Intelligent Power Management System of Bangladesh Using Artificial Neural Network

Md Mahfuzur Rahman; Joy Shaha; Navid Hossain; Arifur Rahman Sabuj; Shuvra Saha; A. S.M. Bakibillah

doi:10.1109/ISMS.2016.27

Intelligent Power Management System of Bangladesh Using Artificial Neural Network

Md Mahfuzur Rahman
, Joy Shaha
, Navid Hossain
, Arifur Rahman Sabuj
, Shuvra Saha
, A. S.M. Bakibillah

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

Abstract

In this research work, we have developed an intelligent power management system using Artificial Neural Network (ANN) which will control load shedding automatically in a local distribution area and utilize different types of power generation units like conventional and non-conventional energy sources. If generation is not sufficient to meet the load demand, then ANN network will anticipate and predict when the load demand is greater than generation and will suggest specifically the area where load shedding would be appropriate. Utilizing and manipulating different types of seasonal and occasional load data (which is actually divided into different areas such as residential-load, industrial-load, commercial-load and VIP-load), we have designed the artificial neural network so that it will automatically show us the area where load-shedding would be preferable on the basis of priority. Hence, the priority is given by the area where maximum load-shedding is desired.

Original language	English
Title of host publication	Proceedings - 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016
Editors	David Al-Dabass, Tiranee Achalakul, Rajchawit Sarochawikasit, Santitham Prom-On
Publisher	IEEE Computer Society
Pages	25-30
Number of pages	6
ISBN (Electronic)	9781509006649
DOIs	https://doi.org/10.1109/ISMS.2016.27
State	Published - 2 Jul 2016
Externally published	Yes
Event	7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016 - Bangkok, Thailand Duration: 25 Jan 2016 → 27 Jan 2016

Publication series

Name	Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS
Volume	0
ISSN (Print)	2166-0662
ISSN (Electronic)	2166-0670

Conference

Conference	7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016
Country/Territory	Thailand
City	Bangkok
Period	25/01/16 → 27/01/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Artificial Neural Network
Error histogram
Power System
Regression Plot
Solar Radiation
Supervised Learning

ASJC Scopus subject areas

Software
Theoretical Computer Science
Modeling and Simulation
Artificial Intelligence

Access to Document

10.1109/ISMS.2016.27

Cite this

Rahman, M. M., Shaha, J., Hossain, N., Sabuj, A. R., Saha, S., & Bakibillah, A. S. M. (2016). Intelligent Power Management System of Bangladesh Using Artificial Neural Network. In D. Al-Dabass, T. Achalakul, R. Sarochawikasit, & S. Prom-On (Eds.), Proceedings - 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016 (pp. 25-30). Article 7877183 (Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS; Vol. 0). IEEE Computer Society. https://doi.org/10.1109/ISMS.2016.27

Rahman, Md Mahfuzur ; Shaha, Joy ; Hossain, Navid et al. / Intelligent Power Management System of Bangladesh Using Artificial Neural Network. Proceedings - 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016. editor / David Al-Dabass ; Tiranee Achalakul ; Rajchawit Sarochawikasit ; Santitham Prom-On. IEEE Computer Society, 2016. pp. 25-30 (Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS).

@inproceedings{7d2c6eb9b7d84cbc8d6075d2ebb4c703,

title = "Intelligent Power Management System of Bangladesh Using Artificial Neural Network",

abstract = "In this research work, we have developed an intelligent power management system using Artificial Neural Network (ANN) which will control load shedding automatically in a local distribution area and utilize different types of power generation units like conventional and non-conventional energy sources. If generation is not sufficient to meet the load demand, then ANN network will anticipate and predict when the load demand is greater than generation and will suggest specifically the area where load shedding would be appropriate. Utilizing and manipulating different types of seasonal and occasional load data (which is actually divided into different areas such as residential-load, industrial-load, commercial-load and VIP-load), we have designed the artificial neural network so that it will automatically show us the area where load-shedding would be preferable on the basis of priority. Hence, the priority is given by the area where maximum load-shedding is desired.",

keywords = "Artificial Neural Network, Error histogram, Power System, Regression Plot, Solar Radiation, Supervised Learning",

author = "Rahman, \{Md Mahfuzur\} and Joy Shaha and Navid Hossain and Sabuj, \{Arifur Rahman\} and Shuvra Saha and Bakibillah, \{A. S.M.\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016 ; Conference date: 25-01-2016 Through 27-01-2016",

year = "2016",

month = jul,

day = "2",

doi = "10.1109/ISMS.2016.27",

language = "English",

series = "Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS",

publisher = "IEEE Computer Society",

pages = "25--30",

editor = "David Al-Dabass and Tiranee Achalakul and Rajchawit Sarochawikasit and Santitham Prom-On",

booktitle = "Proceedings - 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016",

