Lecture Objectives: -Discuss the final project presentations -Energy simulation result evaluation -Review the course topics.

Lecture Objectives:

- Discuss the final project presentations

- Energy simulation result evaluation

- Review the course topics

Oral presentation

• On Thursday class will start at 8:30 am– We will have some guests UTs

• PowerPoint (6-7 minutes presentation)– Upload the file before the class

• Approximately 6-7 slides (a minute per slide)– Problem introduction – Model development - specific problem– Results – Results – Discussion– Conclusions

Today Lab Demo Class

• 5:30 PM in ECJ 3.402

• Beopt Software – Energy Plus GUI

Presenter: Joshua Rhodes

How to evaluate the simulation tools

Two options:

1) Comparison with the experimental data - monitoring

- very expensive- feasible only for smaller buildings

2) Comparison with other energy simulation programs- for the same input data

- system of numerical experiments - BESTEST

Comparison with measured data

Cranfield test rooms (from Lomas et al 1994a)

BESTEST Building Energy Simulation TEST

• System of tests (~ 40 cases) - Each test emphasizes certain phenomena like

external (internal) convection, radiation, ground contact

- Simple geometry- Mountain climate

6 m

2.7 m

3 m

8 m

0.2 m

0.2 m

1 m

2 m

S

N

E

W

COMPARE THE RESULTS

Example of best test comparison

BESTEST test cases

0

2000

4000

6000

8000

10000

12000

195 200 220 230 240 270

Annual heating load [kWH]

new ES prog

ESP

BLAST

DOE2

SRES/SUN

SRES-BRE

S3PAS

TRYNSYS

TASE

BESTEST

http://www.nrel.gov/docs/legosti/old/6231.pdf

http://www.nrel.gov/analysis/

Advance Energy Modeling with coupled

energy and airflow Example: Night Cooling/Hybrid Ventilation

The IONICA Office Building, Cambridge, UK

Night Cooling/Hybrid Ventilation:The IONICA Office Building, Cambridge, UK

Night Cooling/Hybrid Ventilation:

Requires combined Energy and airflow modeling

Night Cooling/Hybrid Ventilation:The IONICA Office Building, Cambridge, UK

Feasibility of natural ventilationFigure 1- Hourly internal temperature distribution according to strategy used

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

base-case external insulation mech. vent. 15ach/int.ins.

mv/ii/south shading mech. vent. 15ach/ext.ins.

mv 15ach/ei/southshading

ho

urs

18-21.1

21.1-23.9

23.9-26.7

26.7-29.4

above 29.4

oC

Example of non-uniform temperature distribution with DV

Energy and Airflow simulation domain

Coupling surfaces

Coupling

EnergySimulationProgram

Air FlowProgram IAQData:

geometryweather

materials

Twall, CFM, Tsupply

Tnear surface, h surface

V,T,…

Energy cons.

Coupling

ESprogram

CFDprogram

(converged)(converged)

CFDprogram

(converged)

ESprogram

controlled parameters m su pp ly and T Tsup ply s ur fac eor

T surfaces

controlled parameters m su pp ly and T Tsu pp ly su rf aceor

T surfaces

satisfactorysmall error

Time s tep Time step

ha dj.c ell , Ta dj.c ell ha dj.c ell , Ta dj.c ell

ES CFD

Onion

ESprogram

CFDprogram

(converged)(converged)

CFDprogram

(converged)

ESprogram

controlled parameters m su pp ly and T Tsup ply s ur fac eor

T surfaces

controlled parameters m su pp ly and T Tsu pp ly su rf aceor

T surfaces

ha dj.c ell , Ta dj.c ell

Time step Time step

ES CFD

Ping-Pong

COUPLED PROGRAM Components and Data flow

GUIPREPROCESSOR

ESPROGRAM

CFDPROGRAM

CFDinputdata(txt)

Convectionb.c. for ES

(txt)TMY2wether

data (txt)

CFDG UI

postprocessor

ESG UI

p ostprocessor

Inputdata for

CFDandES(txt)

call

data flo w

call

ca

ll

ca

ll

call

data flowcall

data flow

ESoutputdata(txt)

CFDoutputdata(txt)

convergency control

Postprocessor Output

Preprocessor Solver

results

results

EnergyEnergy & Buildings

• Conduction (and accumulation) solution method – finite dif (explicit, implicit), response functions

• Time steps • Meteorological data• Radiation and convection models (extern. &

intern.) • Windows and shading• Infiltration models• Conduction to the ground• HVAC and control models

Accuracy of Your Energy Simulation

• Depends primarily on your input data!

• Geometry• Boundary condition• Selected models • Set points• Control• Internal loads and schedule

Building Modeling Software

Very powerful tool

Use it wisely!

Simulation SoftwareGarbage IN Garbage OUT

but

1. Identify basic building elements which affect building energy consumption and analyze the performance of these elements using energy conservation models.

2. Analyze the physics behind various numerical tools used for solving different heat transfer problems in building elements.

3. Use basic numerical methods for solving systems of linear and nonlinear equations.

4. Conduct building energy analysis using comprehensive computer simulation tools.

5. Evaluate the performance of building envelope and environmental systems considering energy consumption.

6. Perform parametric analysis to evaluate the effects of design choices and operational strategies of building systems on building energy use.

7. Use building simulations in life-cycle cost analyses for selection of energy-efficient building components.

Review Course Objectives