Analysis with Machine Learning Algorithms to Estimate Power Factor in an Electrical Network

In this paper we explore the use of machine learning algorithms to accurately estimate the power factor in power grids. The power factor is crucial for an efficient operation of power grids, and its accurate estimation is a major challenge. The analysis of the problem is performed using machine learning, Random Forest and Neural Networks algorithms. Several characteristics and input variables such as voltage, current and power that can influence the estimation were analyzed. We used real data sets taken over a period of one week to support our results and compare the performance of the proposed algorithms with conventional methods. The results provide a comprehensive view on the effectiveness of machine learning algorithms in power factor estimation, as well as their practical implications in power grid management.