Energy Efficiency in Modern Power Systems Utilizing Advanced Incremental Particle Swarm Optimization–Based OPF

Muhammad Bachtiar Nappu (), Ardiaty Arief and Willy Akbar Ajami
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Muhammad Bachtiar Nappu: Electricity Market and Power Systems Research Group, Department of Electrical Engineering, Faculty of Engineering, Hasanuddin University, Gowa 92171, Indonesia
Ardiaty Arief: Power and Energy Systems Research Group, Department of Electrical Engineering, Faculty of Engineering, Hasanuddin University, Gowa 92171, Indonesia
Willy Akbar Ajami: Electricity Market and Power Systems Research Group, Department of Electrical Engineering, Faculty of Engineering, Hasanuddin University, Gowa 92171, Indonesia

Energies, 2023, vol. 16, issue 4, 1-13

Abstract: Since the power grid grows and the necessity for higher system efficiency is due to the increasing number of renewable energy penetrations, power system operators need a fast and efficient method of operating the power system. One of the main problems in a modern power system operation that needs to be resolved is optimal power flow (OPF). OPF is an efficient generator scheduling method to meet energy demands with the aim of minimizing the total production cost of power plants while maintaining system stability, security, and reliability. This paper proposes a new method to solve OPF by using incremental particle swarm optimization (IPSO). IPSO is a new algorithm of particle swarm optimization (PSO) that modifies the PSO structure by increasing the particle size, where each particle changes its position to determine its optimal position. The advantage of IPSO is that the population increases with each iteration so that the optimization process becomes faster. The results of the research on optimal power flow for energy generation costs, system voltage stability, and losses obtained by the IPSO method are superior to the conventional PSO method.

Keywords: economic dispatch; generation cost; incremental particle swarm optimization; incremental social learning; optimal power flow; particle swarm optimization; voltage stability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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