Monotonic Controller for Battery Energy Storage System Using Neural Network

Hassan I. Alhammad; Waleed M. Hamanah; A. Hussein; Mohammad A. Abido

doi:10.1109/GlobConHT56829.2023.10087363

Monotonic Controller for Battery Energy Storage System Using Neural Network

Hassan I. Alhammad
, Waleed M. Hamanah^*
, A. Hussein
, Mohammad A. Abido

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Demand-generation mismatch introduces extensive technical as well as economic challenges to the power system network. Furthermore, with the increasing global interest in integrating variable renewable generation systems, it becomes more challenging to eliminate demand-generation mismatch. Therefore, the elimination of demand-generation mismatch will define the efficacy and quantify the economics of future renewable integrated smart grid systems. Incorporating batteries to provide energy buffering is among the most feasible, but most expensive, solutions to deal with system discrepancies. The battery energy storage system (BESS) has a limited life cycle and inherently lacks economic significance due to frequent charging and discharge. Therefore, in this paper, a monotonic operation of BESS is coordinated and kept between maximum and minimum State-of-Charge (SoC). The classical controller has been designed and validated with sets of generation and load profiles with two batteries. Accordingly, a neural network system based on pattern recognition is trained to operate the BESS under monotonic operation.

Original language	English
Title of host publication	2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350332117
DOIs	https://doi.org/10.1109/GlobConHT56829.2023.10087363
State	Published - 2023
Event	2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023 - Male, Maldives Duration: 11 Mar 2023 → 12 Mar 2023

Publication series

Name	2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023

Conference

Conference	2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023
Country/Territory	Maldives
City	Male
Period	11/03/23 → 12/03/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Battery energy storage system
classical controller
monotonic controller
neural network

ASJC Scopus subject areas

Electrical and Electronic Engineering
Safety, Risk, Reliability and Quality
Artificial Intelligence
Computer Networks and Communications
Energy Engineering and Power Technology
Fuel Technology
Renewable Energy, Sustainability and the Environment

Access to Document

10.1109/GlobConHT56829.2023.10087363

Cite this

Alhammad, H. I., Hamanah, W. M., Hussein, A., & Abido, M. A. (2023). Monotonic Controller for Battery Energy Storage System Using Neural Network. In 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023 (2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobConHT56829.2023.10087363

Alhammad, Hassan I. ; Hamanah, Waleed M. ; Hussein, A. et al. / Monotonic Controller for Battery Energy Storage System Using Neural Network. 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023).

@inproceedings{247c21e27e7a4674a925762d02962072,

title = "Monotonic Controller for Battery Energy Storage System Using Neural Network",

abstract = "Demand-generation mismatch introduces extensive technical as well as economic challenges to the power system network. Furthermore, with the increasing global interest in integrating variable renewable generation systems, it becomes more challenging to eliminate demand-generation mismatch. Therefore, the elimination of demand-generation mismatch will define the efficacy and quantify the economics of future renewable integrated smart grid systems. Incorporating batteries to provide energy buffering is among the most feasible, but most expensive, solutions to deal with system discrepancies. The battery energy storage system (BESS) has a limited life cycle and inherently lacks economic significance due to frequent charging and discharge. Therefore, in this paper, a monotonic operation of BESS is coordinated and kept between maximum and minimum State-of-Charge (SoC). The classical controller has been designed and validated with sets of generation and load profiles with two batteries. Accordingly, a neural network system based on pattern recognition is trained to operate the BESS under monotonic operation.",

keywords = "Battery energy storage system, classical controller, monotonic controller, neural network",

author = "Alhammad, \{Hassan I.\} and Hamanah, \{Waleed M.\} and A. Hussein and Abido, \{Mohammad A.\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023 ; Conference date: 11-03-2023 Through 12-03-2023",

year = "2023",

doi = "10.1109/GlobConHT56829.2023.10087363",

language = "English",

series = "2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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address = "United States",

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Alhammad, HI, Hamanah, WM , Hussein, A & Abido, MA 2023, Monotonic Controller for Battery Energy Storage System Using Neural Network. in 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023. 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023, Male, Maldives, 11/03/23. https://doi.org/10.1109/GlobConHT56829.2023.10087363

Monotonic Controller for Battery Energy Storage System Using Neural Network. / Alhammad, Hassan I.; Hamanah, Waleed M.; Hussein, A. et al.
2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Monotonic Controller for Battery Energy Storage System Using Neural Network

AU - Alhammad, Hassan I.

AU - Hamanah, Waleed M.

AU - Hussein, A.

AU - Abido, Mohammad A.

PY - 2023

Y1 - 2023

N2 - Demand-generation mismatch introduces extensive technical as well as economic challenges to the power system network. Furthermore, with the increasing global interest in integrating variable renewable generation systems, it becomes more challenging to eliminate demand-generation mismatch. Therefore, the elimination of demand-generation mismatch will define the efficacy and quantify the economics of future renewable integrated smart grid systems. Incorporating batteries to provide energy buffering is among the most feasible, but most expensive, solutions to deal with system discrepancies. The battery energy storage system (BESS) has a limited life cycle and inherently lacks economic significance due to frequent charging and discharge. Therefore, in this paper, a monotonic operation of BESS is coordinated and kept between maximum and minimum State-of-Charge (SoC). The classical controller has been designed and validated with sets of generation and load profiles with two batteries. Accordingly, a neural network system based on pattern recognition is trained to operate the BESS under monotonic operation.

AB - Demand-generation mismatch introduces extensive technical as well as economic challenges to the power system network. Furthermore, with the increasing global interest in integrating variable renewable generation systems, it becomes more challenging to eliminate demand-generation mismatch. Therefore, the elimination of demand-generation mismatch will define the efficacy and quantify the economics of future renewable integrated smart grid systems. Incorporating batteries to provide energy buffering is among the most feasible, but most expensive, solutions to deal with system discrepancies. The battery energy storage system (BESS) has a limited life cycle and inherently lacks economic significance due to frequent charging and discharge. Therefore, in this paper, a monotonic operation of BESS is coordinated and kept between maximum and minimum State-of-Charge (SoC). The classical controller has been designed and validated with sets of generation and load profiles with two batteries. Accordingly, a neural network system based on pattern recognition is trained to operate the BESS under monotonic operation.

KW - Battery energy storage system

KW - classical controller

KW - monotonic controller

KW - neural network

UR - https://www.scopus.com/pages/publications/85153576829

U2 - 10.1109/GlobConHT56829.2023.10087363

DO - 10.1109/GlobConHT56829.2023.10087363

M3 - Conference contribution

AN - SCOPUS:85153576829

T3 - 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023

BT - 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023

Y2 - 11 March 2023 through 12 March 2023

ER -

Alhammad HI, Hamanah WM , Hussein A , Abido MA. Monotonic Controller for Battery Energy Storage System Using Neural Network. In 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023). doi: 10.1109/GlobConHT56829.2023.10087363

Monotonic Controller for Battery Energy Storage System Using Neural Network

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this