A Fault Detection and Diagnostics (FDD) tool is a type of energy management and information system that is designed to continuously identify the presence of faults and efficiency improvement opportunities through a 1-way interface to the building automation system and application of automated analytics. It is estimated that 5-30% energy saving can be achieved by employing FDD tools and implementing efficiency measures based on FDD findings. Although the potential of this technology is high, actual savings are only realized when an operator takes an action to fix the problem. There is a subset of faults that can be potentially addressed automatically by the system, without operator intervention. Automating this fault "correction" can significantly increase the savings generated by FDD tools and reduce the reliance on human intervention.
This paper presents preliminary efforts towards delivering automated fault correction. It describes nine fault auto-correction algorithms for heating ventilation and air conditioning (HVAC) systems that were developed to automatically correct faults or improve controls operation. It also presents preliminary testing results of one auto-correction algorithm (improve air handling unit static pressure setpoint reset) in a commercial building, located in Berkeley, California, US. The auto-correction algorithms and implementation frameworks of this initial study provide a foundation for future auto-correction algorithm development and novel schemes for improving building operation performance and reliability.
BT - The 6th International High Performance Buildings Conference at Purdue DA - 05/2021 LA - eng N2 -A Fault Detection and Diagnostics (FDD) tool is a type of energy management and information system that is designed to continuously identify the presence of faults and efficiency improvement opportunities through a 1-way interface to the building automation system and application of automated analytics. It is estimated that 5-30% energy saving can be achieved by employing FDD tools and implementing efficiency measures based on FDD findings. Although the potential of this technology is high, actual savings are only realized when an operator takes an action to fix the problem. There is a subset of faults that can be potentially addressed automatically by the system, without operator intervention. Automating this fault "correction" can significantly increase the savings generated by FDD tools and reduce the reliance on human intervention.
This paper presents preliminary efforts towards delivering automated fault correction. It describes nine fault auto-correction algorithms for heating ventilation and air conditioning (HVAC) systems that were developed to automatically correct faults or improve controls operation. It also presents preliminary testing results of one auto-correction algorithm (improve air handling unit static pressure setpoint reset) in a commercial building, located in Berkeley, California, US. The auto-correction algorithms and implementation frameworks of this initial study provide a foundation for future auto-correction algorithm development and novel schemes for improving building operation performance and reliability.
PY - 2021 T2 - The 6th International High Performance Buildings Conference at Purdue T3 - The 6th International High Performance Buildings Conference at Purdue TI - Fault “Auto-correction” for HVAC Systems: A Preliminary Study ER -