Penerapan Jaringan Syaraf Tiruan Untuk Prediksi Daya Fotovoltaik Dengan Boost Converter - KUNCORO, BAGUS TRI (Sekolah Tinggi Teknologi Ronggolawe Cepu, 2024)
The power system must be planned and operated with an estimate of the optimal photovoltaic output power. Direct sunlight can be converted into electrical energy using photovoltaic (PV) technology. The amount of electrical energy produced by solar modules can be influenced by the amount of sunlight it receives. This study discusses the simulation of the prediction of the output power of a photovoltaic system and boost converter with MPPT, in the next 1 hour using the backpropagation artificial neural network (ANN) method approach. In this study, the learning rate used is 0.01 and the minimum error target is 0.001 with 5 predetermined network architectures. The best performance prediction results with the smallest Mean Squared Error (MSE) value were obtained with the backpropagation neural network structure of the 4-6-1 model which was almost close to its actual value, but further research is still needed so that the prediction results can be even better.