ANN-Based Grid-Connected Solar PV Integrated Smart Home Energy Management System

Md Rokonuzzaman; Mahmuda Khatun Mishu; Wen Shan Tan; Asif Islam; Mohammad Almuhaini; Nowshad Amin

doi:10.1109/APPEEC61255.2024.10922296

ANN-Based Grid-Connected Solar PV Integrated Smart Home Energy Management System

Md Rokonuzzaman, Mahmuda Khatun Mishu, Wen Shan Tan, Asif Islam, Mohammad Almuhaini, Nowshad Amin

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

Abstract

With the growing scarcity of fossil fuels and frequent economic crises, renewable energy sources (RES) and artificial intelligence (AI) techniques present a groundbreaking combination. AI is increasingly popular in energy research due to its accuracy. In this paper, an artificial neural network (ANN)-specifically a Levenberg-Marquardt (LM)-based smart home energy management system (SHEMS)-is developed and integrated with a grid-connected solar photovoltaic (PV) system. The LM algorithm shows the regression value 1, which is implemented with 1,000 sample data taken from a solar PV park. Seventy percent of the data is used to train the LM algorithm, while fifteen percent is to test and the rest to validate. The proposed system connects utility companies and consumers, allowing for bi-directional communication, which improves the efficiency of a sustainable home energy management system.

Original language	English
Title of host publication	2024 IEEE PES 16th Asia-Pacific Power and Energy Engineering Conference
Subtitle of host publication	Innovative Technologies Drive Low-Carbon, Sustainable, and Flexible Energy Systems, APPEEC 2024 - Proceedings
Publisher	IEEE Computer Society
ISBN (Electronic)	9798350386127
DOIs	https://doi.org/10.1109/APPEEC61255.2024.10922296
State	Published - 2024
Event	16th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2024 - Nanjing, China Duration: 25 Oct 2024 → 27 Oct 2024

Publication series

Name	Asia-Pacific Power and Energy Engineering Conference, APPEEC
ISSN (Print)	2157-4839
ISSN (Electronic)	2157-4847

Conference

Conference	16th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2024
Country/Territory	China
City	Nanjing
Period	25/10/24 → 27/10/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

artificial neural network (ANN)
grid-connected solar PV
home energy management system (HEMS)
Internet of things (loT)

ASJC Scopus subject areas

Energy Engineering and Power Technology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/APPEEC61255.2024.10922296

Cite this

Rokonuzzaman, M., Mishu, M. K., Tan, W. S., Islam, A., Almuhaini, M., & Amin, N. (2024). ANN-Based Grid-Connected Solar PV Integrated Smart Home Energy Management System. In 2024 IEEE PES 16th Asia-Pacific Power and Energy Engineering Conference: Innovative Technologies Drive Low-Carbon, Sustainable, and Flexible Energy Systems, APPEEC 2024 - Proceedings (Asia-Pacific Power and Energy Engineering Conference, APPEEC). IEEE Computer Society. https://doi.org/10.1109/APPEEC61255.2024.10922296

Rokonuzzaman, Md ; Mishu, Mahmuda Khatun ; Tan, Wen Shan et al. / ANN-Based Grid-Connected Solar PV Integrated Smart Home Energy Management System. 2024 IEEE PES 16th Asia-Pacific Power and Energy Engineering Conference: Innovative Technologies Drive Low-Carbon, Sustainable, and Flexible Energy Systems, APPEEC 2024 - Proceedings. IEEE Computer Society, 2024. (Asia-Pacific Power and Energy Engineering Conference, APPEEC).

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title = "ANN-Based Grid-Connected Solar PV Integrated Smart Home Energy Management System",

abstract = "With the growing scarcity of fossil fuels and frequent economic crises, renewable energy sources (RES) and artificial intelligence (AI) techniques present a groundbreaking combination. AI is increasingly popular in energy research due to its accuracy. In this paper, an artificial neural network (ANN)-specifically a Levenberg-Marquardt (LM)-based smart home energy management system (SHEMS)-is developed and integrated with a grid-connected solar photovoltaic (PV) system. The LM algorithm shows the regression value 1, which is implemented with 1,000 sample data taken from a solar PV park. Seventy percent of the data is used to train the LM algorithm, while fifteen percent is to test and the rest to validate. The proposed system connects utility companies and consumers, allowing for bi-directional communication, which improves the efficiency of a sustainable home energy management system.",

