learning hvac interim
TRANSCRIPT
Timothy M. Dockins – University of Texas at Arlington
research funded by NSF Grant CNS-0649229
Growing concern over high energy cost and usage of fossil fuels
Lack of cohesive plan in the US to manage the use of fossil fuels
Federal regulation at the producer end is not solving the problem
Apply technology at both consumer and producer level
A layman’s control strategy may not be optimal
31%
Design a system that can learn the dynamics of a residential home and it’s occupants and develop an optimal control strategy to accomplish the following objectives simultaneously:
Minimize cost of running HVAC equipment Maximize the comfort of the occupants
taking multiple occupants into consideration
Thermal Comfort: Standards Predictive Mean Vote – Fanger ISO 7730
Thermal Control: General PID, Adaptive Recovery, etc
Thermal Control: Machine Learning Approaches Artificial Neural Networks Fuzzy Systems Evolutionary Algorithms Brain Emotional Learning
Glue: Generalized Predictive Control Machine Learning techniques applied to various points of
prediction▪ NN for occupancy prediction, NNARX for temperature prediction▪ Fuzzy logic system for thermal comfort prediction
u u u u u u u u u u u u
120 minutes
10 minutes
time
horizon
}1|0{ onoffu 4096 permutations
t0
kt
t ttkUuxcue
ku 0
0 1)()(1limminargˆ
Outdoortemperature
sensor
OccupancySensors
ThermalSpaceModel
HomeOccupancyPredictor
Thermal SensationModel
PredictiveOptimalController
environment controller
HVAC
energy cost
comfort cost
AirTemperature
RadiantTemperature
AirVelocity
RelativeHumidity
CClothing
Level
CActivity
Level
Outdoortemperature
sensor
OccupancySensors
ThermalSpaceModel
HomeOccupancyPredictor
Thermal SensationModel
PredictiveOptimalController
environment controller
HVAC
energy cost
com
fort
cost
AirTemperature
RadiantTemperature
AirVelocity
RelativeHumidity
CClothing
Level
CActivity
Level
occupants
Single occupant’s thermal sensation modeled and predicted using a fuzzy system
Combine multiple occupant models using fuzzy logic
Neutral*CoolWarm
21 PP