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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Hassan, Elia Erwani
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Computer Science & IT Engineering

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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.
Co-Authors Bahaman, Nazrulazhar Bin Hashim, Mohd Ruzaini Mohamad Fani Sulaima, Mohamad Fani Noor, Hanan Izzati Mohd