Pratiwi, Galih Cahyaning (2020) OPTIMALISASI FORECASTING PEMBEBANAN GARDU INDUK JEMBER MENGGUNAKAN PERBANDINGAN METODE TIME SERIES DAN FUZZY SEBAGAI DASAR UPRATING TRAFO. Undergraduate thesis, Universitas Muhammadiyah Jember.
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Abstract
Long-term load forecasting in the power industries is importance, as it provides the industries with future power demand that be useful in generating, transmitting, and distributing power reliably and economically. In recent times, many techniques have been used in load forecasting, there is conventional techniques (time series and regression) and artificial intelligence tecjniques (fuzzy and artificial neural network). In this paper, a time series and fuzzy logic model for long-term load forecasting is presented be compared accurate level before long-term load forecasting. Time series model is developed based on historical load data substation Jember, while fuzzy model is developed based on increase in population, education infrastructure, health infrastructure and historical load data substation Jember. For 2 model used to forecasting in the year of the research, and compared accurate level to load forecasting in 2019-2027. The result obtained shows that the proposed 2 model, fuzzy model more accurate. The result forecasting analysis shows that the transformator I near the maximum limit in 2024 with load 42,9MVA, the transformator II unknown for near the maximum limit, the transformator III near the maximum limit in 2023 with load 47,5MVA, and the transformator IV near the maximum limit in 2021 with load 43,5MVA. Key Words : load forecasting, fuzzy, time series, uprating transformator.
| Item Type: | Thesis (Undergraduate) |
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| Subjects: | 600 Technology and Applied Science > 620 Engineering > 629 Other Branches of Engineering |
| Divisions: | Faculty of Engineering > Department of Electronics Engineering (S1) |
| Depositing User: | PRATIWI GALIH CAHYANING |
| Date Deposited: | 29 Feb 2020 04:37 |
| Last Modified: | 29 Feb 2020 04:38 |
| URI: | http://repository.unmuhjember.ac.id/id/eprint/3701 |
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