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Rahman, MM, Shaha, J, Hossain, N, Sabuj, AR, Saha, S & Bakibillah, ASM 2016, Intelligent Power Management System of Bangladesh Using Artificial Neural Network. in D Al-Dabass, T Achalakul, R Sarochawikasit & S Prom-On (eds), Proceedings - 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016., 7877183, Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS, vol. 0, IEEE Computer Society, pp. 25-30, 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016, Bangkok, Thailand, 25/01/16. https://doi.org/10.1109/ISMS.2016.27

Intelligent Power Management System of Bangladesh Using Artificial Neural Network. / Rahman, Md Mahfuzur; Shaha, Joy; Hossain, Navid et al.
Proceedings - 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016. ed. / David Al-Dabass; Tiranee Achalakul; Rajchawit Sarochawikasit; Santitham Prom-On. IEEE Computer Society, 2016. p. 25-30 7877183 (Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS; Vol. 0).

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

TY - GEN

T1 - Intelligent Power Management System of Bangladesh Using Artificial Neural Network

AU - Rahman, Md Mahfuzur

AU - Shaha, Joy

AU - Hossain, Navid

AU - Sabuj, Arifur Rahman

AU - Saha, Shuvra

AU - Bakibillah, A. S.M.

PY - 2016/7/2

Y1 - 2016/7/2

N2 - In this research work, we have developed an intelligent power management system using Artificial Neural Network (ANN) which will control load shedding automatically in a local distribution area and utilize different types of power generation units like conventional and non-conventional energy sources. If generation is not sufficient to meet the load demand, then ANN network will anticipate and predict when the load demand is greater than generation and will suggest specifically the area where load shedding would be appropriate. Utilizing and manipulating different types of seasonal and occasional load data (which is actually divided into different areas such as residential-load, industrial-load, commercial-load and VIP-load), we have designed the artificial neural network so that it will automatically show us the area where load-shedding would be preferable on the basis of priority. Hence, the priority is given by the area where maximum load-shedding is desired.

AB - In this research work, we have developed an intelligent power management system using Artificial Neural Network (ANN) which will control load shedding automatically in a local distribution area and utilize different types of power generation units like conventional and non-conventional energy sources. If generation is not sufficient to meet the load demand, then ANN network will anticipate and predict when the load demand is greater than generation and will suggest specifically the area where load shedding would be appropriate. Utilizing and manipulating different types of seasonal and occasional load data (which is actually divided into different areas such as residential-load, industrial-load, commercial-load and VIP-load), we have designed the artificial neural network so that it will automatically show us the area where load-shedding would be preferable on the basis of priority. Hence, the priority is given by the area where maximum load-shedding is desired.

KW - Artificial Neural Network

KW - Error histogram

KW - Power System

KW - Regression Plot

KW - Solar Radiation

KW - Supervised Learning

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DO - 10.1109/ISMS.2016.27

M3 - Conference contribution

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T3 - Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS

SP - 25

EP - 30

BT - Proceedings - 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016

A2 - Al-Dabass, David

A2 - Achalakul, Tiranee

A2 - Sarochawikasit, Rajchawit

A2 - Prom-On, Santitham

PB - IEEE Computer Society

T2 - 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016

Y2 - 25 January 2016 through 27 January 2016

ER -

Rahman MM, Shaha J, Hossain N, Sabuj AR, Saha S, Bakibillah ASM. Intelligent Power Management System of Bangladesh Using Artificial Neural Network. In Al-Dabass D, Achalakul T, Sarochawikasit R, Prom-On S, editors, Proceedings - 7th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2016. IEEE Computer Society. 2016. p. 25-30. 7877183. (Proceedings - International Conference on Intelligent Systems, Modelling and Simulation, ISMS). doi: 10.1109/ISMS.2016.27

Intelligent Power Management System of Bangladesh Using Artificial Neural Network

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this