Electrical Grid Stability Prediction using Machine Learning Algorithms

Abstract

Machine learning (ML) is a technique that helps applications makes accurate predictions by using input to predict output values. There are various ML models that provide different results, each representing an alternative to other models with the goal of improving prediction performance. ML is used in different fields to provide good predictions and make the right decisions based on the subject. The current application of ML is predicting electricity grid stability, which aims to forecast problems that may arise in the grid when renewable energy is used, or when electricity production is insufficient to meet consumer needs. This prediction is based on the Dataset a processed and simulated input dataset that has been used by various ML models. Ultimately, the best ML model will be selected for accurate prediction.