OPTIMAL PLACEMENT AND SIZING OF BATTERY ENERGY STORAGE SYSTEM BY MEANS OF LOSS SENSITIVITY FACTOR
Climate change has significantly become one of the biggest challenges in the lives of modern society. To overcome the problem of climate change, one way that can be taken is to decarbonize the power system, in the form of integrating more Renewable Energy (RE) in existing power systems, and in th...
Saved in:
Main Author: | |
---|---|
Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/47887 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
id |
id-itb.:47887 |
---|---|
spelling |
id-itb.:478872020-06-23T11:53:38ZOPTIMAL PLACEMENT AND SIZING OF BATTERY ENERGY STORAGE SYSTEM BY MEANS OF LOSS SENSITIVITY FACTOR Dewanata, Claysius Indonesia Final Project optimal BESS placement, optimal BESS sizing, peak shaving, ?LSF INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/47887 Climate change has significantly become one of the biggest challenges in the lives of modern society. To overcome the problem of climate change, one way that can be taken is to decarbonize the power system, in the form of integrating more Renewable Energy (RE) in existing power systems, and in the power system that will be built. However, the use of RE in power systems brings new problems. Intermittent RE sources such as wind and solar energy are so dependent on the weather that changes in it, such as clouds and turbulence, will affect energy production. These conditions cause the RE power plant is not suitable for use in peak load conditions. An alternative to the problem is to use a Battery Energy Storage System (BESS). BESS installation must be considered carefully because the unoptimal location for BESS placement and unoptimal BESS capacity will increase the losses significantly and reduce the value of the benefits of BESS itself. This final project applies Loss Sensitivity Factor (LSF) to get the optimal BESS placement and capacity. This approach will be based on ?LSF which is defined as the difference between the average LSF value when charging and the average LSF value when discharging. By using the ?LSF method, optimal placement can be obtained which is marked by the system losses being the minimum compared to other buses. Optimal capacity can also be obtained which, when combined with the optimal placement, can further minimize the losses in the system. text |
institution |
Institut Teknologi Bandung |
building |
Institut Teknologi Bandung Library |
continent |
Asia |
country |
Indonesia Indonesia |
content_provider |
Institut Teknologi Bandung |
collection |
Digital ITB |
language |
Indonesia |
description |
Climate change has significantly become one of the biggest challenges in the lives
of modern society. To overcome the problem of climate change, one way that can
be taken is to decarbonize the power system, in the form of integrating more
Renewable Energy (RE) in existing power systems, and in the power system that
will be built. However, the use of RE in power systems brings new problems.
Intermittent RE sources such as wind and solar energy are so dependent on the
weather that changes in it, such as clouds and turbulence, will affect energy
production. These conditions cause the RE power plant is not suitable for use in
peak load conditions. An alternative to the problem is to use a Battery Energy
Storage System (BESS). BESS installation must be considered carefully because the
unoptimal location for BESS placement and unoptimal BESS capacity will increase
the losses significantly and reduce the value of the benefits of BESS itself. This final
project applies Loss Sensitivity Factor (LSF) to get the optimal BESS placement
and capacity. This approach will be based on ?LSF which is defined as the
difference between the average LSF value when charging and the average LSF
value when discharging. By using the ?LSF method, optimal placement can be
obtained which is marked by the system losses being the minimum compared to
other buses. Optimal capacity can also be obtained which, when combined with the
optimal placement, can further minimize the losses in the system.
|
format |
Final Project |
author |
Dewanata, Claysius |
spellingShingle |
Dewanata, Claysius OPTIMAL PLACEMENT AND SIZING OF BATTERY ENERGY STORAGE SYSTEM BY MEANS OF LOSS SENSITIVITY FACTOR |
author_facet |
Dewanata, Claysius |
author_sort |
Dewanata, Claysius |
title |
OPTIMAL PLACEMENT AND SIZING OF BATTERY ENERGY STORAGE SYSTEM BY MEANS OF LOSS SENSITIVITY FACTOR |
title_short |
OPTIMAL PLACEMENT AND SIZING OF BATTERY ENERGY STORAGE SYSTEM BY MEANS OF LOSS SENSITIVITY FACTOR |
title_full |
OPTIMAL PLACEMENT AND SIZING OF BATTERY ENERGY STORAGE SYSTEM BY MEANS OF LOSS SENSITIVITY FACTOR |
title_fullStr |
OPTIMAL PLACEMENT AND SIZING OF BATTERY ENERGY STORAGE SYSTEM BY MEANS OF LOSS SENSITIVITY FACTOR |
title_full_unstemmed |
OPTIMAL PLACEMENT AND SIZING OF BATTERY ENERGY STORAGE SYSTEM BY MEANS OF LOSS SENSITIVITY FACTOR |
title_sort |
optimal placement and sizing of battery energy storage system by means of loss sensitivity factor |
url |
https://digilib.itb.ac.id/gdl/view/47887 |
_version_ |
1822271568788586496 |