Logo

Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation

Mahesh, K. and Nallagownden, P. and Elamvazuthi, I. (2016) Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation. Energies, 9 (12).

Full text not available from this repository.

Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. The distributed generation consists of single and multiple numbers of active power DG, reactive power DG and simultaneous placement of active-reactive power DG. The optimization problem considers two multi-objective functions, i.e., power loss reduction and voltage stability improvements with voltage profile and power balance as constraints. First, the numerical output results of objective functions are obtained in the Pareto-optimal set. Later, fuzzy decision model is engendered for final selection of the compromised solution. The proposed method is employed and tested on standard IEEE 33 bus systems. Moreover, the results of proposed method are validated with other optimization algorithms as reported by others in the literature. The overall outcome shows that the proposed method for optimal placement and sizing gives higher capability and effectiveness to the final solution. The study also reveals that simultaneous placement of active-reactive power DG reduces more power losses, increases voltage stability and voltage profile of the system. © 2016 by the authors; licensee MDPI.

Item Type:Article
Impact Factor:cited By 34
Uncontrolled Keywords:Distributed power generation; Electric losses; Multiobjective optimization; Pareto principle; Reactive power; Screening; System stability; Voltage control, Distribution systems; Multi objective particle swarm optimization; Non-dominated Sorting; Placement and sizing; Power loss reduction, Particle swarm optimization (PSO)
ID Code:25305
Deposited By: Ms Sharifah Fahimah Saiyed Yeop
Deposited On:27 Aug 2021 12:57
Last Modified:27 Aug 2021 12:57

Repository Staff Only: item control page