Large scale predictive analysis for real-time energy management

Abstract

In recent days consumption of energy is high. As population increases gradually, usage of power is also increasing. In this paper the energy management is predicted by using the LSTM Algorithm and to manage the real-time energy. The data is given in the form of data sets. It has been observed that large amount of energy required in future to train data depending on the consumed energy in future. It can observe training progress in the real time environment. To estimate future event in this paper considered energy consumed per day around 440 values and iterations are about 250. The results are validated by using MATLAB/Simulink.