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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Noor Hasliza Abdul Rahman
Universiti Teknologi MARA
Electrical & Electronics Engineering

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Integration of LED-based lighting in academic buildings for energy efficiency considerations Mohamad Zhafran Hussin; Saiful Firdaus Abdul Shukor; Nor Diyana Md Sin; Yusrina Yusof; Muhammad Zairil Muhammad Nor; Noor Hasliza Abdul Rahman
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2513

Abstract

This paper presents an assessment by integration of LED T8 tube lamps in academic buildings for energy efficiency considerations. The proposed project was implemented in conjunction with a national mission, national energy efficiency action plan (NEEAP) for 10-year implementation period of 2016-2025 in reducing allocation on subsidies for efficient expenditure towards energy-saving measures. A case of study in a real environment at one of the UiTM’s buildings as a target task area has been tested by replacing a LED lighting technology in consideration of current operating costs and power factor performances. From the results, LED T8 tubes have shown a better power factor of 0.89 compared to fluorescent lamps with about 0.61 and primarily driven by economic benefits in terms of cost savings of up to 50% with return-on-investment (ROI) 6 months after installation. By integrating this technology, nearly 50% of the total energy consumption in indoor lighting system could be significantly saved, thus reducing the total cost of electricity bills in the future within the target area.
Short term forecasting of electrical consumption using a neural network: joint approximate diagonal eigenvalue Mashitah Mohd Hussain; Zuhaina Zakaria; Nofri Yenita Dahlan; Nur Iqtiyani Ilham; Zhafran Hussin; Noor Hasliza Abdul Rahman; Md Azwan Md Yasin
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp56-66

Abstract

This article aims to estimate the load profiling of electricity that provides information on the electrical load demand. In achieving this research implemented the neural network algorithm of joint approximate diagonalisation of eigen-matrices (JADE) to describe the load profile pattern for each point. Nowadays, utility providers claim that natural sources are used to generate power by rising consumer demands for energy. However, occasionally utility workers need to know the demand at certain location, corresponding to maintenance issues or for any shutdown area involved. A distribution pattern based on the data can be predicted based on the incoming data profile without having detailed information of certain load bus, the concept of derivatives was relevant to forecast the types of distribution data. The model was constructed with load profile information based on three different locations, and the concept of derivative was recognized, including the type of incoming data. Historical data were captured from a selected location in Malaysia that was proposed to train the JADE algorithm from three different empirical distributions of consumers, recording every 15 minutes per day. The results were analyzed based on the error measurement and compared with the real specific load distribution feeder information of needed profiles.
Co-Authors Mashitah Mohd Hussain Md Azwan Md Yasin Mohamad Zhafran Hussin Muhammad Zairil Muhammad Nor Nofri Yenita Dahlan Nor Diyana Md Sin Nur Iqtiyani Ilham Saiful Firdaus Abdul Shukor Yusrina Yusof Zhafran Hussin Zuhaina Zakaria