Monitoring HVAC and R performance degradation using relative COP from joint power and temperature relations
Systems and methods for monitoring an HVAC&R system employ a monitoring agent that uses observations of evaporator and condenser intake temperatures, evaporator discharge temperature, and a compressor input power parameter to learn operating characteristics of the HVAC&R system in newly maintained condition. Thereafter, the agent continuously or regularly computes a relative coefficient of performance (COP) for the system under subsequent observed ambient conditions, and relates the present instantaneous efficiency of the HVAC&R system under the observed ambient conditions to the instantaneous efficiency when the system was in newly maintained condition. The relative COP can be used to detect system degradation and quantify the energy usage and cost attributable to the degradation. The agent can take appropriate actions to prevent/minimize damage based on the degree of degradation detected, including shutting off power to the HVAC&R system. The monitoring agent can also be extended to other types of systems besides HVAC&R system.
1 . A monitoring system for an HV AC&R system, the monitoring system comprising:
one or more hardware processors and memory configured to execute:
a data acquisition process operable to acquire observations about the HVAC&R system, the observations including fluid temperature measurements for a condenser and fluid temperature measurements for an evaporator, the observations further including compressor input power parameter measurements corresponding to the fluid temperature measurements;
a joint compressor input power parameter (CIPP)/evaporator discharge temperature (ETD) process operable to learn a joint CIPP and ETD relation between fluid temperature measurements for an evaporator intake temperature and a condenser intake temperature, the compressor input power parameter measurements, and an evaporator temperature drop, the joint CIPP/ETD process configured to compute a predicted value for a compressor input power parameter using the joint CIPP and ETD relation, and compute a predicted value for the evaporator temperature drop using the joint CIPP and ETD relation;
a relative coefficient of performance (COP) process operable to compute a power parameter based relative coefficient of performance for the HV AC&R system based on the predicted value for the compressor input power parameter, or an evaporator temperature drop based relative coefficient of performance for the HVAC&R system based on the predicted value for the evaporator temperature drop, or both; and
a degradation detection process operable to receive the power parameter based relative coefficient of performance or the evaporator temperature drop based relative coefficient of performance from the relative COP process, or both, and is operable to shut off power to the HVAC&R system in response to the power parameter based relative coefficient of performance or the evaporator temperature drop based relative coefficient of performance, or both, exceeding one or more predefined thresholds.
2 . The monitoring system of claim 1 , wherein the degradation detection process is further operable to compute a cost factor attributable to the performance degradation using the evaporator temperature drop based coefficient of performance.
3 . The monitoring system of claim 1 , wherein the degradation detection process is further operable to determine that air flow occlusion is present in the HVAC&R system and issue a signal indicative of the air flow occlusion in response to the evaporator temperature drop based relative coefficient of performance exceeding the one or more predefined threshold.
4 . The monitoring system of claim 1 , wherein the degradation detection process is further operable to issue a signal indicative of a dirty air filter when air flow occlusion is present in the HVAC&R system.
5 . The monitoring system of claim 1 , wherein the relative COP process computes the power parameter based relative coefficient of performance at least by computing a ratio comprising a predicted value for the compressor input power parameter over a measured value of the compressor input power parameter, or wherein the relative COP process computes the evaporator temperature drop based relative coefficient of performance at least by computing a ratio comprising a measured value of the evaporator temperature drop over a predicted value of evaporator temperature drop.
6 . The monitoring system of claim 1 , wherein the observations acquired by the data acquisition process are stored, at the joint CIPP and ETD relation process, via a CIPP temperature map, each CIPP temperature map containing a plurality of cells, each cell corresponding to a condenser intake temperature and an evaporator intake temperature, each cell including summary statistics for measured values for the compressor input power parameter.
7 . The monitoring system of claim 1 , wherein the observations acquired by the data acquisition process are stored, at the joint CIPP and ETD relation process, via an ETD temperature map, each ETD temperature map containing a plurality of cells, each cell corresponding to a condenser intake temperature and an evaporator intake temperature, each cell including summary statistics for measurement derived values of the evaporator temperature drop.
8 . The monitoring system of claim 1 , wherein the data acquisition process, the joint CIPP and ETD process, the relative COP process, and the degradation detection process reside within an agent of the monitoring system, the agent comprising the ibe ir nire hardware processors and memory and is executed on one or more of the following: a cloud-based network, a fog-based network, and locally to the HVAC&R system.
9 . The monitoring system of claim 1 , further comprising a vapor-compression cycle (VCC) state generator operable to augment the observations acquired by the data acquisition process with system state information indicating (i) an ON/OFF state of the HVAC&R system, (ii) a suitability of the observations for learning and predicting compressor input power parameters, and (iii) a suitability of the observations for learning and predicting evaporator temperature drop.
