Prakiraan Beban Listrik Jangka Pendek Kota Banda Aceh Berbasis Logika Fuzzy

. Syukriyadin, Rio Syahputra

Abstract


One of the technical aspects that support the optimal operation planning of a power plant when viewed in
terms of system reliability and economic is about short-term load forecasting. The objective of this research is to
forcasting hourly short-term electric load peak (17:30 to 22:30 GMT) at loading area of Transmission Distribution
Banda Aceh Unit of PT. PLN P3B Aceh 150-20 kV by using Adaptive Neuro Fuzzy Inference System (ANFIS)
method. The toolbox used to predict short-term electric load in this research is by using MATLAB software R2007b
and Microsoft Excel 2007. ANFIS structure is trained using ANFIS Sugeno models, three types of membership
functions with three and four fuzzy sets for each type of membership function. ANFIS structure is trained using a
hybrid algorithm. From the simulation results obtained that the structure of the input membership functions of ANFIS
3 gbell with three fuzzy sets as the ideal structure. Further results of ANFIS estimation compared with the moving
average method. From the simulation results is shown that ANFIS models generate MAPE 3.42%, while the forecasts
using the moving average method generate MAPE 6.58%.


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DOI: https://doi.org/10.17529/jre.v10i1.149

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