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Utamidewi, Dianti
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Modeling and Control of a Based Extreme Learning Machine as Distributed Setpoint for the HEPP Cascade System in a Nickel Processing Plant Sarira, Yayan Iscahyadi; Syafaruddin, Syafaruddin; Gunadin, Indar Chaerah; Utamidewi, Dianti
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.211

Abstract

The aim of this research is to model the cascade system of hydropower plants in order to predict the set point power value of each generator. The model simulates several input data variables to obtain an accurate prediction of the set point value. Various historical data are used in this study to evaluate the relationship between input and output variables. This paper presents an Extreme Learning Machine (ELM) method for modeling system models and generating set point values for each generator in a hydroelectric power plant (HEPP) cascade system in a nickel processing plant (NPP). The issue of coordination time between the production and utility departments is addressed. The research aims to use the ELM method to auto-generate setpoint values.  The MATLAB application serves as a simulator for generating the expected Extreme Learning Machine (ELM) model.  As a result, this allows for automatic changes to the set point of each generator in the cascade system. The ELM method yields a MAPE value of 13.94%, indicating accurate predictions.
Insulation Coordination System 150kV Substation and Transmission Line against Lightning Surge Interference in a Nickel Smelting Plant Samad, Busyairi; Manjang, Salama; Kitta, Ikhlas; Utamidewi, Dianti; Amri, Arham
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.248

Abstract

Related with the increasing demand for electrical energy at nickel smelting plant, a highly reliable electric power system is needed to be able to supply important loads such as electric furnaces and auxiliary equipment. The electric power system delivers electrical power to consumers through substations and transmission lines. The distribution of electrical power through high voltage overhead lines (SUTT) sometimes goes through areas with a high enough lightning strike potential that it can cause sudden blackouts due to direct strikes and back flashovers. Therefore, it is necessary to insulation coordination of the substation and transmission line to avoid damage to electrical equipment. This research aims to determine the magnitude of the voltage due to lightning strikes on GSW and Conductor by varying the location of the lightning protection system on 150 kV overhead line which is useful for obtaining isolation coordination systems on transmission lines and substations in the nickel smelting industry. which is useful for obtaining isolation coordination systems on transmission lines and substations in the nickel smelting plant. This research was carried out by selecting lightning strikes in the current strike of 100 kA on transmission line with simulation use device ATP draw software. This research showed that the installation of lightning protection equipment on high-voltage overhead lines and transmission towers resulted in a significant voltage drop due to lightning strikes lowering under BIL existing insulators.
Co-Authors Amri, Arham Gunadin, Indar Chaerah Ikhlas Kitta Salama Manjang Samad, Busyairi Sarira, Yayan Iscahyadi Syafaruddin Syafaruddin