Optimum distributed generation placement with voltage sag effect minimization

► A new optimal distributed generation placement algorithm is proposed. ► Optimal number, sizes and locations of the DGs are determined. ► Technical factors like loss, voltage sag problem are minimized. ► The percentage savings are optimized. The present paper proposes a new formulation for the opti...

Full description

Saved in:
Bibliographic Details
Published in:Energy conversion and management Vol. 53; no. 1; pp. 163 - 174
Main Authors: Biswas, Soma, Goswami, Swapan Kumar, Chatterjee, Amitava
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 2012
Elsevier
Subjects:
Algorithms
Applied sciences
Buses (vehicles)
case studies
Distributed generation (DG)
Electric potential
electric power
Energy
Exact sciences and technology
Genetic algorithm
Minimization
Optimal placement
Optimization
Placement
Sag
system optimization
Voltage
Voltage sag
Genetic algorithm
Voltage sag
Distributed generation (DG)
Optimal placement
ISSN:0196-8904, 1879-2227
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:► A new optimal distributed generation placement algorithm is proposed. ► Optimal number, sizes and locations of the DGs are determined. ► Technical factors like loss, voltage sag problem are minimized. ► The percentage savings are optimized. The present paper proposes a new formulation for the optimum distributed generator (DG) placement problem which considers a hybrid combination of technical factors, like minimization of the line loss, reduction in the voltage sag problem, etc., and economical factors, like installation and maintenance cost of the DGs. The new formulation proposed is inspired by the idea that the optimum placement of the DGs can help in reducing and mitigating voltage dips in low voltage distribution networks. The problem is configured as a multi-objective, constrained optimization problem, where the optimal number of DGs, along with their sizes and bus locations, are simultaneously obtained. This problem has been solved using genetic algorithm, a traditionally popular stochastic optimization algorithm. A few benchmark systems radial and networked (like 34-bus radial distribution system, 30 bus loop distribution system and IEEE 14 bus system) are considered as the case study where the effectiveness of the proposed algorithm is aptly demonstrated.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2011.08.020