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All Journal Kitektro CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Jurnal Serambi Engineering Aceh International Journal of Science and Technology Jurnal Rekayasa elektrika
Suriadi Suriadi
Teknik Elektro, Fakultas Teknik, Universitas Syiah Kuala Banda Aceh Indonesia
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Other

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Metode Maximum Power Point Tracking (MPPT) dan Boost Converter Menggunakan Fuzzy Logic Controller (FLC) pada Modul Surya Teuku Murisal Asyadi; Ira Devi Sara; Suriadi Suriadi
Jurnal Rekayasa Elektrika Vol 17, No 1 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (501.142 KB) | DOI: 10.17529/jre.v17i1.17863

Abstract

Solar modules have current and voltage characteristics that are non-linear, so efforts must always be made to work at the maximum power point so that no energy is wasted. The characteristics of the solar module will change depending on the level of radiation and temperature which causes the output power of the solar module to fluctuate and become unstable. To reduce oscillations in the output power of the solar module, the Fuzzy Logic Control (FLC) method used using the boost converter. Several studies have been done to maximize the output power of solar panels, one of which is by using namely by using Maximum Power Point Tracking (MPPT). This study aims to obtain the maximum power point in a set of solar modules arranged in series and parallel through the performance of the FLC method. In tracking the maximum power point during normal operation, the fuzzy method works together with a boost converter. Fuzzy-based MPPT was tested on a solar module under several radiation and temperature conditions using Matlab / Simulink software. The Fuzzy design method shows better results compared to other methods. The results obtained show the advantages of the FLC method in terms settling time, power loss, and oscillation at the point of the operating system.
Reduksi Osilasi Daya Pada MPPT Panel Surya Dengan Metode Kombinasi PNO dan Fuzzy Suriadi Suriadi; Intan Nurul Fajri; Rizal Munadi; Mansur Gapy
Jurnal Rekayasa Elektrika Vol 15, No 2 (2019)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v15i2.13682

Abstract

Solar panels are an essential part of a system of electrical source devices that receives light energy to be processed into electrical energy with direct current (DC) output. The main problem in the use of solar panels is that the production of power in solar panels is not constant due to the temperature and solar radiation changes. This non-constant power causes the solar panel output power to fluctuate and become unstable. This output power will be used in processing using the MPPT Perturb and Observe (PNO) method to obtain the maximum solar panel receiving point. This PNO method uses two input parameters and can be applied to all types of solar panels. This study aims to reduce the oscillation of the output power of MPPT using electronic power simulations on a three-level boost converter by combining PNO and Fuzzy MPPT methods. The Fuzzy method in this study uses the Mamdani inference method, which uses two inputs and one output. The boost converter was tested using a simulation on several conditions of sunlight received by solar panels. The simulation results show that the power output from the MPPT PNO and Fuzzy methods can reduce oscillation more optimally, 78.57%. 
Analisis Kinerja Penggabungan Logika Fuzzy dan PID pada Penjejak Matahari Dua Sumbu Muhammad Nur Hasan; Yuwaldi Away; Suriadi Suriadi; Andri Novandri
Jurnal Rekayasa Elektrika Vol 19, No 1 (2023)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v19i1.15128

