Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method

I. Gde Made Yoga Semadhi Artha; Ida Bagus Gede Manuaba

doi:doi:10.11648/j.jeee.20190701.11

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Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method

I. Gde Made Yoga Semadhi Artha, Ida Bagus Gede Manuaba

Published in Journal of Electrical and Electronic Engineering (Volume 7, Issue 1)

Received: 31 October 2018 Accepted: 27 November 2018 Published: 24 January 2019

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Abstract

The development of the tourist destinations of Bali Island, especially Nusa Dua area, should be included with the development of electricity supply in the region. To facilitate a process of electrical energy planning in the region, it is necessary to forecast the electrical load in the area. Forecasting is a process to estimate future events / things to come. In this research, the forecasting of the long-term electrical load for five years and this forecasting method using ANFIS method and use ANN method as a comparison. From the simulation conducted by MAPE which resulted from forecasting the weekly electrical load using ANFIS method is 0.028% while MAPE forecasting using ANN method is 51.57%. From the comparison result, it can be said that the annual electricity load forecasting using the ANFIS method has a better forecasting accuracy than using the ANN method. The forecasting results of this transformer load is used as a reference in planning the electricity system on the Bali Island.

Published in	Journal of Electrical and Electronic Engineering (Volume 7, Issue 1)
DOI	10.11648/j.jeee.20190701.11
Page(s)	1-7
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

ANFIS, MAPE, Electrical Load

References

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APA Style

I. Gde Made Yoga Semadhi Artha, Ida Bagus Gede Manuaba. (2019). Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method. Journal of Electrical and Electronic Engineering, 7(1), 1-7. https://doi.org/10.11648/j.jeee.20190701.11

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ACS Style

I. Gde Made Yoga Semadhi Artha; Ida Bagus Gede Manuaba. Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method. J. Electr. Electron. Eng. 2019, 7(1), 1-7. doi: 10.11648/j.jeee.20190701.11

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AMA Style

I. Gde Made Yoga Semadhi Artha, Ida Bagus Gede Manuaba. Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method. J Electr Electron Eng. 2019;7(1):1-7. doi: 10.11648/j.jeee.20190701.11

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@article{10.11648/j.jeee.20190701.11,
  author = {I. Gde Made Yoga Semadhi Artha and Ida Bagus Gede Manuaba},
  title = {Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method},
  journal = {Journal of Electrical and Electronic Engineering},
  volume = {7},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.jeee.20190701.11},
  url = {https://doi.org/10.11648/j.jeee.20190701.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20190701.11},
  abstract = {The development of the tourist destinations of Bali Island, especially Nusa Dua area, should be included with the development of electricity supply in the region. To facilitate a process of electrical energy planning in the region, it is necessary to forecast the electrical load in the area. Forecasting is a process to estimate future events / things to come. In this research, the forecasting of the long-term electrical load for five years and this forecasting method using ANFIS method and use ANN method as a comparison. From the simulation conducted by MAPE which resulted from forecasting the weekly electrical load using ANFIS method is 0.028% while MAPE forecasting using ANN method is 51.57%. From the comparison result, it can be said that the annual electricity load forecasting using the ANFIS method has a better forecasting accuracy than using the ANN method. The forecasting results of this transformer load is used as a reference in planning the electricity system on the Bali Island.},
 year = {2019}
}

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TY  - JOUR
T1  - Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method
AU  - I. Gde Made Yoga Semadhi Artha
AU  - Ida Bagus Gede Manuaba
Y1  - 2019/01/24
PY  - 2019
N1  - https://doi.org/10.11648/j.jeee.20190701.11
DO  - 10.11648/j.jeee.20190701.11
T2  - Journal of Electrical and Electronic Engineering
JF  - Journal of Electrical and Electronic Engineering
JO  - Journal of Electrical and Electronic Engineering
SP  - 1
EP  - 7
PB  - Science Publishing Group
SN  - 2329-1605
UR  - https://doi.org/10.11648/j.jeee.20190701.11
AB  - The development of the tourist destinations of Bali Island, especially Nusa Dua area, should be included with the development of electricity supply in the region. To facilitate a process of electrical energy planning in the region, it is necessary to forecast the electrical load in the area. Forecasting is a process to estimate future events / things to come. In this research, the forecasting of the long-term electrical load for five years and this forecasting method using ANFIS method and use ANN method as a comparison. From the simulation conducted by MAPE which resulted from forecasting the weekly electrical load using ANFIS method is 0.028% while MAPE forecasting using ANN method is 51.57%. From the comparison result, it can be said that the annual electricity load forecasting using the ANFIS method has a better forecasting accuracy than using the ANN method. The forecasting results of this transformer load is used as a reference in planning the electricity system on the Bali Island.
VL  - 7
IS  - 1
ER  -

