An improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic system
In restructured power systems, transmission congestion is an imperative issue. Establishment of solar photovoltaic system at appropriate areas is likely to relieve congestion in transmission lines in the restructured power systems. Congestion management technique by utilizing solar photovoltaic sour...
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2020-08-01
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Series: | Measurement + Control |
Online Access: | https://doi.org/10.1177/0020294020914930 |
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doaj-d91e8d7541d84e9d81e8a472974c06e12020-11-25T04:04:33ZengSAGE PublishingMeasurement + Control0020-29402020-08-015310.1177/0020294020914930An improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic systemS T Suganthi0D Devaraj1 Department of Computer Engineering, Lebanese French University, Erbil, Iraq Department of Electrical & Electronics Engineering, Kalasalingam University, Krishnankoil, IndiaIn restructured power systems, transmission congestion is an imperative issue. Establishment of solar photovoltaic system at appropriate areas is likely to relieve congestion in transmission lines in the restructured power systems. Congestion management technique by utilizing solar photovoltaic sources, using an improved teaching learning–based optimization, is investigated in this article. Bus sensitivity factors which have the direct influence on the congested lines are utilized to locate the solar photovoltaic sources at appropriate areas. Congestion management is figured as an optimization problem with a goal of limiting the congestion management price utilizing the improved teaching learning–based optimization approach, which espouses the self-driven learning principle. IEEE-30 bus test system is simulated and tested in MATLAB environment so as to demonstrate the viability of the suggested methodology than different methodologies.https://doi.org/10.1177/0020294020914930 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
S T Suganthi D Devaraj |
spellingShingle |
S T Suganthi D Devaraj An improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic system Measurement + Control |
author_facet |
S T Suganthi D Devaraj |
author_sort |
S T Suganthi |
title |
An improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic system |
title_short |
An improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic system |
title_full |
An improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic system |
title_fullStr |
An improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic system |
title_full_unstemmed |
An improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic system |
title_sort |
improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic system |
publisher |
SAGE Publishing |
series |
Measurement + Control |
issn |
0020-2940 |
publishDate |
2020-08-01 |
description |
In restructured power systems, transmission congestion is an imperative issue. Establishment of solar photovoltaic system at appropriate areas is likely to relieve congestion in transmission lines in the restructured power systems. Congestion management technique by utilizing solar photovoltaic sources, using an improved teaching learning–based optimization, is investigated in this article. Bus sensitivity factors which have the direct influence on the congested lines are utilized to locate the solar photovoltaic sources at appropriate areas. Congestion management is figured as an optimization problem with a goal of limiting the congestion management price utilizing the improved teaching learning–based optimization approach, which espouses the self-driven learning principle. IEEE-30 bus test system is simulated and tested in MATLAB environment so as to demonstrate the viability of the suggested methodology than different methodologies. |
url |
https://doi.org/10.1177/0020294020914930 |
work_keys_str_mv |
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