Optimization on PID and ANFIS Controller on Dual Axis Tracking for Photovoltaic Based on Firefly Algorithm

Ali, Machrus; Nurohmah, Hidayatul; Budiman, .; Suharsono, Judi; Suyono, Hadi; Muslim, Muhammad Aziz

doi:10.1109/iceeie47180.2019.8981428

Cited by 17 publications

(10 citation statements)

References 7 publications

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“…The acceleration of the rotary angle comes from the acceleration of the gear-1 angle. Moment of inertia horizontal rotary axis solar cell panel [15].…”

Section: Transfer Function Horizontal Axismentioning

confidence: 99%

Determination of the parameters of the firefly method for PID parameters in solar panel applications

Ali

Suyono²,

Muslim³

et al. 2022

Sinergi

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The optimal performance of solar panels is very important to produce maximum electrical energy. Solar panels can work optimally when equipped with a solar tracker. The solar panel tracker works by following the sun's movement. A Proportional, Integral, Derivative (PID) based control is used to optimize the performance of the solar tracker. An optimal tuning is needed to get the PID parameter. The Firefly method is an intelligent method that can be used to optimize PID parameters. Three Firefly Algorithm (FA) parameters are used in the program: Beta is used to determine firefly speed, Alpha is used for flexibility of movement, and Gamma is used for more complex constraints or problems. This Dual Axis photovoltaic tracking study uses the beta value determination, changing the Bêta value from 0.1 to 0.9. From the results of 10 models, it was found that the PID constant values were varied. On the horizontal Axis, the best results are if the Beta is given at 0.4, and the worst result is if the Beta is given at 0.8. On the vertical Axis, the best results are if the Beta is given at 0.3, and the worst result is if the Beta is given at 0.8.

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“…The acceleration of the rotary angle comes from the acceleration of the gear-1 angle. Moment of inertia horizontal rotary axis solar cell panel [15].…”

Section: Transfer Function Horizontal Axismentioning

confidence: 99%

Determination of the parameters of the firefly method for PID parameters in solar panel applications

Ali

Suyono²,

Muslim³

et al. 2022

Sinergi

Self Cite

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“…Telah banyak metode kecerdasan buatan atau Artificial Intelligent (AI) yang digunakan dalam optimasi system, diantaranya dalam sistem tenaga listrik, diantaranya adalah metode Firefly Algorithm (FA). FA sering digunakan karena konvergensi program yang lebih capat dan proses komputasi yang sangat sederhana diantaranya telah digunakan pada kontrol kendaran[1][2] [3][4], kontrol mikro hidro [5], kontrol turbin angin [6], kontrol mesin diesel [6], kontrol kecepatan motor [7][8], kontrol level air [9][10], dan kontrol traking photovoltaic [11]. MFA merupakan algoritma yang memodifikasi Metode Firefly Alghorithm yang mampu mengoptimasikan pada system photovoltaic [12] [13].…”

Section: Pendahuluanunclassified

Modifikasi Firefly Algorithm Untuk Partial Shading pada Photovoltaic

Budiman

Ali

2021

alinier

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Shadows of buildings or trees can partially cover the PV resulting in differences in solar radiation reception. Partial shading occurs when the PV module receives different solar radiation due to shadows of buildings or trees or clouds. This condition causes the output power of the PV array to decrease. Based on the PV curve, partial shading has a direct effect, so that a decrease in voltage or current causes a decrease in the output power of the PV. Because this requires a good control device. In this study, the method was compared without control (Uncontrolled), conventional PID (PID), PID tuned by Firefly Algorithm (PID-FA), and PID tuned by Modified Firefly Algorithm (PID-MFA). From the simulation results, it is found that the best voltage is obtained from the PID-MFA controller, the best voltage obtained from the PID-MFA controller is 1.2755 pu, the best current on the PID-MFA is 4,313; 3.67; 2,551 pu, and the maximum power is 3,253 pu. Thus it can be concluded that the best controller is PID-MFA. This research can later be used as a reference and other controllers are used to obtain an optimal controller.

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“…Kecerdasan buatan (Artificial Intelligence) banyak dipakai penelitian dalam menyelesaikan permasalahan optimasi system tenaga listrik, diantaranya optimasi pada pengaturan tracking photovoltaic [1], pada kontrol frekuensi mikrohydro [2][3], kecepatan putar turbin angin [4] [5], pada control frekuensi wind-diesel [6] [7], maupun optimasi kontrol level aliran air [8], maupun kontrol lainnya. Banyak penelitian yang telah membandingkan metode Imperialist Competitive Algorithms (ICA) dengan kecerdasan buatan lainnya dan ICA menghasilkan hasil yang lebih baik dari kecerdasan buatan lainnya [9][10] [11].…”

Section: Pendahuluanunclassified

Rekonfigurasi Jaringan Distribusi Radial Di Penyulang Purwoasri Berbasis Modified Imperialist Competitive Algorithms (MICA)

et al. 2020

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Radial distribution network configuration is difficult to simplify because it is very complex. This network reconfiguration is used to redesign the configuration form of the radial distribution network by opening and closing switches on the distribution network. Purwoasri feeders, Rayon Kertosono, Mojokerto area have very large losses that need to be reconfigured. The resulting power flow will produce a network power loss as a result of the configuration. The reconfiguration process will be repeated until the configuration form that produces the smallest power loss is obtained. The number of feeders and buses on the network will be difficult if done with manual calculations and requires a very long time, so solving the problem must use a computer program. Network reconfiguration using the Matlab 2013a program will analyze its power flow using the Newton Raphson method and using the artificial intelligence method, Modified Imperialist Competitive Algorithms (MICA). With this method, it was obtained before the reconfiguration of the network suffered a loss of 89,724 kWatt after the reconfiguration had a loss of 54.8299 kWatt. The results of reconfiguration can reduce losses of 0.6173 kWatt or 38.95688%.

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Optimization on PID and ANFIS Controller on Dual Axis Tracking for Photovoltaic Based on Firefly Algorithm

Cited by 17 publications

References 7 publications

Determination of the parameters of the firefly method for PID parameters in solar panel applications

Determination of the parameters of the firefly method for PID parameters in solar panel applications

Modifikasi Firefly Algorithm Untuk Partial Shading pada Photovoltaic

Rekonfigurasi Jaringan Distribusi Radial Di Penyulang Purwoasri Berbasis Modified Imperialist Competitive Algorithms (MICA)

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