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Fault “Auto-correction” for HVAC Systems: A Preliminary Study

Publication Type

Conference Paper

Date Published

05/2021

Authors

Lin, Guanjing, Marco Pritoni, Yimin Chen, Christopher Weyandt, Raphael Vitti, Jessica Granderson

Abstract

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.

Journal

The 6th International High Performance Buildings Conference at Purdue

Year of Publication

2021