Electricity Load Forecasting Using RNN

Recurrent Neural Network (RNN) based forecasting mechanisms have proved their significance to anticipate in perioperative outcomes to improve the decision making on the future course of actions. The RNN models have long been used in many application domains which needed the identification and prioritization of adverse factors. Several prediction methods are being popularly used to handle forecasting problems. This method demonstrates the capability of RNN model to forecast the electricity load of upcoming days from a city which can be considered to increase or decrease the generation of load. Our proposed method integrates a numeral of approach, intended to advance the cooperativeness of the explore operation. In this work, we develop the project of electricity forecast which can be able to predict outcomes of total load consumed.

KEYWORDS: Electricity, Total load forecast, RNN