Peak Load Prediction Using Fuzzy Logic For The 150 kV Sulselrabar System

Prediction of electrical load on 150 kV Sulselrabar electrical system, analyzed using approach at night peak load using Fuzzy Logic based intelligent method. The peak load characteristics are certainly different from the load in normal time, therefore a special approach is needed to predict the peak...

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Main Authors: Muhammad Ruswandi Djalal, Andareas Pangkung, Sonong Sonong, Apollo Apollo
Format: Article
Language:English
Published: University of Brawijaya 2018-07-01
Series:JITeCS (Journal of Information Technology and Computer Science)
Online Access:http://jitecs.ub.ac.id/index.php/jitecs/article/view/39
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spelling doaj-1edb51b3a3ae42c7b92d5197904b797d2020-11-24T22:08:17ZengUniversity of BrawijayaJITeCS (Journal of Information Technology and Computer Science)2540-94332540-98242018-07-0131495910.25126/jitecs.2018313932Peak Load Prediction Using Fuzzy Logic For The 150 kV Sulselrabar SystemMuhammad Ruswandi Djalal0Andareas Pangkung1Sonong Sonong2Apollo Apollo3State Polytechnic of Ujung PandangState Polytechnic of Ujung PandangState Polytechnic of Ujung PandangState Polytechnic of Ujung PandangPrediction of electrical load on 150 kV Sulselrabar electrical system, analyzed using approach at night peak load using Fuzzy Logic based intelligent method. The peak load characteristics are certainly different from the load in normal time, therefore a special approach is needed to predict the peak night load. As input data will be used data of night peak load in 2010 until 2015, on the same day and date, each 4 days before day-H or day date which will be predicted load. For the data processing stage is divided into several stages, namely pre-processing, processing, and post-processing. The load data processing follows several procedures, ie computing WDmax, LDmax, TLDmax and VLDmax each year. Data processing is processed using excel software and then using Matlab software to run Fuzzy Logic. From the analysis results obtained, Error Prediction The peak evening load is very small that is equal to -0.070033687%. As comparison data used actual day-H data is April 2016. The graph of analysis result also shown in this paper. Keywords– Fuzzy Logic Control, Load Forecasting, Error, VLDmaxhttp://jitecs.ub.ac.id/index.php/jitecs/article/view/39
collection DOAJ
language English
format Article
sources DOAJ
author Muhammad Ruswandi Djalal
Andareas Pangkung
Sonong Sonong
Apollo Apollo
spellingShingle Muhammad Ruswandi Djalal
Andareas Pangkung
Sonong Sonong
Apollo Apollo
Peak Load Prediction Using Fuzzy Logic For The 150 kV Sulselrabar System
JITeCS (Journal of Information Technology and Computer Science)
author_facet Muhammad Ruswandi Djalal
Andareas Pangkung
Sonong Sonong
Apollo Apollo
author_sort Muhammad Ruswandi Djalal
title Peak Load Prediction Using Fuzzy Logic For The 150 kV Sulselrabar System
title_short Peak Load Prediction Using Fuzzy Logic For The 150 kV Sulselrabar System
title_full Peak Load Prediction Using Fuzzy Logic For The 150 kV Sulselrabar System
title_fullStr Peak Load Prediction Using Fuzzy Logic For The 150 kV Sulselrabar System
title_full_unstemmed Peak Load Prediction Using Fuzzy Logic For The 150 kV Sulselrabar System
title_sort peak load prediction using fuzzy logic for the 150 kv sulselrabar system
publisher University of Brawijaya
series JITeCS (Journal of Information Technology and Computer Science)
issn 2540-9433
2540-9824
publishDate 2018-07-01
description Prediction of electrical load on 150 kV Sulselrabar electrical system, analyzed using approach at night peak load using Fuzzy Logic based intelligent method. The peak load characteristics are certainly different from the load in normal time, therefore a special approach is needed to predict the peak night load. As input data will be used data of night peak load in 2010 until 2015, on the same day and date, each 4 days before day-H or day date which will be predicted load. For the data processing stage is divided into several stages, namely pre-processing, processing, and post-processing. The load data processing follows several procedures, ie computing WDmax, LDmax, TLDmax and VLDmax each year. Data processing is processed using excel software and then using Matlab software to run Fuzzy Logic. From the analysis results obtained, Error Prediction The peak evening load is very small that is equal to -0.070033687%. As comparison data used actual day-H data is April 2016. The graph of analysis result also shown in this paper. Keywords– Fuzzy Logic Control, Load Forecasting, Error, VLDmax
url http://jitecs.ub.ac.id/index.php/jitecs/article/view/39
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AT sonongsonong peakloadpredictionusingfuzzylogicforthe150kvsulselrabarsystem
AT apolloapollo peakloadpredictionusingfuzzylogicforthe150kvsulselrabarsystem
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