Efficient charging/discharging algorithm for battery storage system
Batteries typically have a fixed amount of charge and discharge cycle before they come to the end of their useful lifespan. In order to maintain and maximize a battery’s lifespan, the battery has to go through a planned sequence of charging and discharging cycle to avoid overcharge or deep discharge...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
2015
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/64629 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-64629 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-646292023-07-07T17:47:07Z Efficient charging/discharging algorithm for battery storage system Chow, Tze Hui Gooi Hoay Beng School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries Batteries typically have a fixed amount of charge and discharge cycle before they come to the end of their useful lifespan. In order to maintain and maximize a battery’s lifespan, the battery has to go through a planned sequence of charging and discharging cycle to avoid overcharge or deep discharge. An important parameter that must be estimated is the state of charge (SOC), as there is no direct measurement available, it is very important to carry out an accurate method in estimating the SOC level of the battery. Failure to estimate the SOC precisely may affect the performance and the lifetime of the battery. This report discusses various techniques to estimate the SOC of the battery such as open-circuit voltage (OCV) method, coulomb counting method and extended Kalman filter (EKF) algorithm. Next, an efficient charging or discharging algorithm is designed by using LabVIEW software to maintain the desired SOC level automatically. This algorithm uses the state machine design pattern which is able to execute a network of decision-making algorithm. Then, a battery management system (BMS) is able to decide when to charge or discharge the battery energy storage system (BESS) based on the SOC level and power demand by the microgrid. Lastly, three case studies with implementation of the algorithm are discussed. Bachelor of Engineering 2015-05-29T02:07:18Z 2015-05-29T02:07:18Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/64629 en Nanyang Technological University 62 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries |
spellingShingle |
DRNTU::Engineering::Electrical and electronic engineering::Electric power::Auxiliaries, applications and electric industries Chow, Tze Hui Efficient charging/discharging algorithm for battery storage system |
description |
Batteries typically have a fixed amount of charge and discharge cycle before they come to the end of their useful lifespan. In order to maintain and maximize a battery’s lifespan, the battery has to go through a planned sequence of charging and discharging cycle to avoid overcharge or deep discharge. An important parameter that must be estimated is the state of charge (SOC), as there is no direct measurement available, it is very important to carry out an accurate method in estimating the SOC level of the battery. Failure to estimate the SOC precisely may affect the performance and the lifetime of the battery. This report discusses various techniques to estimate the SOC of the battery such as open-circuit voltage (OCV) method, coulomb counting method and extended Kalman filter (EKF) algorithm. Next, an efficient charging or discharging algorithm is designed by using LabVIEW software to maintain the desired SOC level automatically. This algorithm uses the state machine design pattern which is able to execute a network of decision-making algorithm. Then, a battery management system (BMS) is able to decide when to charge or discharge the battery energy storage system (BESS) based on the SOC level and power demand by the microgrid. Lastly, three case studies with implementation of the algorithm are discussed. |
author2 |
Gooi Hoay Beng |
author_facet |
Gooi Hoay Beng Chow, Tze Hui |
format |
Final Year Project |
author |
Chow, Tze Hui |
author_sort |
Chow, Tze Hui |
title |
Efficient charging/discharging algorithm for battery storage system |
title_short |
Efficient charging/discharging algorithm for battery storage system |
title_full |
Efficient charging/discharging algorithm for battery storage system |
title_fullStr |
Efficient charging/discharging algorithm for battery storage system |
title_full_unstemmed |
Efficient charging/discharging algorithm for battery storage system |
title_sort |
efficient charging/discharging algorithm for battery storage system |
publishDate |
2015 |
url |
http://hdl.handle.net/10356/64629 |
_version_ |
1772828717372932096 |