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Optimal Placement of Capacitors in Radial Distribution Grids via Enhanced Modified Particle Swarm Optimization
by
Tahir, Muhammad Junaid
, Rahmat, Mohd Khairil
, Rasheed, Muhammad Babar
in
annual net saving maximization
/ Cost control
/ Genetic algorithms
/ Heuristic
/ loss sensitivity factor
/ Methods
/ modified particle swarm optimization
/ Nominations
/ novel inertia term
/ optimal placement and sizing of capacitors
/ Optimization algorithms
/ Optimization techniques
/ Performance evaluation
/ radial distribution grids
/ Systems stability
2022
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Optimal Placement of Capacitors in Radial Distribution Grids via Enhanced Modified Particle Swarm Optimization
by
Tahir, Muhammad Junaid
, Rahmat, Mohd Khairil
, Rasheed, Muhammad Babar
in
annual net saving maximization
/ Cost control
/ Genetic algorithms
/ Heuristic
/ loss sensitivity factor
/ Methods
/ modified particle swarm optimization
/ Nominations
/ novel inertia term
/ optimal placement and sizing of capacitors
/ Optimization algorithms
/ Optimization techniques
/ Performance evaluation
/ radial distribution grids
/ Systems stability
2022
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Optimal Placement of Capacitors in Radial Distribution Grids via Enhanced Modified Particle Swarm Optimization
by
Tahir, Muhammad Junaid
, Rahmat, Mohd Khairil
, Rasheed, Muhammad Babar
in
annual net saving maximization
/ Cost control
/ Genetic algorithms
/ Heuristic
/ loss sensitivity factor
/ Methods
/ modified particle swarm optimization
/ Nominations
/ novel inertia term
/ optimal placement and sizing of capacitors
/ Optimization algorithms
/ Optimization techniques
/ Performance evaluation
/ radial distribution grids
/ Systems stability
2022
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Optimal Placement of Capacitors in Radial Distribution Grids via Enhanced Modified Particle Swarm Optimization
Journal Article
Optimal Placement of Capacitors in Radial Distribution Grids via Enhanced Modified Particle Swarm Optimization
2022
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Overview
This paper presents the integration of shunt capacitors in the radial distribution grids (RDG) with constant and time-varying load consideration for the reduction of power losses and total annual cost, which turns to enhance the voltage profile and annual net savings. To gather the stated goals, three objective functions are formulated with system constraints. To solve this identified problem, a novel optimization technique based on the modification of particle swarm optimization is proposed. The solution methodology is divided into two phases. In phase one, potential candidate buses are nominated using the loss sensitivity factor method and in phase two the proposed technique first selects the optimal buses for the capacitor placement among the potential buses then it decides the optimal sizing of the capacitors as well. To demonstrate the performance in terms of efficiency and strength, the proposed technique is tested on IEEE 15, 33, and 69 bus system for the optimal placement and sizing of capacitors (OPSC) problem. The results are achieved in terms of annual net savings for 15 bus (47.66%case−1, 32.76%case−2, 26.46%case−3), 33 bus (33.09% case−1, 27.06%case−2, 24.15%case−3), and 69 bus (34.51% case−1, 29.43%case−2, 25.83%case−3) which are comparable to other state of the art methods, and it also indicates the success of the proposed technique.
Publisher
MDPI AG
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