FORECAST OF ELECTRIC ENERGY CONSUMPTION IN SANGGAU REGENCY USING COMBNED METHODS

Authors

  • Ignasius Ari Junardi Tanjungpura University

DOI:

https://doi.org/10.26418/telectrical.v2i1.78909

Keywords:

Electric Energy Demand, MAPE, DKL 3.2, Simple Linear Regression

Abstract

Electrical energy is an essential need in this era that continues to increase in line with economic and population growth. This condition must of course be anticipated as early as possible so that the provision of electrical energy can be available in sufficient quantities, thus forecasting electrical energy demand is an anticipatory step to see the growth in electrical energy demand which is expected to grow rapidly in the following years. In conducting this research, the data used is in the form of electrical energy customer data, connected power and electrical energy consumption which is then calculated and compared the results between the DKL 3.2 model and the simple linear regression method. The total forecast results of the DKL 3.2 method in 2028 are 141,990 customers, 444,266,970.17 kWh, 232,100,915.26 VA, while the simple linear regression method is 159,850 customers, 302,867,395.10 kWh, 305,291,235 VA. The results of the calculation of projected electrical energy demand in Sanggau Regency in 2024-2028 continue to increase, in the DKL 3.2 model for the number of customers the average annual increase is 3.292%, connected power is 3.126% and for electrical energy consumption is 15.031%. Meanwhile, for the simple linear regression method for the number of customers the average annual increase is 5.680%, connected power is 8.529% and for electrical energy consumption is 6.615%. From the comparison of the two methods for the linear regression method, the calculation is more accurate than the DKL 3.2 model with the difference in error in the number of electrical energy customers by 2.388%, connected power by 5.722% and electrical energy consumption by 8.416%

References

D. Hidayati, “Perkiraan Kebutuhan Konsumsi Energi Listrik Di Kabupaten Pati Pada Tahun 2026 Dengan Menggunakan Metode Gabungan,†2018.

S. Siregar, “Studi Prakiraan Kebutuhan Energi Listrik Tahun 2013-2017 Wilayah Kota Padang Sidimpuan Dengan Metode Gabungan,†2013.

A. Wahid, I. Junaidi, and H. M. I. Arsyad, “Analisis Kapasitas Dan Kebutuhan Daya Listrik Untuk Menghemat Penggunaan Energi Listrik Di Fakultas Teknik Universitas Tanjungpura,†2014.

N. Ulwan et al., “Prakiraan Kebutuhan Energi Listrik Kota Pontianak Pada Tahun 2021-2025 Dengan Metode Gabungan,†Jurnal Untan, 2021.

H. Darmawan, G. Budiono, and R. Hartayu, “Analisis Perbandingan Metode Prakiraan Kebutuhan Energi Listrik Menggunakan Moving Average Dan Exponential Smoothing Di PT. PLN Distribusi Jawa Timur,†2023.

Harahap Bima Tondi Inatta, “Analisis Prakiraan Kebutuhan Energi Listrik Di Provinsi Jambi Tahun 2019 - 2040 Menggunakan Model DKL 3.2 Dan Simulasi Perangkat Lunak LEAP (Long Range Energy Alternatives Planning),†2021.

Situmeang Frans Ezer, “Proyeksi Kebutuhan Energi Listrik Di Provinsi Jawa Tengah Tahun 2019 – 2025 Dengan Metode DKL Dan Business As Usual (BAU) Menggunakan Software Leap,†2019.

A. Datumaya Wahyudi Sumari, M. Bisri Musthafa, D. Rossiawan Hendra Putra, P. Studi Magister Terapan Teknik Elektro, J. Teknik Elektro, and P. Negeri Malang, “Perbandingan Kinerja Metode-Metode Prediksi pada Transaksi Dompet Digital di Masa Pandemi,†masa berlaku mulai, vol. 1, no. 3, pp. 642–647, 2017.

Sawindu Ari Cahya, “Perkiraan Kebutuhan Energi Listrik Menggunakan Software Leap Di PT. PLN (Persero) UP3 Surakarta Sampai Tahun 2024 Publikasi Ilmiah,†2020.

A. Ramadan, “Analisa Prakiraan Kebutuhan Energi Listrik Rayon Boyolali Menggunakan Metode DKL 3.2,†2021.

R. V. Klyuev et al., “Methods of Forecasting Electric Energy Consumption: A Literature Review,†Energies (Basel), vol. 15, no. 23, Dec. 2022, doi: 10.3390/en15238919.

Nurjanah and I, “Prakiraan Kebutuhan Energi Listrik Tahun 2016 – 2020 Pada PT. PLN (Persero) Unit Area Pelayanan Dan Jaringan (APJ) Tegal Dengan Metode Gabungan,†2016.

R. Septyawan, “Analisis Peramalan Kebutuhan Energi Listrik PLN Area Batam Menggunakan Metode Regresi Linear,†Jurnal Universitas Islam Indonesia, 2018.

Downloads

Published

2024-06-19

Issue

Vol. 2 No. 1: June 2024

Section

Articles

License

Copyright (c) 2024 Telecommunications, Computers, and Electricals Engineering Journal (TELECTRICAL)

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors who publish with this journal agree to the following terms:

  • Copyright of the published articles will be transferred to the journal as the publisher of the manuscripts. Therefore, the author confirms that the copyright has been managed by the publisher.
  • Publisher of TELECTRICAL is  Universitas Tanjungpura.
  • The copyright follows Creative Commons Attribution"“ShareAlike License (CC BY SA): This license allows to Share  "” copy and redistribute the material in any medium or format, Adapt  "” remix, transform, and build upon the material, for any purpose, even commercially.

Telecommunications, Computers, and Electricals Engineering Journal  by Universitas Tanjungpura is licensed under    CC BY-SA 4.0