10 . The monitoring system of claim 1 , wherein the joint CIPP and ETD process learn the joint CIPP and ETD relation using a machine learning based learning process.
11 . A method of monitoring an HV AC&R system, the method comprising:
acquiring, at a data acquisition processor, observations about the HVAC&R system, the observations including fluid temperature measurements for a condenser and fluid temperature measurements for an evaporator, the observations further including compressor input power parameter measurements corresponding to the fluid temperature measurements;
learning, at a joint compressor input power parameter (CIPP)/evaporator discharge temperature (ETD) processor, a joint CIPP and ETD relation between fluid temperature measurements for an evaporator intake temperature and a condenser intake temperature, the compressor input power parameter measurements, and an evaporator temperature drop, the joint CIPP/ETD processor configured to compute a predicted value for a compressor input power parameter using the joint CIPP and ETD relation, and compute a predicted value for the evaporator temperature drop using the joint CIPP and ETD relation;
computing, at a relative coefficient of performance (COP) processor, a power parameter based relative coefficient of performance for the HV AC&R system based on the predicted value for the compressor input power parameter, or an evaporator temperature drop based relative coefficient of performance for the HVAC&R system based on the predicted value for the evaporator temperature drop, or both; and
receiving, at a degradation detection processor, the power parameter based relative coefficient of performance or the evaporator temperature drop based relative coefficient of performance from the relative COP processor, or both, and shutting off power to the HVAC&R system in response to the power parameter based relative coefficient of performance or the evaporator temperature drop based relative coefficient of performance, or both, exceeding one or more predefined thresholds.
12 . The method of claim 11 , further comprising computing, at the degradation detection processor, a cost factor attributable to the performance degradation using the evaporator temperature drop based coefficient of performance.
13 . The method of claim 11 , further comprising shutting off, at the degradation detection processor, power to the HV AC&R system in response to the power parameter based relative coefficient of performance or the evaporator temperature drop based relative coefficient of performance, or both, exceeding the one or more predefined thresholds.
14 . The method of claim 11 , further comprising determining, at the degradation detection processor, that air flow occlusion is present in the HVAC&R system and issuing a signal indicative of the air flow occlusion in response to the evaporator temperature drop based relative coefficient of performance exceeding the one or more predefined thresholds.
15 . The method of claim 14 , further comprising issuing, at the degradation detection processor, a signal indicative of a dirty air filter when air flow occlusion is present in the HV AC&R system.
16 . The method of claim 11 , wherein the relative COP processor computes the power parameter based relative coefficient of performance at least by computing a ratio comprising a predicted value for the compressor input power parameter over a measured value of the compressor input power parameter, or wherein the relative COP processor computes the evaporator temperature drop based relative coefficient of performance at least by computing a ratio comprising a measured value of the evaporator temperature drop over a predicted value of evaporator temperature drop.
17 . The method of claim 11 , further comprising storing, at the joint CIPP and ETD relation processor, via a CIPP temperature map, the observations acquired by the data acquisition processor, each CIPP temperature map containing a plurality of cells, each cell corresponding to a condenser intake temperature and an evaporator intake temperature, each cell including summary statistics for measured values for the compressor input power parameter.
18 . The method of claim 11 , further comprising storing, at the joint CIPP and ETD relation processor, via an ETD temperature map, the observations acquired by the data acquisition processor, each ETD temperature map containing a plurality of cells, each cell corresponding to a condenser intake temperature and an evaporator intake temperature, each cell including summary statistics for measurement derived values of the evaporator temperature drop.
19 . The method of claim 11 , wherein the data acquisition processor, the joint CIPP and ETD processor, the relative COP processor, and the degradation detection processor reside within an agent of a monitoring system, the agent executed on one or more of the following:
a cloud-based network, a fog-based network, and locally to the HVAC&R system.
20 . The method of claim 11 , further comprising augmenting, at a vapor-compression cycle (VCC) state generator, the observations acquired by the data acquisition processor with system state information indicating (i) an ON/OFF state of the HV AC&R system, (ii) a suitability of the observations for learning and predicting compressor input power parameters, and (iii) a suitability of the observations for learning and predicting evaporator temperature drop.
21 . The method of claim 11 , wherein learning the joint CIPP and ETD relation by the joint CIPP and ETD is performed using a machine learning based learning process.
22 . A non-transitory computer-readable medium containing program logic that, when executed by operation of one or more computer processors, causes the one or more computer processors to perform a method according to claim 11 .