Optimized Annual State Electricity Consumption Prediction Using GWO-GNN

As we enter the new era of electrification, the demand for electricity is surging. Accurate forecasting of electricity consumption is important because it not only reduces production costs but also minimizes carbon emissions. Therefore, precise predictions of electricity consumption are imperative for both the economy and ecology. In this paper, we present a Grey Neural Network combined with a Grey Wolf Optimizer (GWO-GNN) to predict the annual state of electricity consumption. The performance of the model is better than the prevailing models in terms of average error value. The proposed methodology consistently demonstrates its exceptional ability to yield accurate predictions of electricity consumption across diverse data sets.