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Author Information

I. Gde Made Yoga Semadhi Artha

Department of Electrical Engineering, Udayana University, Denpasar, Indonesia
Ida Bagus Gede Manuaba

Department of Electrical Engineering, Udayana University, Denpasar, Indonesia

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APA Style

I. Gde Made Yoga Semadhi Artha, Ida Bagus Gede Manuaba. (2019). Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method. Journal of Electrical and Electronic Engineering, 7(1), 1-7. https://doi.org/10.11648/j.jeee.20190701.11

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ACS Style

I. Gde Made Yoga Semadhi Artha; Ida Bagus Gede Manuaba. Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method. J. Electr. Electron. Eng. 2019, 7(1), 1-7. doi: 10.11648/j.jeee.20190701.11

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AMA Style

I. Gde Made Yoga Semadhi Artha, Ida Bagus Gede Manuaba. Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method. J Electr Electron Eng. 2019;7(1):1-7. doi: 10.11648/j.jeee.20190701.11

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@article{10.11648/j.jeee.20190701.11,
  author = {I. Gde Made Yoga Semadhi Artha and Ida Bagus Gede Manuaba},
  title = {Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method},
  journal = {Journal of Electrical and Electronic Engineering},
  volume = {7},
  number = {1},
  pages = {1-7},
  doi = {10.11648/j.jeee.20190701.11},
  url = {https://doi.org/10.11648/j.jeee.20190701.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20190701.11},
  abstract = {The development of the tourist destinations of Bali Island, especially Nusa Dua area, should be included with the development of electricity supply in the region. To facilitate a process of electrical energy planning in the region, it is necessary to forecast the electrical load in the area. Forecasting is a process to estimate future events / things to come. In this research, the forecasting of the long-term electrical load for five years and this forecasting method using ANFIS method and use ANN method as a comparison. From the simulation conducted by MAPE which resulted from forecasting the weekly electrical load using ANFIS method is 0.028% while MAPE forecasting using ANN method is 51.57%. From the comparison result, it can be said that the annual electricity load forecasting using the ANFIS method has a better forecasting accuracy than using the ANN method. The forecasting results of this transformer load is used as a reference in planning the electricity system on the Bali Island.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Transformer’s Load Forecasting to Find the Transformer Usage Capacity with Adaptive Neuro-Fuzzy Inference System Method
AU  - I. Gde Made Yoga Semadhi Artha
AU  - Ida Bagus Gede Manuaba
Y1  - 2019/01/24
PY  - 2019
N1  - https://doi.org/10.11648/j.jeee.20190701.11
DO  - 10.11648/j.jeee.20190701.11
T2  - Journal of Electrical and Electronic Engineering
JF  - Journal of Electrical and Electronic Engineering
JO  - Journal of Electrical and Electronic Engineering
SP  - 1
EP  - 7
PB  - Science Publishing Group
SN  - 2329-1605
UR  - https://doi.org/10.11648/j.jeee.20190701.11
AB  - The development of the tourist destinations of Bali Island, especially Nusa Dua area, should be included with the development of electricity supply in the region. To facilitate a process of electrical energy planning in the region, it is necessary to forecast the electrical load in the area. Forecasting is a process to estimate future events / things to come. In this research, the forecasting of the long-term electrical load for five years and this forecasting method using ANFIS method and use ANN method as a comparison. From the simulation conducted by MAPE which resulted from forecasting the weekly electrical load using ANFIS method is 0.028% while MAPE forecasting using ANN method is 51.57%. From the comparison result, it can be said that the annual electricity load forecasting using the ANFIS method has a better forecasting accuracy than using the ANN method. The forecasting results of this transformer load is used as a reference in planning the electricity system on the Bali Island.
VL  - 7
IS  - 1
ER  -

Copy | Download