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

Authors

  • Muhammad Ruswandi Djalal State Polytechnic of Ujung Pandang
  • Andareas Pangkung State Polytechnic of Ujung Pandang
  • Sonong Sonong State Polytechnic of Ujung Pandang
  • Apollo Apollo State Polytechnic of Ujung Pandang

DOI:

https://doi.org/10.25126/jitecs.20183139

Abstract

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

Author Biographies

Muhammad Ruswandi Djalal, State Polytechnic of Ujung Pandang

Department of Energy Engineering

Andareas Pangkung, State Polytechnic of Ujung Pandang

Department of Energy Engineering

Sonong Sonong, State Polytechnic of Ujung Pandang

Department of Energy Engineering

Apollo Apollo, State Polytechnic of Ujung Pandang

Department of Energy Engineering

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Published

2018-07-30

How to Cite

Djalal, M. R., Pangkung, A., Sonong, S., & Apollo, A. (2018). Peak Load Prediction Using Fuzzy Logic For The 150 kV Sulselrabar System. Journal of Information Technology and Computer Science, 3(1), 49–59. https://doi.org/10.25126/jitecs.20183139

Issue

Vol. 3 No. 1: June 2018

Section

Articles

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