Optimization of Thermal Power Plant Operations Using Genetic Algorithms

Main Article Content

Sapto Nisworo
Tidar University

Arnawan Hasibuan
Universitas Malikussaleh

Syafii Syafii
Universitas Andalas

Keywords

scheduling, electric power, cost

Abstract

Accurate scheduling of capacity and operating time for electricity generation is intended to be able to determine the start and end periods of electricity generation operations and produce power output that can meet load requirements. In this research, the goal to be achieved is to know the existence of power plants when to start operating and when to stop operations and to minimize operational costs by dividing the value of the power that will be generated at each power plant. Genetic algorithms are applied to thermal power plant data patterns to design a scheduling plan. The process involves combining the six power generating units to be tested into three different samples. It was found that the total power load and total cost for Sample 1 was 78,109 MW and IDR 200,285, 66.26, Sample 2 was 74,497 MW and IDR 149,774,156.41, and Sample 3 was 78,681 MW and IDR 156,297,893, respectively. 08. This shows that the cost of sample 1 compared to sample 2 decreased by 25.22%, then in sample 2 when compared to sample 3 it increased by 4.17%. The data also shows that a higher number of generations results in lower costs. Therefore, genetic algorithms produce better solutions from one generation to the next.

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Published
Nov 30, 2023
DOI https://doi.org/10.25077/jnte.v12n2.1090.2023

Article Details

How to Cite
Sapto Nisworo, Hasibuan, A., & Syafii, S. (2023). Optimization of Thermal Power Plant Operations Using Genetic Algorithms. Jurnal Nasional Teknik Elektro, 12(3), 50–55. https://doi.org/10.25077/jnte.v12n2.1090.2023
Issue
Vol 12, No 3: November 2023
Section
Electrical Power and Energy
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