Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : Loss minimization

Optimal Placement and Size of Distributed Generators Based on Autoadd and PSO to Improve Voltage Profile and Minimize Power Losses

Mustafa R. Nasser; Inaam I. Ali; Mohammed H. Alkhafaji

Engineering and Technology Journal, 2021, Volume 39, Issue 3A, Pages 453-464
DOI: 10.30684/etj.v39i3A.1781

This work aims to improve the voltage profile and reduce electrical network losses through optimal planning of distributed generators. A new search algorithm (Autoadd) along with the (PSO) are introduced to choose the best location and size for distributed generators. Two systems are implemented; a 33-bus test network and a 30-bus of a local community in the city of Al- Diwaniyah. At the power flow, a solution is implemented using a fixed-point iteration method within an OpenDSS environment to check the performance of both networks. Moreover, the optimal location and size of the distributed generators are determined using Autoadd and PSO methods. The Autoadd method is implemented within the OpenDSS environment, while the (PSO) method is implemented within the MATLAB-OpenDSS environment through the com-interface. The validity and effectiveness of the proposed methods are validated by comparison with the published researches. The results have proven that the fixed-point method has achieved high efficiency and accuracy in terms of analyzing the power flow, whereas the (Autoadd) algorithm has achieved a better effect in terms of improving the voltage profile and minimizing losses

Al - Kalij Sub-Station: Feeder Reconfiguration by Particle Swarm Optimization

Qais M. Alias; Rana Ali Abttan

Engineering and Technology Journal, 2011, Volume 29, Issue 12, Pages 2375-2385

This paper presents the solution approach for the optimal reconfiguration problem
in distribution networks implementing Particle Swarm Optimization (PSO)
Network reconfiguration in distribution system is changing the status of
sectionalizing switches to reduce the power loss in the system. The main objective of
network reconfiguration is to find the network topology which is having the
minimum losses during any conditions exists in the network. A network
configuration is a valid solution to the problem if it satisfies reliability, security and
other operation constraints.
Particle Swarm Optimization is a robust stochastic evolutionary computation
technique, which is based on the movement and intelligence of swarms.
A standard particle swarm optimization algorithm is adapted and used in this work.
The primary case study is a part of the Baghdad area distribution network. It consists
of four feeders and 102 buses. The algorithm validity is verified first via application
to standard systems. Results show that the standard particle swarm optimization is
suitable for off-line reconfiguration studies.