Continuous Monitoring and Fault Detection Diagnosis of large HVAC systems (Heating, Ventilation and Air Conditioning)
The need to reduce CO2 emissions makes energy in the built environment a key issue given that inefficient buildings represent around 35% of the total energy consumption. Continuous Monitoring (CM) and Fault Detection and Diagnosis (FDD) are complex but important technologies in detecting inefficiencies in Heating Ventilation Air Conditioning (HVAC). With a rise in demand for cooling caused by global warming, this project is developing a new approach based on data analytics and machine learning. This will enable resulting CM and FDD modules to be programmed in a state-of-the-art Building Management System (BMS) and become market-ready by the end of the project.
General project problem description
Different assignments in the domain of data analytics, Machine Learning applications, energy analysis, fault detection, diagnosis, Condition based maintenance, energy flexibility, prediction models, battery storage.
