Optimal Capacitor Sizing for Reactive Power Optimization by Using a New Hybrid Algorithm Based on Merging of Chaotic Strategy with PSO Algorithm

Hussain, Ali Nasser; Abdullah, Ali Abdulabbas; Neda, Omar Muhammed

doi:10.36478/jeasci.2019.2112.2123

Cited by 2 publications

(2 citation statements)

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“…An individual signifies the candidate solution and every group of individuals signifies a swarm. Kennedy and Eberhart were first enhanced and developed this algorithm in 1995 [21], [22]. Each individual in the PSO algorithm has local best position (𝑃 𝑏𝑒𝑠𝑡 ), and global best position (𝐺 𝑏𝑒𝑠𝑡 ) [23].…”

Section: Pso Algorithmmentioning

confidence: 99%

Optimal distributed generation placement using artificial intelligence for improving active radial distribution system

Jumaa

Neda²,

Mhawesh

2021

Bulletin EEI

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There are several profits of distributed generator (DG) units which are believed for improving the safety of the distribution power grids. However, these profits can be maximized by ensuring optimum sizing and positioning of DG units because an arbitrary location of DG units may adversely affect and jeopardize power grids which could contribute to maximising of power loss and degradation of the voltage profile. Therefore, several approaches were suggested to ensure optimum position and size of DGs. The primary aim of this article is for establishing technique for optimum scheduling and operating of DG to lessen power loss, revamp voltage profile and overall network reliability. Artificial intelligence method called particle swarm optimization (PSO) is utilized for finding the best site and size of DG to lessen power loss and boost the voltage profile. In this paper, IEEE 33 distribution system is utilized to display applicability of PSO. The results of the PSO are compared with the results gotten by other methods in the literature. Finally, the results show that the PSO is superior than the other methods.

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Section: Pso Algorithmmentioning

confidence: 99%

Optimal distributed generation placement using artificial intelligence for improving active radial distribution system

Jumaa

Neda²,

Mhawesh

2021

Bulletin EEI

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“…In recent years, with the continuous expansion of PS scale and increasing load changes, the importance of RP OPT in PS has become increasingly prominent [1][2]. RP OPT can improve the stability of PS, reduce voltage deviation and power grid loss, and it is of great significance to the reliability, economy and environmental protection of PS [3][4].…”

Section: Introductionmentioning

confidence: 99%

Reactive Power Optimization of Power System Based on Particle Swarm Optimization Algorithm

Liu,

Wei,

2023

HSET

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With the popularization and development of the Power System (PS), the power factor and stability issues of the PS are becoming increasingly prominent. The Reactive Power (RP) in the PS has a significant impact on system stability and efficiency. Therefore, how to optimize the RP in the PS, improve power factor and stability, has become one of the research hotspots in the field of power. This paper aims to solve the problem of RP Optimization (OPT) in PS, and optimize the size and distribution of RP by using particle swarm OPT, so as to improve the stability and efficiency of PS. Through experimental testing, it was found that the Algorithm (ALG) has good performance in RP OPT problems and has great potential for application in PS OPT. The experimental results show that among these five sets of results, the value range of objective function 1 ranges from 156.75 kW^2 to 162.46 kW^2, indicating that different RP compensation capacities have different effects on the magnitude of RP loss.

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Optimal Capacitor Sizing for Reactive Power Optimization by Using a New Hybrid Algorithm Based on Merging of Chaotic Strategy with PSO Algorithm

Cited by 2 publications

References 0 publications

Optimal distributed generation placement using artificial intelligence for improving active radial distribution system

Optimal distributed generation placement using artificial intelligence for improving active radial distribution system

Reactive Power Optimization of Power System Based on Particle Swarm Optimization Algorithm

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