Lecture Objectives:

1. Lecture Objectives: • Define the final project Deliverables and Grading policy • Analyze factors that influence accuracy of our modeling study • Learn about automatic control

2. Final project topics: Deliverables: • 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 7 Report with complete analysis 3) Project defense Oral presentation: - May 5 and May 7 in class, or - Sometime afternoon

3. 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.

4. 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

5. 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

6. Accuracy of energy simulation • There are many different factors for inaccuracy of energy simulation results …..... ……. …….

7. 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)

8. How to check the accuracyof numerical model? Comparison wit existing analytical solutions

9. How to check the validity of the larger simulation models? Energy balance Building room: large number of analytical and Numerical equations (sub-models)

10. How to evaluate the whole building simulation tools Two options: • 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

11. 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 COMPARE THE RESULTS

12. Example of best test comparison

13. What are the reasons for the energy simulation • Design (sizing of different systems) • Economic benefits • Impact on environed • Budget planning

14. Basic purpose of HVAC control • Daily, weekly, and seasonal swings make HVAC control challenging • Highly unsteady-state environment • Provide 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

15. Example: Heat exchanger control Modulating (Analog) control Cooling coil air water Basic Control loop x (set point temperature)

16. Cooling coil control valve Electric (pneumatic) motor Position (x) fluid Volume flow rate Vfluid = f(x) - linear or exponential function

17. The PID control algorithm For our example of heating coil: constants time e(t) – difference between set point and measured value Position (x) Differential Proportional Integral Differential (how fast) Proportional (how much) Integral (for how long) Position of the valve

18. The control in HVAC system – only PI Proportional Integral value Set point Proportional affect the slope Integral affect the shape after the first “bump” Set point

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

20. Models integrated in HVAC System simulation Example: Economizer (fresh air volume flow rate control) Controlled device is damper - Damper for the air - Valve for the liquids fresh air damper mixing recirc. air T & RH sensors

21. HVAC Control Economizer (fresh air volume flow rate control) Controlled device is damper - Damper for the air - Valve for the liquids fresh air damper mixing recirc. air % fresh air 100% T & RH sensors Minimum for ventilation

22. Economizer – cooling regime How to control the fresh air volume flow rate? 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 % fresh air 100% Minimum for ventilation

23. 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

24. Example of Sequence of calculation in energy simulation models