Abstract
Faults in buildings systems affect energy efficiency and occupancy comfort. Simulating building behavior and comparing it with measured data allows to detect discrepancies due to faults. We propose a methodology to recursively compare actual data with dynamic energy simulations at different layers of aggregation to reduce the scope in searching for faults through the development the Online Energy Simulator, a tool to set up automated simulations using standard interfaces usable with different building systems and simulation engines. We test our simulator on a real building at the University of Southern Denmark, showing how continuous monitoring allows to quickly detect and identify buildings faults.
Highlights
Buildings are responsible for a large portion of energy consumption
We propose a methodology to recursively compare actual data with dynamic energy simulations at different layers of aggregation to reduce the scope in searching for faults through the development the Online Energy Simulator, a tool to set up automated simulations using standard interfaces usable with different building systems and simulation engines
In this article we propose a methodology for fault detection and diagnostics (FDD) in buildings using energy models simulations and comparing with real building at different aggregation layers
Summary
Buildings are responsible for a large portion of energy consumption. In the USA they accounted for 7% of primary energy consumption in 2010, which is more than transportation and industrial sector. Buildings energy consumption is rapidly increasing over time, doubling from 1290 TWh in 1980 to 2784 TWh in 2010 [1]. Modern buildings have complex control systems that monitor the current status and manage heating, cooling, ventilation and lighting. Each one of these subsystems has increasing complexity, and can, suffer from faults and malfunctions. It is estimated that in 2009 the most common faults in USA commercial buildings were responsible for over $3.3 billion in energy waste [5]
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