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Sensor errors greatly affect the performance of control, diagnosis, and optimization systems within building energy systems, negatively impacting energy efficiency. Virtual in-situ sensor calibration (VIC), a Bayesian theory based method, can improve building energy performance by calibrating erroneous sensors in working building energy systems on a large scale. Working sensors do not need to be removed...
Systematic and random errors of working sensors in building systems could significantly compromise the system's performance and thus indoor environmental quality. An extended virtual in-situ calibration has been suggested to solve problems regarding sensor errors and calibration. This calibration can correct these errors for all critical working sensors in building systems without removing working...
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