Modeling of Energy Production of Sengguruh Hydropower Plant Using Neuro Fuzzy Network

Daniel Rohi, Hanny H. Tumbelaka


The hydroelectric power plant needs to be operated carefully to obtain optimal results, as it is highly dependent on water availability. Factors to take into account are the water discharge and the duration of time for the operation. Decomposition analysis method is the method chosen to manage the operation of hydropower. This paper discusses the hydropower operation model using artificial intelligence with Neuro Fuzzy Takagi-Sugeno (NFTS) network technique. The Hydropower plants selected for modeling is Sengguruh Hydroelectric Power Plant with a capacity of 29 MW. This model was developed using three factors as inputs. They are the discharge of water, turbine water discharge and duration of operation time. The output is electric energy production. The data used is the operating data for one year, from January to December. The model testing shows satisfactory results as it reveals the real conditions and the errors occurred on the network was below 6.7%.


Artificial Intelligence; Hydropower Plant; Neuro-fuzzy; Renewable Energy;

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