ASHRAE Journal - October 2021 - 68

ASHRAE TECHNOLOGY AWARD CASE STUDIES
time, based on the latest cooling load and the weather
conditions. A key feature of the algorithm is that in
determining the optimal control settings, it can evaluate
all possible combinations of equipment and control
settings to ensure the minimum energy use of the chiller
plant at all times.
Once the optimal control settings are found, it is sent
back to the building management system (BMS) for
immediate implementation to continuously minimize
the energy consumption of the whole chiller plant.
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Comparison Between Dynamic (PGML-Model-Based)
And Traditional Optimization in Chiller Plants
The dynamic (PGML-model-based) optimization can
bring the following advantages:
* The equipment deterioration
is one of the factors considered for
dynamic optimization;
* All control variables are
taken into account for real-time
optimization (including the control
variables of chillers, cooling towers
and chilled water and condensing
pumps); and
* Data-driven optimization can
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be adaptive to any sudden changes
(the real-time optimization can still
be performed if some chillers have
sudden faults or are under maintenance).
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Operation and Maintenance
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68
ASHRAE JOURNAL ashrae.o rg O CTO B E R 2 0 2 1
Discover Unnoticed Faults
Unlike traditional fault detection
and diagnosis (FDD), our AFDD
focuses on the detection of the
unnoticed faults such as equipment
deterioration and control instability.
Figure 2 shows the detection of
hunting in an AHU control valve.
The magnitude of oscillation was
also evaluated to assess the severity
of its impact on the HVAC system.
2021
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ASHRAE Journal - October 2021

Table of Contents for the Digital Edition of ASHRAE Journal - October 2021
