Algerian Journal of Renewable Energy and Sustainable Development
Volume 6, Numéro 2, Pages 205-215
2024-12-15
Using Machine Learning Algorithms In Home Energy Management Systems For Energy Cost Forecasting
Authors : Abderraouf Bouakkaz . Adel Lahsasna .
Abstract
Facing global energy challenges, as energy demand continues to increase significantly, businesses and individuals are increasingly exploring ways to optimize energy use to reduce costs and environmental impacts. Artificial intelligence (AI) has become a key tool for accomplishing these goals, offering innovative ways to monitor, analyse and optimize energy consumption, thereby reducing expenses and promoting sustainability. In this study, energy cost prediction across different seasons is explored using various machine learning regression models, including Linear Regression (LR), Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Networks (ANN). The performance and accuracy of each model were evaluated, with all implementations conducted using Python version 3.11.The paper aims to predict the cost of energy consumption, ultimately minimizing the total energy cost. The assessment of performance and the accuracy of these models are evaluated using the MSE metric, showing how machine learning can help reduce energy consumption and costs.
Keywords
Machine learning Energy management Cost of energy Energy consumption Prediction
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