Energy Management in Modern Buildings Based on Demand Prediction and Machine Learning—A Review
Seyed Morteza Moghimi, T. Aaron Gulliver, Ilamparithi Thirumai Chelvan
Abstract
Increasing building energy consumption has led to environmental and economic issues. Energy demand prediction (DP) aims to reduce energy use. Machine learning (ML) methods have been used to improve building energy consumption, but not all have performed well in terms of accuracy and efficiency. In this paper, these methods are examined and evaluated for modern building (MB) DP.
Topics & Concepts
Energy (signal processing)Energy managementEnergy demandArchitectural engineeringComputer scienceEngineeringEnvironmental economicsEconomicsMathematicsStatisticsBuilding Energy and Comfort OptimizationEnergy Load and Power ForecastingSmart Grid Energy Management