Abstract

Utilization of renewable energy from solar panel systems is increasingly being applied, but until now its utilization has not been maximized. The movement of the sun caused by rotation of the earth and cloudy condition should be taken into account to maximize the electrical energy in solar panels. In this study, a concept to calculate the movement of a two-axis sun tracker is proposed by using a combination of two controller methods, i.e. Proportional Integral Derivative (PID) and Fuzzy logic known as Fuzzy-PID (F-PID). To follow the movement of the sun, the LDR sensor is used as an input to light as well as output used to drive 2 units servo for x-axis and y-axis. Sun tracker that is used is based on tetrahedron geometry and uses three Light Dependent Resistor (LDR) sensors as input. Input and output components are connected to the Atmega 328P by using a combination of Fuzzy logic and PID programs (F-PID). Fuzzy logic programming is first performed on the Matlab application using Fuzzy Inference System (FIS), then converted into an Arduino-based programming language. The sun tracker movement and the voltage received by the solar panel will be stored into the SD card using a data logging module. Adjusting the sun tracker movement using the combined Fuzzy logic and PID method intends to maximize the electrical energy received by the solar panel. The results showed that the F-PID method obtained the maximum voltage of 5.3 V, a maximum current of 0.11 A, and a maximum power of 0.61 W.
Determination of Optimum Resources for the Blang Kejeren Electrical System Using PSS Sincal Application Ulil Azmi Panggabean; Suriadi Suriadi; Rakhmad Syafutra Lubis
Circuit: Jurnal Ilmiah Pendidikan Teknik Elektro Vol 8, No 1 (2024)
Publisher : PTE FTK UIN Ar-Raniry

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22373/crc.v8i1.19441

Abstract

Currently, the Customer Service Unit (ULP) of the Blang Kejeren State Power Company (PLN) uses the system of the Diesel Power Power Centre (PLTD). Sistem ini terdiri dari PLTD yang dimiliki PLN dan PLtD Lewa, serta beberapa PLTMH (Pusat Listrik Tenaga Mikro Hidro). Aim of the study is to assess the technical viability of the 20 kV ULP Blangkejeren system if supplied with the Kutacane GI and parallel with Distributed Generation (DG). This is because there is no distribution network that can connect the Blangkejeren ULP load centre to the Kutacane GI. Using the PSS Sincal Power System Analysis Application, load scenarios for power plants and distribution networks are modeled and simulated. The findings indicate that the 20kV Ulp Blangkjeren system provided by GI Kutacana, PLTMH, PLTM Lawe, and PLTD Rema is the most appropriate scenario. This situation is regarded as optimal, with a network voltage of 21.07 kV on the ULP Blangkejeren Connection Guard Bus. 
Prediksi Kecepatan Angin Jangka Menengah dengan Artificial Neural Network untuk Estimasi Daya Listrik Tenaga Angin (Studi Kasus: Kota Sabang) Abdul Malek; Suriadi Suriadi; Khairun Saddami
Jurnal Serambi Engineering Vol 8, No 3 (2023): Juli 2023
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v8i3.6010

Abstract

Indonesia, as a country at the equator, has a very large renewable energy potential that can be used as a source of electrical energy. Electricity consumption in Indonesia, especially in Aceh, continues to increase annually because of population growth and increasing economic needs. Recently, the construction of power plants has been considered to be environmentally friendly and economical. One of the efforts that can be made is the development of wind-power plants. The availability of certain wind speeds was expected. Therefore, accurate prediction data must be used as the basis for building wind power plants. To increase the accuracy of wind speed prediction by looking at the error rate in predicting the amount of wind speed generated using an Artificial Neural Network with feed-forward and feed-backward functions from the back propagation algorithm (BPNN). The results of the application using the Neural Network algorithm with a back propagation Neural Network (BPNN) to predict wind speed show that the Neural Network algorithm can predict wind speed with an error of 0.0036. In July 2021, the estimated energy demand is 81.5 KWH.
Co-Authors Abdul Malek Amirul Mukminin Asyadi, Teuku Murisal Hafidh Hafidh Hafidh Hasan Intan Nurul Fajri Ira Devi Sara Mansur Gapy Marwan Marwan Muhammad Farhan Rozi Muhammad Nur Hasan Muhammad Tadjuddin Muhammad Yanis Muna Nabilah Muzailin Affan Muzakir Zainal Noprida Sari Novandri, Andri Nurul Aulia Rakhmad Syafutra Lubis Ramdhan Halid Siregar Rizal Munadi Rizqan Maulana Saddami, Khairun Syukiryadin Syukiryadin Teuku Syaufi Hayu Ulil Azmi Panggabean Yuwaldi Away Yuwaldi Away