keywords = "artificial neural network (ANN), grid-connected solar PV, home energy management system (HEMS), Internet of things (loT)",

author = "Md Rokonuzzaman and Mishu, \{Mahmuda Khatun\} and Tan, \{Wen Shan\} and Asif Islam and Mohammad Almuhaini and Nowshad Amin",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 16th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2024 ; Conference date: 25-10-2024 Through 27-10-2024",

year = "2024",

doi = "10.1109/APPEEC61255.2024.10922296",

language = "English",

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Rokonuzzaman, M, Mishu, MK, Tan, WS, Islam, A , Almuhaini, M & Amin, N 2024, ANN-Based Grid-Connected Solar PV Integrated Smart Home Energy Management System. in 2024 IEEE PES 16th Asia-Pacific Power and Energy Engineering Conference: Innovative Technologies Drive Low-Carbon, Sustainable, and Flexible Energy Systems, APPEEC 2024 - Proceedings. Asia-Pacific Power and Energy Engineering Conference, APPEEC, IEEE Computer Society, 16th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2024, Nanjing, China, 25/10/24. https://doi.org/10.1109/APPEEC61255.2024.10922296

ANN-Based Grid-Connected Solar PV Integrated Smart Home Energy Management System. / Rokonuzzaman, Md; Mishu, Mahmuda Khatun; Tan, Wen Shan et al.
2024 IEEE PES 16th Asia-Pacific Power and Energy Engineering Conference: Innovative Technologies Drive Low-Carbon, Sustainable, and Flexible Energy Systems, APPEEC 2024 - Proceedings. IEEE Computer Society, 2024. (Asia-Pacific Power and Energy Engineering Conference, APPEEC).

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

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T1 - ANN-Based Grid-Connected Solar PV Integrated Smart Home Energy Management System

AU - Rokonuzzaman, Md

AU - Mishu, Mahmuda Khatun

AU - Tan, Wen Shan

AU - Islam, Asif

AU - Almuhaini, Mohammad

AU - Amin, Nowshad

PY - 2024

Y1 - 2024

N2 - With the growing scarcity of fossil fuels and frequent economic crises, renewable energy sources (RES) and artificial intelligence (AI) techniques present a groundbreaking combination. AI is increasingly popular in energy research due to its accuracy. In this paper, an artificial neural network (ANN)-specifically a Levenberg-Marquardt (LM)-based smart home energy management system (SHEMS)-is developed and integrated with a grid-connected solar photovoltaic (PV) system. The LM algorithm shows the regression value 1, which is implemented with 1,000 sample data taken from a solar PV park. Seventy percent of the data is used to train the LM algorithm, while fifteen percent is to test and the rest to validate. The proposed system connects utility companies and consumers, allowing for bi-directional communication, which improves the efficiency of a sustainable home energy management system.

AB - With the growing scarcity of fossil fuels and frequent economic crises, renewable energy sources (RES) and artificial intelligence (AI) techniques present a groundbreaking combination. AI is increasingly popular in energy research due to its accuracy. In this paper, an artificial neural network (ANN)-specifically a Levenberg-Marquardt (LM)-based smart home energy management system (SHEMS)-is developed and integrated with a grid-connected solar photovoltaic (PV) system. The LM algorithm shows the regression value 1, which is implemented with 1,000 sample data taken from a solar PV park. Seventy percent of the data is used to train the LM algorithm, while fifteen percent is to test and the rest to validate. The proposed system connects utility companies and consumers, allowing for bi-directional communication, which improves the efficiency of a sustainable home energy management system.

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KW - grid-connected solar PV

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KW - Internet of things (loT)

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T3 - Asia-Pacific Power and Energy Engineering Conference, APPEEC

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PB - IEEE Computer Society

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Y2 - 25 October 2024 through 27 October 2024

ER -

Rokonuzzaman M, Mishu MK, Tan WS, Islam A , Almuhaini M, Amin N. ANN-Based Grid-Connected Solar PV Integrated Smart Home Energy Management System. In 2024 IEEE PES 16th Asia-Pacific Power and Energy Engineering Conference: Innovative Technologies Drive Low-Carbon, Sustainable, and Flexible Energy Systems, APPEEC 2024 - Proceedings. IEEE Computer Society. 2024. (Asia-Pacific Power and Energy Engineering Conference, APPEEC). doi: 10.1109/APPEEC61255.2024.10922296

ANN-Based Grid-Connected Solar PV Integrated Smart Home Energy Management System

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this