample Test ◽  
Low Efficiency ◽  
The Right ◽  
Test Module

After years of development, the neural network classification, clustering and forecasting applications have a lot of development, but the neural network has the inevitable defects, if you enter the attribute set, the classification boundaries are not clear, convergence low efficiency and accuracy, there may even be the state does not converge, using rough set theory, the right value to modify the function to be modified, and joined the contradictions sample test module, after the use of EEG to verify reached the deletion of number of features and the purpose to improve the classification accuracy.

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