Analysis load forecasting of power system using fuzzy logic and artificial neural network

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...

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Bibliographic Details
Main Authors: Ammar, Naji, Sulaiman, Marizan, Mohamad Nor, Ahmad Fateh
Format: Article
Language:English
Published: Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) 2017
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Online Access:http://eprints.uthm.edu.my/2458/1/AJ%202019%20%2824%29.pdf
http://eprints.uthm.edu.my/2458/
https://jtec.utem.edu.my/jtec/article/view/1560
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Institution: Universiti Tun Hussein Onn Malaysia
Language: English
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Summary: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.