Energy efficiency is crucial for the oil and gas industry, where operational costs and environmental impact are under constant scrutiny. Predicting and managing electrical consumption and peak demand accurately, especially with the variability of weather conditions, is a significant challenge. This work presents a neural network model trained on historical weather and electrical data to forecast electrical consumption, peak demand, and power factor.
Daniel Mawunyo Doe, Prabhu Srinivasan, Shane Pollock, Huzeifa Ismail
