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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences
Mohamad Fani Sulaima, Mohamad Fani
Universiti Teknikal Malaysia Melaka
Computer Science & IT Earth & Planetary Sciences Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Optimal economic environmental power dispatch by using artificial bee colony algorithm Hassan, Elia Erwani; Noor, Hanan Izzati Mohd; Bin Hashim, Mohd Ruzaini; Sulaima, Mohamad Fani; Bahaman, Nazrulazhar
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp1469-1478

Abstract

Today, most power plants worldwide use fossil fuels such as natural gas, coal, and oil as the primary resource for energy reproduction primarily. The new term for economic environmental power dispatch (EEPD) problems is on the minimum total cost of the generator and fossil fuel emissions to address atmosphere pollution. Thus, the significant objective functions are identified to minimize the cost of generation, most minor emission pollutants, and lowest system losses individually.  As an alternative, an Artificial Bee Colony (ABC) swarming algorithm is applied to solve the EEPD problem separately in the power systems on both standard IEEE 26 bus system and IEEE 57 bus system using a MATLAB programming environment. The performance of the introduced algorithm is measured based on simple mathematical analysis such as a simple deviation and its percentage from the obtained results. From the mathematical measurement, the ABC algorithm showed an improvement on each identified single objective function as compared with the gradient approach of using the Newton Raphson method in a short computational time.
Evaluation of the time-of-use tariff responsiveness for plug-in electric vehicle home charging in Malaysia Baharin, Nurliyana; Sulaima, Mohamad Fani; Dahlan, Nofri Yenita; Mokhlis, Hazlie
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp769-776

Abstract

Plug-in electric vehicles (PEVS) have become increasingly popular as a viable transportation option as owners can charge them at home. This will add much energy to the house if the users charge their PEVs at home. The PEV charging load will lead to extra energy demand on the distribution network, and the users will need to pay more for electricity if they use the current domestic tariff in Malaysia. This research aims to analyze the PEV charging costs using time-of-use (ToU) tariffs with different time segmentations and price elasticity. The effect of four residential load profile patterns has also been investigated in Malaysia as a case study. Four PEV charging scenarios were created, and the charging times were set according to Malaysian driving styles, with charging times starting at 6 PM, 10 PM, and 9 AM. The PEV and electric vehicle supply equipment (EVSE) are set to be homogeneous, and the EV was assumed to have a minimum state-of-charge of 20%. The main contribution of this paper is the selection of the ToU tariff segmentation, where the structure of the smallest time segmentation gave the lowest electricity bill per month compared to the Tenaga Malaysia Berhad (TNB) domestic tariff.
Co-Authors Bahaman, Nazrulazhar Baharin, Nurliyana Bin Hashim, Mohd Ruzaini Dahlan, Nofri Yenita Hassan, Elia Erwani Mokhlis, Hazlie Noor, Hanan Izzati Mohd