Machine Learning Models for Energy Consumption Forecasting in Power Generation

The application of machine learning for power-related purposes represents a novel notion in artificial intelligence for predicting power generation. While prediction models are employed to forecast various global situations, their application in predicting energy-related themes will be distinctive and specialized. Scholars and AI engineers, in collaboration with professionals in the energy sector, are conducting investigations to develop AI models that assist in their work. Consequently, due to the distinct nature of the situation and the diversity of datasets, several AI models are chosen and built to aid in their tasks. This study examines the application of AI models for enhancing energy efficiency in power generating in Malaysia. A Linear Regression model and an Artificial Neural Network are developed to forecast future power consumption across various industries in Malaysia, compute the growth rate and average growth rate of the projected energy consumption, and identify a viable area for investment. It also formulates a power strategy based on the aggregate anticipated energy usage. Both models are developed, analyzed, and compared to ascertain the most suitable model for this scenario.