Optimal location and sizing determination of Distributed Generation and DSTATCOM using Particle Swarm Optimization algorithm

2014 ◽  
Vol 62 ◽  
pp. 562-570 ◽  
Author(s):  
S. Devi ◽  
M. Geethanjali
Keyword(s):  
Particle Swarm Optimization ◽  
Distributed Generation ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Optimal Location ◽  
Swarm Optimization

Cloud Adapt Particle Swarm Optimization Algorithm for Distribution Network Planning with Distributed Generation

2013 ◽  
Vol 427-429 ◽  
pp. 1136-1140 ◽  
Author(s):  
Bu Quan Xu ◽  
Li Chen Zhang ◽  
Bu Zhen Xu
Keyword(s):  
Particle Swarm Optimization ◽  
Distributed Generation ◽  
Optimization Algorithm ◽  
Distribution Systems ◽  
Particle Swarm Optimization Algorithm ◽  
Cloud Model ◽  
Particle Swarm ◽  
Value Assessment ◽  
General Group ◽  
Swarm Optimization

Distributed Generation (DG) can be used to improve power quality, power supply reliability and reduce network loss et. Meanwhile Particle Swarm Optimization algorithm (PSO) is easy to fall into the local minimum. In this paper we propose a Cloud Adaptive Particle Swarm Optimization algorithm (CAPSO) to optimize the site and size of DG based on cloud model which has a tendency and randomness property. Judged by two dynamic value assessment, particle belongs to which group, excellent, general and poor. The inertia weight in general group is adaptively varied depending on X-conditional cloud generation. Taking the minimum network loss as the objective function, simulation on the IEEE 33BUS distribution systems to validate the methodology. Analysis and simulations indicate that it has good convergence speed and exactness.

scholarly journals The Siting and Sizing Problem of Distributed Generation Based on a Novel Fractional Particle Swarm Optimization Algorithm

2021 ◽  
Vol 257 ◽  
pp. 01036
Author(s):  
Fengming Zhang ◽  
Lingyan Que ◽  
Xinxin Zhang ◽  
Fumian Wang ◽  
Bing Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Distributed Generation ◽  
Optimization Algorithm ◽  
Capacity Planning ◽  
Large Scale ◽  
Particle Swarm Optimization Algorithm ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Environmental Benefits ◽  
Swarm Optimization

Large-scale distributed generation grid-connection brings huge economic and environmental benefits, but also threatens the stability of the grid. To make the grid consume a higher proportion of distributed generation, it is necessary to optimize the location and capacity of the distributed generation connected to the grid. Firstly, the uncertainty analysis model of wind speed, illumination intensity, and load of grid is established. Secondly, a distributed generation location and capacity planning model with the lowest annual comprehensive cost as the objective function is constructed. Then, a novel fractional particle swarm optimization algorithm is proposed, and the performance of the algorithm on complex optimization problems is tested. Finally, the simulation results of the IEEE 33-bus system example verify the rationality of the established model and the effectiveness of the proposed algorithm.

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