Optimum reactive power to improve power factor in industry using genetic algortihm

Yani, Ahmad; Junaidi, Juliandry Kurniawan; Irwanto, M.; Haziah, A. H.

doi:10.11591/ijeecs.v14.i2.pp751-757

Cited by 6 publications

(6 citation statements)

References 10 publications

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“…In the literature, the number of application studies of the GA technique is uncountable and the fields of application are very diverse. These include for example: Power Supply System [19], Electric Vehicles [20], Traffic Light Signal Parameters Optimization [21], Dynamic Optimization Problems [22], Resolution university course schedules [23], Power factor improvement in the industry [24], etc. In the following, we present an application of the GA to the optimal design of a three-stage amplifier.…”

Section: Genetic Algorithmmentioning

confidence: 99%

A Genetic algorithm for the optimal design of a multistage amplifier

Beqal

Benhala

Zorkani

2020

IJECE

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The optimal sizing of analog circuits is one of the most complicated processes, because of the number of variables taken into, to the number of required objectives to be optimized and to the constraint functions restrictions. The aim is to automate this activity in order to accelerate the circuits design and sizing. In this paper, we deal with the optimization of the three stage bipolar transistor amplifier performances namely the voltage gain (AV), the input impedance (ZIN), the output impedance (ZOUT), the power consumption (P) and the low and the high cutoff frequency (FL,FH), through the Genetic Algorithm (GA). The presented optimization problem is of multi-dimensional parameters, and the trade-off of all parameters. In fact, the passive components (Resistors and Capacitors) are selected from manufactured constant values (E12, E24, E48, E96, E192) for the purpose of reduce the cost of design; also, the intrinsic parameters of transistors (hybrid parameters and the junction capacitances) are considered variables in order not to be limited in design. SPICE simulation is used to validate the obtained result/performances.

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Section: Genetic Algorithmmentioning

confidence: 99%

A Genetic algorithm for the optimal design of a multistage amplifier

Beqal

Benhala

Zorkani

2020

IJECE

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“…The relatively high temperature in a maintenance environment causes heat stress. Heat stress causes disruption to the growth of broiler chickens [Bayu, 2012;Yani, 2019]. This growth disturbance is related to a decrease in feed consumption and an increase in drinking water consumption as long as chickens experience heat stress [Rangkuti et al 2018].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Chicken Temperature Control Using a Control System

Junaidi¹,

Siagian

Ritonga³

et al. 2022

JMCIE

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Chicken is one of the side dishes favored by many people in the world. Therefore, many entrepreneurs do business with chicken. This research is the result of a survey of several technical journals about the temperature of the chicken coop taken. From observations and tests carried out in the field carefully, this research was carried out to analyze the temperature. The chicken coop regulation system is carried out with the aim of preventing livestock from dying due to the surrounding temperature not being appropriate for his age. This study uses the Atmega 8535 microcontroller as the main controller, LM35 as the main controller temperature sensor in the enclosure, and IC L293D as a DC motor driver. The microcontroller will instruct DCmotor to work if the measured temperature is above the specified temperature limit and will instruct the relay to turn on or turn off the incandescent light if the measured temperature is below the specified temperature limit. By using this relay, the temperature of the chicken coop will be appropriate for anticipating disease outbreaks from the chickens.

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“…3) The energy-saving equipment of the enterprise power distribution network is still in a single operation. This has formed a situation of 'isolated islands', resulting in scattered information and low integration [1]. Such a situation is not convenient for high-level management and control.…”

Section: Introductionmentioning

confidence: 99%

Distribution network monitoring and management system based on intelligent recognition and judgement

Xue

Sun

et al. 2021

Applied Mathematics and Nonlinear Sciences

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Based on the shortcomings of the current intelligent management of distribution networks, the article designs and implements a remote intelligent detection system for live distribution networks. The article constructs and realises an algorithm based on a genetic algorithm (GA) and agent system. The algorithm is applied to energy-saving intelligent supervision of equipment in the distribution network. The simulation experiment shows that the integrated algorithm based on GA and agent system can accurately detect power quality in real time. At the same time, the algorithm can monitor the energy consumption of equipment in the distribution network under multiple disturbances.

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Optimum reactive power to improve power factor in industry using genetic algortihm

Cited by 6 publications

References 10 publications

A Genetic algorithm for the optimal design of a multistage amplifier

A Genetic algorithm for the optimal design of a multistage amplifier

Analysis of Chicken Temperature Control Using a Control System

Distribution network monitoring and management system based on intelligent recognition and judgement

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