Long-term forecasting for growth of electricity load based on customer sectors
The availability of electrical energy is an important issue. Along with the growth of the human population, electrical energy also increases. This study addresses problems in the operation of the electric power system. One of the problems that occur is the power imbalance due to scale growth between...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Indonesian Institute of Sciences
2022-12-01
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| Series: | Journal of Mechatronics, Electrical Power, and Vehicular Technology |
| Subjects: | |
| Online Access: | https://mev.lipi.go.id/mev/article/view/580 |
| _version_ | 1797952282881425408 |
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| author | Sujito Sujito Ridho Riski Hadi Langlang Gumilar Abdullah Iskandar Syah Moh. Zainul Falah Tran Huy Duy |
| author_facet | Sujito Sujito Ridho Riski Hadi Langlang Gumilar Abdullah Iskandar Syah Moh. Zainul Falah Tran Huy Duy |
| author_sort | Sujito Sujito |
| collection | DOAJ |
| description | The availability of electrical energy is an important issue. Along with the growth of the human population, electrical energy also increases. This study addresses problems in the operation of the electric power system. One of the problems that occur is the power imbalance due to scale growth between demand and generation. Alternative countermeasures that can be done are to prepare for the possibility that will occur in the future or what we are familiar with forecasting. Forecasting using the multiple linear regression method with this research variable assumes the household sector, business, industry, and public sectors, and is considered by the influence of population, gross regional domestic product, and District Minimum Wage. In forecasting, it is necessary to evaluate the accuracy using mean absolute percentage error (MAPE). MAPE evaluation results show a value of 0.142 % in the household sector, 0.085 % in the business sector, 1.983 % in the industrial sector, and 0.131 % in the total customer sector. |
| first_indexed | 2024-04-10T22:43:52Z |
| format | Article |
| id | doaj.art-69be5763472341cab0592995b362d161 |
| institution | Directory Open Access Journal |
| issn | 2087-3379 2088-6985 |
| language | English |
| last_indexed | 2024-04-10T22:43:52Z |
| publishDate | 2022-12-01 |
| publisher | Indonesian Institute of Sciences |
| record_format | Article |
| series | Journal of Mechatronics, Electrical Power, and Vehicular Technology |
| spelling | doaj.art-69be5763472341cab0592995b362d1612023-01-15T16:43:09ZengIndonesian Institute of SciencesJournal of Mechatronics, Electrical Power, and Vehicular Technology2087-33792088-69852022-12-0113221422110.14203/j.mev.2022.v13.214-221297Long-term forecasting for growth of electricity load based on customer sectorsSujito Sujito0Ridho Riski Hadi1Langlang Gumilar2Abdullah Iskandar Syah3Moh. Zainul FalahTran Huy Duy4State University of MalangElectrical Engineering, Electrical Engineering Department, Universitas Negeri MalangIntelligent Power and Advance Energy System, Jurusan Teknik Elektro, Universitas Negeri MalangElectrical Engineering, Electrical Engineering Department, Universitas Negeri MalangElectrical Engineering Department, Dalat University, VietnamThe availability of electrical energy is an important issue. Along with the growth of the human population, electrical energy also increases. This study addresses problems in the operation of the electric power system. One of the problems that occur is the power imbalance due to scale growth between demand and generation. Alternative countermeasures that can be done are to prepare for the possibility that will occur in the future or what we are familiar with forecasting. Forecasting using the multiple linear regression method with this research variable assumes the household sector, business, industry, and public sectors, and is considered by the influence of population, gross regional domestic product, and District Minimum Wage. In forecasting, it is necessary to evaluate the accuracy using mean absolute percentage error (MAPE). MAPE evaluation results show a value of 0.142 % in the household sector, 0.085 % in the business sector, 1.983 % in the industrial sector, and 0.131 % in the total customer sector.https://mev.lipi.go.id/mev/article/view/580district minimum wagegross regional domestic productlong-term forecastingmean absolute percentage errormultiple linear regression. |
| spellingShingle | Sujito Sujito Ridho Riski Hadi Langlang Gumilar Abdullah Iskandar Syah Moh. Zainul Falah Tran Huy Duy Long-term forecasting for growth of electricity load based on customer sectors Journal of Mechatronics, Electrical Power, and Vehicular Technology district minimum wage gross regional domestic product long-term forecasting mean absolute percentage error multiple linear regression. |
| title | Long-term forecasting for growth of electricity load based on customer sectors |
| title_full | Long-term forecasting for growth of electricity load based on customer sectors |
| title_fullStr | Long-term forecasting for growth of electricity load based on customer sectors |
| title_full_unstemmed | Long-term forecasting for growth of electricity load based on customer sectors |
| title_short | Long-term forecasting for growth of electricity load based on customer sectors |
| title_sort | long term forecasting for growth of electricity load based on customer sectors |
| topic | district minimum wage gross regional domestic product long-term forecasting mean absolute percentage error multiple linear regression. |
| url | https://mev.lipi.go.id/mev/article/view/580 |
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