Analysis Load Forecasting of Power System Using of Fuzzy Logic and Artificial Neural Network

Authors

  • Naji Ammar Higher Institute for Water Technology, Agelat, Libya.
  • Marizan Sulaiman Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, Melaka, Malaysia.
  • Ahmad Fateh Mohamad Nor Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, Melaka, Malaysia.

Keywords:

ANFIS, Artificial Neural Networks (ANN), Fuzzy Logic (FL), Load Forecasting,

Abstract

Load forecasting is a vital element in the energy management of function and execution purpose throughout the energy power system. Power systems problems are complicated to solve because power systems are huge complex graphically widely distributed and are influenced by many unexpected events. This paper presents the analysis of load forecasting using fuzzy logic (FL), artificial neural network (ANN) and ANFIS. These techniques are utilized for both short term and long-term load forecasting. ANN and ANFIS are used to improve the results obtained through the FL. It also studied the effects of humidity, temperature and previous load on Load Forecasting. The simulation is done by the Simulink environment of MATLAB software.

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Published

2017-09-29

How to Cite

Ammar, N., Sulaiman, M., & Mohamad Nor, A. F. (2017). Analysis Load Forecasting of Power System Using of Fuzzy Logic and Artificial Neural Network. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(3), 181–192. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1560

Issue

Vol. 9 No. 3: July - September 2017

Section

Articles

License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)