Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)

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Prediction of PV Power Output and Battery Charging Conditions on OFF Grid Systems MicroHydro Pantai Bantul Yogyakarta Using Rule-Based Algorithm

Authors
Norma Mahmudah1, *, Ibrahim Saiful Millah1, A. Labib Fardany Faisal1, Luki Septya Mahendra1, Agus Dwi Santoso2, Retia Arnofal1, Moh Rahbini1
1Industrial Electrical Engineering, Politeknik Negeri Madura, Madura, Indonesia
2Ship Electrical Engineering Technology, Politeknik Pelayaran Surabaya, Surabaya, Indonesia
*Corresponding author. Email: norma.mahmudah@poltera.ac.id
Corresponding Author
Norma Mahmudah
Available Online 17 February 2024.
DOI
10.2991/978-94-6463-364-1_94How to use a DOI?
Keywords
Artificial Neural Network; Cascade Forward Neural Network; Levenberg-marquard; Photovoltaic (PV); Energy Management System (EMS); State of Charge (SOC)
Abstract

Energy Management System (EMS) is used as a renewable energy control strategy. This research uses photovoltaics and wind turbines, which is a suitable combination because photovoltaics work during the day while wind turbines can supply batteries that are used at night. The Energy Management System (EMS) in this research consists of photovoltaics, wind turbines, batteries and commercial loads. The system uses an off-grid system with real data from PLTH Pantai Baru Bantul. Prediction of PV power output uses an Artificial Neural Network (ANN), namely Cascade Forward Neural Network, by considering irradiance, PV module temperature, current PV data, which has a Mean Square Error (MSE) of 0.9% with a learning rate of 0.01. The rule base algorithm is used to maximize power from PV renewable energy and wind turbines by implementing a load-shedding scheme so that the resulting power is maximized for charging the battery and maintaining the battery SOC at safe limits with a minimum SOC of 20% and a maximum SOC of 90%. The research is expected to provide recommendations for managing renewable energy using an off-grid system to make it more efficient and reduce dependence on external energy sources.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)
Series
Advances in Engineering Research
Publication Date
17 February 2024
ISBN
978-94-6463-364-1
ISSN
2352-5401
DOI
10.2991/978-94-6463-364-1_94How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Norma Mahmudah
AU  - Ibrahim Saiful Millah
AU  - A. Labib Fardany Faisal
AU  - Luki Septya Mahendra
AU  - Agus Dwi Santoso
AU  - Retia Arnofal
AU  - Moh Rahbini
PY  - 2024
DA  - 2024/02/17
TI  - Prediction of PV Power Output and Battery Charging Conditions on OFF Grid Systems MicroHydro Pantai Bantul Yogyakarta Using Rule-Based Algorithm
BT  - Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)
PB  - Atlantis Press
SP  - 1032
EP  - 1043
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-364-1_94
DO  - 10.2991/978-94-6463-364-1_94
ID  - Mahmudah2024
ER  -