Optimal location of a new generating unit using particle swarm optimization

2011 ◽  
Author(s):  
M. N. Suharto ◽  
M. Y. Hassan ◽  
M. P. Abdullah ◽  
M. S. Majid ◽  
F. Hussin
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Optimal Location ◽  
Swarm Optimization

Optimal Location and Size of Multiple Renewable Distributed Generation Units in Power Systems Using an Improved Version of Particle Swarm Optimization

2021 ◽  
pp. 15-27
Author(s):  
Mamdouh Kamaleldin AHMED ◽  
◽  
Mohamed Hassan OSMAN ◽  
Nikolay V. KOROVKIN ◽  
◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Power Systems ◽  
Distributed Generation ◽  
Particle Swarm ◽  
Optimal Location ◽  
Particle Swarm Algorithm ◽  
Power Losses ◽  
Negative Effects ◽  
Swarm Optimization ◽  
Distributed Generations

The penetration of renewable distributed generations (RDGs) such as wind and solar energy into conventional power systems provides many technical and environmental benefits. These benefits include enhancing power system reliability, providing a clean solution to rapidly increasing load demands, reducing power losses, and improving the voltage profile. However, installing these distributed generation (DG) units can cause negative effects if their size and location are not properly determined. Therefore, the optimal location and size of these distributed generations may be obtained to avoid these negative effects. Several conventional and artificial algorithms have been used to find the location and size of RDGs in power systems. Particle swarm optimization (PSO) is one of the most important and widely used techniques. In this paper, a new variant of particle swarm algorithm with nonlinear time varying acceleration coefficients (PSO-NTVAC) is proposed to determine the optimal location and size of multiple DG units for meshed and radial networks. The main objective is to minimize the total active power losses of the system, while satisfying several operating constraints. The proposed methodology was tested using IEEE 14-bus, 30-bus, 57-bus, 33-bus, and 69- bus systems with the change in the number of DG units from 1 to 4 DG units. The result proves that the proposed PSO-NTVAC is more efficient to solve the optimal multiple DGs allocation with minimum power loss and a high convergence rate.

Optimal Location of SVC using Particle Swarm Optimization and Voltage Stability Indexes

2016 ◽  
Vol 6 (6) ◽  
pp. 2581 ◽  
Author(s):  
M.N. Dazahra ◽  
F. Elmariami ◽  
A. Belfqih ◽  
J. Boukherouaa
Keyword(s):  
Particle Swarm Optimization ◽  
Network Model ◽  
Voltage Stability ◽  
Particle Swarm ◽  
Optimal Location ◽  
Electrical Network ◽  
Programming Algorithm ◽  
Static Var Compensator ◽  
Swarm Optimization ◽  
Stability Indexes

<p>Flexible AC transmission system are widley used in power sytems to ensure voltage stability, in virtue of their high cost the choise of the best location in electrical network is essential. The porpose of this paper is to present a new method for finding the optimal location, size and number of Static Var Compensator in order to enhace the voltage stability of electrical network. The optimal solution has been found by using the evolutionary programming algorithm, particle swarm optimization, combined with voltage stability indexes used for the estimation of the voltage collapse in power systems.The proposed algorithm has been validated by application on both simulation network model IEEE 30-Buses under different load cases and the electric network model of Casablanca region in Morocco.The results of the application have been analysed and compared in each case in order to get the optimal number of Static Var Compensator to be used.</p>

Sign in / Sign up

Export Citation Format

Share Document