ME 4343 HVAC Design

Real-Time Building Energy Modeling and Fault Detection and Diagnostics for

a DoD BuildingBing Dong1, Zheng O’Neill2

1 University of Texas, San Antonio, TX, USA2 University of Alabama, AL, USA

The work was done at the United Technologies Research Center

Introduction

• Motivation

Source: NBI report 2008 Energy Performance of LEED For New Construction Buildings

Introduction

• HVAC systems consume >20% more energy than design intent – Equipment performance degradation, and interact with other systems.– Existing control and information systems do not make visible system

level energy consumption.

• Need for a scalable building energy management system that includes whole building energy diagnostics and visualization

– Better HVAC operational controls and energy diagnostics– Raises the visibility of energy performance to help decision making

Building Facts

• Each 150K sf2 Barrack– Compartments, classrooms and

cafeteria/galley• Cooling

– Two absorption chiller: 450 ton – Chilled water loop with fixed-speed

primary pump• Heating

– Steam from the base wide central heating plant

– steam to water heat exchanger• 5 AHUs for each building• More than 200 VAV boxes with reheat

coil• A distributed Direct Digital Control

System (DDC)4

7114

7113

Technology Approaches

5

Core Layer: BIM-based DatabaseBIM to BEM Real-time Data Acquisition

Application Layer: Real-time energy simulation, visualization and diagnostics

BIM BasedDatabase

00:00 06:00 12:00 18:00 00:000

200

400

600

800

1000

BLD

G7114 W

ate

r S

ide L

oad (

kW

)

SimulatedMeasured

03:00 06:00 09:00 12:00 15:00 18:00 21:00

-0.1

0

0.1

BLD

G7114 W

ate

r S

ide L

oad (

kW

)

Energy Visualization

Building Reference Model

Energy Diagnostics

PC Running Integrated infrastructurePC Running EMS

BACnetGate Way

Ethernet

HVAC Lighting Weather

Core Applications

BCVTB

Revit

• Overview of the Integrated Infrastructure

Technology Approaches

• Integrated Energy Modeling Approach

Tosur Tisur Tamb Tzone

C

1/hiA 1/hoA R Qsurfi Qsurfo

C

Qstructure

Rwin

BIM Database

y = 6.4017x2 - 331.03x + 3355.6R² = 0.9715

0

5000

10000

15000

20000

25000

30000

35000

40000

0 10 20 30 40 50 60 70 80 90 100

Fan

Pow

er (w

)

Fan Speed (%)

Fan SpeedMeasured PowerPoly. (Fan Speed)

Envelope Model

HVAC Equipment Models

Calibration

Calibration

Total PumpsCooling Tower Fans

AHU Supply

Fans

AHU Return

Fans

Exhaust Fans

Dev -5% -4% -13% -4% -3% -12%

-25%

-20%

-15%

-10%

-5%

0%

Elec

tric

Ene

rgy

Dev

iatio

n

Target ±10% at rated conditions

Model Integration

and Validation

Architectural Model

Mechanical Model

Real-Time Data Acquisition

Technology Approaches

7

BIM to BEM automatic code generation

Traditional Approach

Building 7114 Architectural Model

Building 7114 Mechanical Model

Tosur Tisur Tamb Tzone

C

1/hiA 1/hoA R Qsurfi Qsurfo

C

Qstructure

Rwin

BEM (Thermal Network Model)

One Week

Technology Approaches

8

BIM to BEM automatic code generation

Automatic data extract

IFC BIM Database

Automatic data extract

BEMInput files

Building 7114 Architectural Model

Tosur Tisur Tamb Tzone

C

1/hiA 1/hoA R Qsurfi Qsurfo

C

Qstructure

Rwin

BEM (Thermal Network Model)

Building 7114 Mechanical Model

Our ApproachTraditional Approach

Building 7114 Architectural Model

Building 7114 Mechanical Model

Tosur Tisur Tamb Tzone

C

1/hiA 1/hoA R Qsurfi Qsurfo

C

Qstructure

Rwin

BEM (Thermal Network Model)

One Week < 5 minutes!!

gbXML

Technology Approaches

9

Real-time Data Acquisition

Simens EMSOur DAQ

sleeping area

cafeteria classroom

Outside view

Naval Station Great Lakes (Bldg 7114) Extend BCVTB BACnet actors: 1) BACnet reader utility:

