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All Journal Bulletin of Electrical Engineering and Informatics
Norazhar Abu Bakar
Universiti Teknikal Malaysia Melaka
Electrical & Electronics Engineering

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Laboratory prediction energy control system based on artificial intelligence network Desmira Desmira; Norazhar Abu Bakar; Mohd Ruzaini Hashim; Romi Wiryadinata; Mustofa Abi Hamid
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.1821

Abstract

The use of electrical energy increases globally every year. The laboratory prediction energy control system (LPECS) predicted energy demand. This research was conducted in the Electrical Engineering Vocational Education laboratory by comparing the artificial neural fuzzy system (ANFIS) with the fuzzy logic. The comparison of methods aimed to determine their reliability in the energy demand prediction systems. The results showed that the minimum value of the target data using the conventional method (actual data) was 44.42%. Meanwhile, the prediction data using the ANFIS method was 44.33%, and the prediction data using the fuzzy method was 59.31%. The maximum value of the conventional ways (actual data) of ANFIS and fuzzy was similar by 77.59%. The RMSE ANFIS value was 0.1355%, the mean absolute percentage error (MAPE) was 0.2791%, and the fuzzy logic was 0.1986%. Thus, the ANFIS is applicable to determine the minimum and maximum values. Meanwhile, fuzzy can only show the maximum value but cannot reach the minimum value properly.
Comparative study of moisture treatment techniques for mineral insulating oil Imran Sutan Chairul; Sharin Ab Ghani; Norazhar Abu Bakar; Mohd Shahril Ahmad Khiar; Nor Hidayah Rahim; Mohamad Nazri Mohamad Din
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5927

Abstract

The presence of moisture is one of the factors that promote degradation of transformer insulating oils and deterioration of cellulose insulation materials in oil-immersed power transformers, which affect the lifespan of the transformers. Realizing the importance of moisture in transformer insulating oils, this study compares the effectiveness of three moisture treatment techniques nitrogen bubbling technique (NBT), molecular sieve technique (MST), and vacuum oven technique (VOT)) for mineral oil (MO). The moisture content and AC breakdown voltage of the MO samples before and after moisture treatment were measured using Karl Fischer coulometric titrator and portable oil tester, respectively, in accordance with the American Society for Testing and Materials (ASTM) D1533 and ASTM D1816 standards. The results showed that NBT is the best moisture treatment technique for the MO, where the NBT reduced 80.79% of moisture present in the oil, followed by MST and VOT, which reduced 72.87 and 42.28% of moisture, respectively. The results also showed that the AC breakdown voltage of the MO samples after moisture treatment was improved owing to the reduction in moisture content.
Co-Authors Desmira Desmira Imran Sutan Chairul Mohamad Nazri Mohamad Din Mohd Ruzaini Hashim Mohd Shahril Ahmad Khiar Mustofa Abi Hamid Nor Hidayah Rahim romi wiryadinata Sharin Ab Ghani