Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG)

Network reconfiguration which is constrained non linear optimization problem has been solved for loss minimization, load balancing, etc. for last two decades using various heuristic search evolutionary algorithms like binary particle swarm optimization, neuro-fuzzy techniques, etc. The contribution...

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Main Authors: R. Rajaram, K. Sathish Kumar, N. Rajasekar
Format: Article
Language:English
Published: Elsevier 2015-11-01
Series:Energy Reports
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484715000165
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spelling doaj-1513657a16b0425ca2d6ae9337289df92020-11-24T23:59:43ZengElsevierEnergy Reports2352-48472015-11-011C11612210.1016/j.egyr.2015.03.002Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG)R. RajaramK. Sathish KumarN. RajasekarNetwork reconfiguration which is constrained non linear optimization problem has been solved for loss minimization, load balancing, etc. for last two decades using various heuristic search evolutionary algorithms like binary particle swarm optimization, neuro-fuzzy techniques, etc. The contribution of this paper lies in considering distributed generation which are smaller power sources like solar photovoltaic cells or wind turbines connected in the customer roof top. This new connection in the radial network has made unidirectional current flow to become bidirectional there by increasing the efficiency but sometimes reducing stability of the system. Modified plant growth simulation algorithm has been applied here successfully to minimize real power loss because it does not require barrier factors or cross over rates because the objectives and constraints are dealt separately. The main advantage of this algorithm is continuous guiding search along with changing objective function because power from distributed generation is continuously varying so this can be applied for real time applications with required modifications. This algorithm here is tested for a standard 33 bus radial distribution system for loss minimization and test results here shows that this algorithm is efficient and suitable for real time applications.http://www.sciencedirect.com/science/article/pii/S2352484715000165Radial distribution systemDistributed generationDistribution generation unitDistribution network reconfigurationModified plant growth simulation algorithm
collection DOAJ
language English
format Article
sources DOAJ
author R. Rajaram
K. Sathish Kumar
N. Rajasekar
spellingShingle R. Rajaram
K. Sathish Kumar
N. Rajasekar
Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG)
Energy Reports
Radial distribution system
Distributed generation
Distribution generation unit
Distribution network reconfiguration
Modified plant growth simulation algorithm
author_facet R. Rajaram
K. Sathish Kumar
N. Rajasekar
author_sort R. Rajaram
title Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG)
title_short Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG)
title_full Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG)
title_fullStr Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG)
title_full_unstemmed Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG)
title_sort power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with distributed generation (dg)
publisher Elsevier
series Energy Reports
issn 2352-4847
publishDate 2015-11-01
description Network reconfiguration which is constrained non linear optimization problem has been solved for loss minimization, load balancing, etc. for last two decades using various heuristic search evolutionary algorithms like binary particle swarm optimization, neuro-fuzzy techniques, etc. The contribution of this paper lies in considering distributed generation which are smaller power sources like solar photovoltaic cells or wind turbines connected in the customer roof top. This new connection in the radial network has made unidirectional current flow to become bidirectional there by increasing the efficiency but sometimes reducing stability of the system. Modified plant growth simulation algorithm has been applied here successfully to minimize real power loss because it does not require barrier factors or cross over rates because the objectives and constraints are dealt separately. The main advantage of this algorithm is continuous guiding search along with changing objective function because power from distributed generation is continuously varying so this can be applied for real time applications with required modifications. This algorithm here is tested for a standard 33 bus radial distribution system for loss minimization and test results here shows that this algorithm is efficient and suitable for real time applications.
topic Radial distribution system
Distributed generation
Distribution generation unit
Distribution network reconfiguration
Modified plant growth simulation algorithm
url http://www.sciencedirect.com/science/article/pii/S2352484715000165
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