Automatically generate a.xml configuration file and a .csv point description file based on the file created by Simens EMS

2) StoreBACnetDatatoBIMDatabase: Based on the .csv file, automatically create SQL statements based on the raw data received from EMS

3) DatabaseManager Establish the connection between BCVTB and BIM-

based database

Building Control Virtual Test Bed (BCVTB)

10

Results

Real-time Energy Performance Visualization

Building Hierarchy Interface

Time-Series Energy Flows Interface

Energy Statistics Pie Chart Interface

Results

11

Real-time Energy Simulation

1,_1, raz TQ

2,_2 , raz TQ

3,_3 , raz TQ

4,_4 , raz TQ

raz TQ _,

fanQ

fanQ

exam _

rmam _

mixamT _, ambamT _,

HCQ CCQ

samT _,

1

1

5

3

2

4

4

swmT _, rwmT _,

ram _

5

2

2

3

3

56

8

3

6

Zone modeSupply/Return fanMixed airEconomizerHeating coilCooling coil

8 Zone reheat coil

7

7 DAT set-point

9

10

9 Secondary loop pumps10 Bypasss loop

11

11 Primary loop pumps

12

12 Hotwater loop pumps

13

13 Chiller S/R water temp14

14 Condenser pumps

15

15 Cooling tower

07/06 07/07 07/08 07/09 07/10 07/110

500

1000

BLD

G71

14 W

ater

Sid

e Lo

ad (

kW)

SimulatedMeasured

07/07 07/08 07/09 07/10 07/11

-0.1

-0.05

0

0.05

0.1

Inst

ant E

rror

Building 7114 AHU3 secondary and primary system diagram

Building 7114 Real-Time Simulation Results from 07/06/2011 to 07/11/2011.

Results

OAT

AHU energy

OAD

Airflow

Damper

Valve

AHU network1,_1, raz TQ

2,_2 , raz TQ

3,_3 , raz TQ

4,_4 , raz TQ

raz TQ _,

fanQ

fanQ

exam _

rmam _

mixamT _, ambamT _,

HCQCCQ

samT _,

1

1

5

32

4

4

swmT _, rwmT _,

ram _

5

2

2

3

3

56

8

3

6

Zone modeSupply/Return fanMixed airEconomizerHeating coilCooling coil

8 Zone reheat coil

7

7 Discharge air temp set-point

Reference ROM

Building Operation data

Train

Inference

Energy Impact

07/21 07/26 07/31

55

60

65

70

75

80

85

90

95

100

Times

Tem

pera

ture

(F

) /

Dam

per

Pos

ition

(%

)

MAT

OA Damper

DATDATS

OAT

Operation data

OA damper 100%

DAT setpoint cannot be maintained

07/17 07/24 07/31

0.4

0.6

0.8

1OA Damper Position

07/17 07/24 07/310

500

1000

Anomaly Score

07/17 07/24 07/31

0.4

0.6

0.8

1OA Damper Position

07/17 07/24 07/310

500

1000

Anomaly Score

Actual

Expected

Building 7114

Building 7114 Energy Diagnostics: Economizer fault identified and corrected

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

B711

4 CH

W A

vera

ge B

TU/h

rOAT BINS (F)

With Faults

Faults Corrected

Economizer faults: Enthalpy calculation in control sequences is wrong

Faults was corrected on Aug 3rd , 2011. Measured chilled water energy consumption shows 18% savings were achieved

Conclusion

• This study has demonstrated an integrated infrastructure which integrates design information, database and real-time data acquisition in a real building to support energy modeling, visualization and FDD.

13

Observations and Lessons learned: • Manually mapping BMS points of each HVAC component. • The designed control logic in the HVAC control system is usually different from what is actually implemented locally. Communication with field people is necessary to get an accurate baseline model.

• Acknowledgements:– DoD ESTCP program manager: Dr. Jim Galvin– UTRC: Dong Luo, Madhusudana, Shashanka ,Sunil Ahuja, Trevor

Bailey– Naval Station Great Lakes

• Energy manager: Peter Behrens• Mechanical Engineer: Kirk Brandys• Facility team

• Questions?

14

Thank you!