Lecture Objectives:

• Define the final project Deliverables and Grading policy

• Analyze factors that influence accuracy of our modeling study

• Learn about automatic control

Final project topics:Deliverables:1) Preliminary report : April 28 - 5% of your final report- Should includes

- model (matchcad, excel, … , or software file) and- 1 page that contains assumptions

2) Final report : May 7Report with complete analysis

3) Project defenseOral presentation:

- May 5 and May 7 in class, or - Sometime afternoon

Final project grading:• 20% Oral presentation

Written Report (80% of total project grade)• 20% Model and justification of assumptions • 20% Depth of analysis • 20% Completeness and accuracy• 20% Quality of writing and result presentation

Final report length: 5 pages, at lest 50% text.

Accuracy of Building Energy Simulation Tool

Large number of:

– Analytical – Numerical – Empirical

models

for energy and mass transfer calculation in building envelope and building systems

Modeling steps• Define the domain• Analyze the most important phenomena and

define the most important elements• Discretize the elements and define the

connection • Write the energy and mass balance equations• Solve the equations (use numeric methods or

solver)• Present the result

Accuracy of energy simulation

• There are many different factors for inaccuracy of energy simulation results

….....…….…….

Accuracy of energy simulation Depends on

2 Assumptions - simplification which you introduced to solve the problem- level of details in your analytical and numerical models

1 Input data– geometry– material properties – weather data – operation schedule

3 Numerical methods - used to solve equations from analytical and numerical models

Find the balance !Always think what you want to achieve (what kind of analysis you want to provide)

How to check the accuracyof numerical model?

Comparison wit existing analytical solutions

Ts

0

T

-L / 2 L /2

h

h

h

T o

T

h omogenous wa ll

L = 0.2 mk = 0 . 5 W/ m Kc = 9 20 J/kgK

= 120 0 k g/mp

2

0 1 2 3 4 5 6 7 8 9 100.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Analytical solution Numerical -3 nodes, =60 min Numerical -7 nodes, =60 min Numerical -7 nodes, =12 min

(T-T

s)/(T

o-Ts

)

hour

How to check the validity of the larger simulation models?

0 24 48 72 96 120 144 168 1920

50

100

150

200

250

300

350

400

Same Area

Q internal sources Q at control surface

Q [W

]

hour

Building room:large number of analytical and Numerical equations (sub-models)

Energy balance

How to evaluate the whole building 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

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

SN

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

What are the reasons for the energy simulation

• Design (sizing of different systems)

• Economic benefits

• Impact on environed

• Budget planning

Basic purpose of HVAC controlDaily, weekly, and seasonal swings make HVAC control challengingHighly unsteady-state environmentProvide balance of reasonable comfort at minimum cost and energy

Two distinct actions:1) Switching/Enabling: Manage availability

of plant according to schedule using timers.

2) Regulation: Match plant capacity to demand

Basic Control loopExample: Heat exchanger control

– Modulating (Analog) control

air

water

Cooling coil

(set point temperature)

x

Cooling coil control valve

Position (x)

fluid

Electric (pneumatic) motor

Vfluid = f(x) - linear or exponential function

Volume flow rate

The PID control algorithm

For our example of heating coil:

Proportional Integral Differential

time

Position (x)

constants

e(t) – difference between set point and measured value

dTTd

TKdTTTKTTKx di

)()()( measuredpointset

measuredpointset measuredpointset

Proportional(how much)

Integral(for how long)

Differential(how fast)

Position of the valve

The control in HVAC system – only PI

dTTTKTTKxi

)()( measuredpointset measuredpointset

Proportional Integral

Proportionalaffect the slope

Integralaffect the shape after the first “bump”

Set point

Set point

value

Detail control system simulationMatLAB - Simulink

Control system simulation - take into account HVAC component behavior but focus more on control devices and stability of control scheme

Models integrated in HVAC System simulation Example:

Economizer (fresh air volume flow rate control)

mixing

damperfresh air

T & RH sensors

recirc. air

Controlled device is damper

- Damper for the air - Valve for the liquids

HVAC Control

Economizer (fresh air volume flow rate control)

mixing

damperfresh air

T & RH sensors

recirc. air

Controlled device is damper

- Damper for the air - Valve for the liquids

% fresh air

Minimum for ventilation

100%

Economizer – cooling regime

How to control the fresh air volume flow rate?

% fresh air

Minimum for ventilation

100%

If TOA < Tset-point → Supply more fresh air than the minimum required

The question is how much?

Open the damper for the fresh air

and compare the Troom with the Tset-point .

Open till you get the Troom = Tset-point

If you have 100% fresh air and your still need cooling use cooling coil.

What are the priorities: - Control the dampers and then the cooling coils or - Control the valves of cooling coil and then the dampers ?

Defend by SEQUENCE OF OERATION the set of operation which HVAC designer provides to the automatic control engineer

Economizer – cooling regime

Example of SEQUENCE OF OERATIONS:

If TOA < Tset-point open the fresh air damper the maximum position

Then, if Tindoor air < Tset-point start closing the cooling coil valve

If cooling coil valve is closed and T indoor air < Tset-point start closing the damper till you get T indoor air = T set-point Other variations are possible

Sequence of calculation in energy simulation modeling is different than sequence of operation !

We often assume perfect aromatic control

Example of Sequence of calculation in energy simulation models

HVAC solver calculates Q using

plant_real Matrix solver results

Matrix solver solves newT and T

for Qrad_surf air_real

plant_real

T < Trad_sur f max

Matrix solver solves Q for

T or Tplant_corec

max min

for heating:

or for cooling:T > Trad_surf_corec min

yes

yes

no

no

controlled Trad_surf controlled Tsupply

Matrix S.

for

air_setpoint

solves required T and Q

Trad_surf plant

HVAC solver calculates Q using

plant_realMatrix solver results

Matrix solver solves new T and T

for Q supply air_real

plant_real

T < T < Tmin supply max

Matrix solver solves Q for

T or Tplant_corect

max min

yes

yes

no

no

controlled msupply

Matrix S.

for

air_setpoint

solves required T and Q

Tsupply plant

Q < Qplant_real plant Q < Qplant_real plant

HVAC solver calculates Q using

plant_realMatrix solver results

Matrix solver solves new m and T

for Qsupply air_real

plant_real

Matrix solver solves Q for

m or m and Tplant_corec t

max min supply

yes

yes

no

no

Matrix S.

for

air_setpoint

solves required m and Q

Tsupply plant

Q < Qplant_real plant

Matrix Solver

for

air_setpoint

solves Q

Tplant_recqured

Matrix solver

for Q

solves T

= 0air

plant_recqured

Matrix solver

for air_setpoint

solves Qplant_recqured

T

HVAC solver calculates Q using

plant_realMatrix solver results

Matrix solver so lves T

for Qair_real

plant_real

yes

no Q < Qplant_real plant_required

contro lled pure convective source

m < m < mmin supply max

If

corect

zone reheater and m > m

T and checkT < T < T

min supply

supply

min supply max

load calculation HVAC is OFF

HVAC control is ON

II III IV V

VII