PERAMALAN JANGKA PENDEK ENERGI PLTS OFF GRID ITPLN DENGAN JARINGAN SYARAF TIRUAN
Total View This Week0
Total View This Week0
Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Farobi, Achmad
Yogianto, Aloysius Agus
Yogianto, Aloysius Agus
Subject
Teknik Elektro
Datestamp
2022-09-28 07:33:14
Abstract :
Solar energy is the largest alternative energy source that has great potential because the energy is easily available, especially in Indonesia and is environmentally friendly energy. Solar energy can be converted into electricity using a tool, namely a solar panel (photovoltaic). The use of solar panels in Indonesia today has developed a lot, one of which is in residential homes which are commonly used as a source of electricity for bathing water heaters or also used to supply daily electricity needs. Forecasting the energy output from photovoltaics needs to be done to determine the electrical energy generated from the photovoltaic so that there is no shortage or excess of electrical power so that optimal energy is obtained to be distributed to the load. The method used for forecasting photovoltaic power is Backpropagation Neural Network for the next 5 hours. The data used for forecasting is the ambient temperature and energy of PLTS taken for 3 consecutive days. In the study, the error value in forecasting was 0.000334%, namely when the measurement was at 12.00 and the largest value for the forecasting error was 24.322%, when the measurement was at 09.15. Then from the calculation of the error with the Mean Absolute Percentage Error method is 2.6158%, with the error it can be said that the results of forecasting with artificial neural network have a fairly good accuracy.
Solar energy is the largest alternative energy source that has great potential because the energy is easily available, especially in Indonesia and is environmentally friendly energy. Solar energy can be converted into electricity using a tool, namely a solar panel (photovoltaic). The use of solar panels in Indonesia today has developed a lot, one of which is in residential homes which are commonly used as a source of electricity for bathing water heaters or also used to supply daily electricity needs. Forecasting the energy output from photovoltaics needs to be done to determine the electrical energy generated from the photovoltaic so that there is no shortage or excess of electrical power so that optimal energy is obtained to be distributed to the load. The method used for forecasting photovoltaic power is Backpropagation Neural Network for the next 5 hours. The data used for forecasting is the ambient temperature and energy of PLTS taken for 3 consecutive days. In the study, the error value in forecasting was 0.000334%, namely when the measurement was at 12.00 and the largest value for the forecasting error was 24.322%, when the measurement was at 09.15. Then from the calculation of the error with the Mean Absolute Percentage Error method is 2.6158%, with the error it can be said that the results of forecasting with artificial neural network have a fairly good accuracy.
Download
book
BibTex
Latex, Jabref
cloud_download
Original Resource
url resource Institution
