PV Power Forecast Based on Artificial Neural Network at Indonesia Shopping Mall PV Rooftop

Karimatun Nisa'; Luki Mahendra; Hodi Eko; Imam Wahyudi Farid

doi:10.1109/ICAMIMIA54022.2021.9807694

PV Power Forecast Based on Artificial Neural Network at Indonesia Shopping Mall PV Rooftop

Karimatun Nisa'
, Luki Mahendra
, Hodi Eko
, Imam Wahyudi Farid

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

2 Citations (Scopus)

Abstract

In this research, forecast of Photovoltaic (PV) rooftop power output has been carried out. Forecast is using machine learning Artificial Neural Network (ANN). ANN is precisely used for forecast by memorizing and learning data patterns that are used as training and targets. The input training data used are irradiance, PV temperature and time per 10 minutes and time per 1 hour for 6 days. While the target is the PV output power data for 6 days. The training algoritm that used is Levenberg-Marquardt (LM) Algorithm. LM trains the network faster and has high rate of convergence. The performance parameter used to determine a good ANN forecast is the Mean Square Error (MSE). After conducting the training data, the data is tested for ANN forecast using input data on the seventh days. The output is the forecasted PV output power. The forecast results will be compared with the PV output power measurement data.

Original language	English
Title of host publication	2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	335-338
Number of pages	4
ISBN (Electronic)	9781665499699
DOIs	https://doi.org/10.1109/ICAMIMIA54022.2021.9807694
Publication status	Published - 2021
Event	2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Surabya, Indonesia Duration: 8 Dec 2021 → 9 Dec 2021

Publication series

Name	2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding

Conference

Conference	2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021
Country/Territory	Indonesia
City	Surabya
Period	8/12/21 → 9/12/21

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

ANN
Forecasting
Levenberg-Marquardt
MSE
PV

Access to Document

10.1109/ICAMIMIA54022.2021.9807694

Cite this

Nisa', K., Mahendra, L., Eko, H., & Farid, I. W. (2021). PV Power Forecast Based on Artificial Neural Network at Indonesia Shopping Mall PV Rooftop. In 2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding (pp. 335-338). (2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAMIMIA54022.2021.9807694

Nisa', Karimatun ; Mahendra, Luki ; Eko, Hodi et al. / PV Power Forecast Based on Artificial Neural Network at Indonesia Shopping Mall PV Rooftop. 2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 335-338 (2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding).

@inproceedings{eac17497cd214e48bae6e66a33e9db21,

title = "PV Power Forecast Based on Artificial Neural Network at Indonesia Shopping Mall PV Rooftop",

abstract = "In this research, forecast of Photovoltaic (PV) rooftop power output has been carried out. Forecast is using machine learning Artificial Neural Network (ANN). ANN is precisely used for forecast by memorizing and learning data patterns that are used as training and targets. The input training data used are irradiance, PV temperature and time per 10 minutes and time per 1 hour for 6 days. While the target is the PV output power data for 6 days. The training algoritm that used is Levenberg-Marquardt (LM) Algorithm. LM trains the network faster and has high rate of convergence. The performance parameter used to determine a good ANN forecast is the Mean Square Error (MSE). After conducting the training data, the data is tested for ANN forecast using input data on the seventh days. The output is the forecasted PV output power. The forecast results will be compared with the PV output power measurement data.",

keywords = "ANN, Forecasting, Levenberg-Marquardt, MSE, PV",

author = "Karimatun Nisa' and Luki Mahendra and Hodi Eko and Farid, \{Imam Wahyudi\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 ; Conference date: 08-12-2021 Through 09-12-2021",

year = "2021",

doi = "10.1109/ICAMIMIA54022.2021.9807694",

language = "English",

series = "2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding",

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

pages = "335--338",

booktitle = "2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding",

address = "United States",

}

Nisa', K, Mahendra, L, Eko, H & Farid, IW 2021, PV Power Forecast Based on Artificial Neural Network at Indonesia Shopping Mall PV Rooftop. in 2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding. 2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding, Institute of Electrical and Electronics Engineers Inc., pp. 335-338, 2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021, Surabya, Indonesia, 8/12/21. https://doi.org/10.1109/ICAMIMIA54022.2021.9807694

PV Power Forecast Based on Artificial Neural Network at Indonesia Shopping Mall PV Rooftop. / Nisa', Karimatun; Mahendra, Luki; Eko, Hodi et al.
2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding. Institute of Electrical and Electronics Engineers Inc., 2021. p. 335-338 (2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding).

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

TY - GEN

T1 - PV Power Forecast Based on Artificial Neural Network at Indonesia Shopping Mall PV Rooftop

AU - Nisa', Karimatun

AU - Mahendra, Luki

AU - Eko, Hodi

AU - Farid, Imam Wahyudi

PY - 2021

Y1 - 2021

N2 - In this research, forecast of Photovoltaic (PV) rooftop power output has been carried out. Forecast is using machine learning Artificial Neural Network (ANN). ANN is precisely used for forecast by memorizing and learning data patterns that are used as training and targets. The input training data used are irradiance, PV temperature and time per 10 minutes and time per 1 hour for 6 days. While the target is the PV output power data for 6 days. The training algoritm that used is Levenberg-Marquardt (LM) Algorithm. LM trains the network faster and has high rate of convergence. The performance parameter used to determine a good ANN forecast is the Mean Square Error (MSE). After conducting the training data, the data is tested for ANN forecast using input data on the seventh days. The output is the forecasted PV output power. The forecast results will be compared with the PV output power measurement data.

AB - In this research, forecast of Photovoltaic (PV) rooftop power output has been carried out. Forecast is using machine learning Artificial Neural Network (ANN). ANN is precisely used for forecast by memorizing and learning data patterns that are used as training and targets. The input training data used are irradiance, PV temperature and time per 10 minutes and time per 1 hour for 6 days. While the target is the PV output power data for 6 days. The training algoritm that used is Levenberg-Marquardt (LM) Algorithm. LM trains the network faster and has high rate of convergence. The performance parameter used to determine a good ANN forecast is the Mean Square Error (MSE). After conducting the training data, the data is tested for ANN forecast using input data on the seventh days. The output is the forecasted PV output power. The forecast results will be compared with the PV output power measurement data.

KW - ANN

KW - Forecasting

KW - Levenberg-Marquardt

KW - MSE

KW - PV

UR - https://www.scopus.com/pages/publications/85135051128

U2 - 10.1109/ICAMIMIA54022.2021.9807694

DO - 10.1109/ICAMIMIA54022.2021.9807694

M3 - Conference contribution

AN - SCOPUS:85135051128

T3 - 2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding

SP - 335

EP - 338

BT - 2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021

Y2 - 8 December 2021 through 9 December 2021

ER -

Nisa' K, Mahendra L, Eko H, Farid IW. PV Power Forecast Based on Artificial Neural Network at Indonesia Shopping Mall PV Rooftop. In 2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding. Institute of Electrical and Electronics Engineers Inc. 2021. p. 335-338. (2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021 - Proceeding). doi: 10.1109/ICAMIMIA54022.2021.9807694

PV Power Forecast Based on Artificial Neural Network at Indonesia Shopping Mall PV Rooftop

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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