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

• 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
• Subjects: TK3001-3521 Distribution or transmission of electric power
• 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
• Institution: Universiti Tun Hussein Onn Malaysia

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.