Energy Forecasting and Time Series Analysis Using Machine Learning

Abstract

We have moved from lacking a sufficient supply of electricity/power to producing it in abundance, so it is paramount to decipher how to bring it to optimal usage. This research lays a hand on forecasting energy, bringing in the consumption of electricity and city across the households, enabling stakeholders to accurately predict future energy consumption and generation and meet the demand to enhance sustainable practices. This research examines various Machine Learning algorithms and the very essence of Time Series Forecasting. Forecasting can be done in different span/time intervals as required but eventually depends on factors such as managing the load, trading electricity, and optimizing energy storage, which is crucial for strategic planning and helps to identify trends influenced by economic and social factors. Considering how we are moving forward, having Power System Forecasting is essential to make the optimal use of our resources, and with the generated data, using the approach of Machine Learning and Forecasting to understand the pattern can make a difference.