With the increase in technological advancement, the need for an energy conservation system is increasing. It is necessary to build an effective and predictive system now that existing energy consumption models emphasize on and forecast accuracy. Consumption of energy has increased many folds and now has become a concerning issue. The utilization of energy has increased with human development and growth. The main reasons for these problems are uncontrolled power usage, including excessive consumption, lack of optimal design, and energy wastage. The purpose of this work is to predict the future trend in power usage for any system that monitors and requires this information in real-time. The best model to accomplish this goal was evaluated using recurrent neural networks (RNN) and long short-term memory (LSTM). Results from experiments demonstrate great accuracy and require fewer computer resources during model training than competing models.

Keywords : Power Consumption, Short-term load forecasting, electricity markets, spot prices, Recurrent Neural Networks (RNN).