First CASSANDRA Workshop Presentation

1. Pilot Case 1:
Shopping Center
Prof. Luca Ferrarini
Eng. Giancarlo Mantovani
Politecnico di Milano, Italy

2. Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions

3. Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions

4. Pilot case objectives
• Pilot case 1 has the following main objectives:
– To deploy CASSANDRA software package to the specific case, feeding
the platform with data coming from a real test scenario.
– To evaluate the applicability of demand response and feedback
programs in the commercial sector.
– To use CASSANDRA as a decision support tool in the pilot case and
evaluate the obtained results in order to determine platform
effectiveness.

5. Pilot site: Campo dei Fiori mall
Type: Shopping center
Location: GAVIRATE (Italy)
Technical data:
• 5-floor building
• 30 retail shops
• Large gym and pool at first floor
• Bars and restaurant on fifth floor
• Park with PV roof cover (602 kWp)

6. Pilot site: Campo dei Fiori mall
• It is an existing shopping center
• Equipped with the local power systems:
– Cooling system
– Heating system
– Electrical power station
• Fully instrumented with a building automation system for monitoring:
– Temperature / humidity
– Plants state
– Electrical consumptions meters

7. Building envelope
• Large central compartment
with lifts and escalators
• Heated swimming pool (with
thermal recovery systems)
• Glass roof (high solar radiation
contribution to internal
temperature)
• Walls above and under ground

8. Building plans
• Cooling towers
• Heat exchangers (e.g.: district
heating)
• Local refrigeration units and
boilers
• …

9. Building plans

10. Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions

11. Pilot case approach
• Part 1: in-simulation
– Thermal and electrical modeling of the building-plants system
– Study in simulation of the impact of different energy control systems
– Testing of various pricing policies on the controlled building
• Part 2: in-field
– Application of a behavioral program to the commercial building retail
shops
– Provide consumption reduction by informing shop-owners about their
electrical consumptions (feedback program)

12. Pilot case approach – in-simulation
Building modeling
• Building envelope model
• Building plants model
• Control-oriented approach

13. Pilot case approach – in-simulation
Energy control
• Application of different energy
control policies
• Local optimization of the
building
Building modeling
• Building envelope model
• Building plants model
• Control-oriented approach

14. Pilot case approach – in-simulation
Demand-response
• Energy price negotiation with the
grid
• Constraints definition for Energy
Controller
Energy control
• Application of different energy
control policies
• Local optimization of the
building
Building modeling
• Building envelope model
• Building plants model
• Control-oriented approach

15. Pilot case approach – in-simulation
Grid
Demand-response
• Energy price negotiation with the
grid
• Constraints definition for Energy
Controller
Energy control
• Application of different energy
control policies
• Local optimization of the
building
Building modeling
• Building envelope model
• Building plants model
• Control-oriented approach

16. Pilot case approach – in-field
• Implementation of a behavioral feedback program
– Informing shop-owners about their electrical consumption
– Use a web-application as channel
• Monetary incentives are provided as result of a competition among
shops

17. Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions

18. In-simulation: building models
• Thermal model from UNI regulations:
– Applies models and formulas from UNI/TS 13790 for building energy use
calculation
• Five-floor stratified thermal model:
– Takes into account vertical temperature distribution
– Built from first principle thermal equations, detailed modeling approach
– Models building envelope, thermal plants and external conditions
(weather/occupancy)
• Single volume thermal model:
– Simplified model with an unique temperature for the whole building
– Models building envelope, thermal plants and external conditions
– Good for behavior prediction

19. In-simulation: zoned thermal model
• Features:
– Finite-volume
dynamic model
– Short-period
simulation
– More complex and
detailed
– Considers
building use and
occupancy
• Physical entities modeled:
– Envelope (walls, glass roof, furniture, etc…)
– Plants (fan-coils, air-handling units, refrigeration units/heat
pumps, heat transfer in the water circuits, etc…)

20. In-simulation: zoned thermal model
• January 2012 (t[s],Ti[°C])
simulatedactual

21. In-simulation: zoned thermal model
• August 2012 (t[s],Ti[°C])
simulatedactual

22. In-simulation: single-volume model
• Models commercial building average temperature
• Scalable modeling methodology (different building can be modeled
only with parameters re-tuning)
• Useful for consumption prediction in a short-term/medium-term
E ≅ 0.2 oC
Temperature[oC]
Time [s]
Single-volume
Zoned model

23. In-simulation: control strategies
• IDEA: use control strategies for decreasing temperature stratification:
(+) More comfort with..
(-) Less energy consumption
• Possible control variables:
– Temperatures and mass flows
– Equipment switch on-off signals
• Considered techniques:
– Hysteresis (current practice, does not control supply water temperature)
– Single-PI regulator (controls average temperature)
– Five-PI (controls temperature in each floor)
– MPC (optimizes building-plants overall system, work in progress)

24. In-simulation: control strategies results
• Single-PI, comparison with current practice:
– Cannot control thermal stratification (comfort not improved)
– -7% energy consumption
• Five-PI, comparison with current practice:
– -25% temperature stratification (comfort improved)
– -5% energy consumption (less savings with respect to single-PI)

25. In-simulation: demand-response
• Test consumption and comfort changes when the building
operates under demand-response programs
• Pricing schemas applied:
– TOU (Time Of Use pricing)
– CPP (Critical Peak Pricing)
– RTP (Real Time pricing)
• Demand response assets and strategies:
– Thermal inertia
– Load shaping:
– Demand limiting
– Demand shedding
– Demand shifting

26. In-simulation: demand-response
Demand limiting
Demand cannot exceed
a certain level
Demand shedding
A temporary
consumption reduction
is performed in critical
periods
Demand shifting
Demand is
anticipated/delayed in
time
Energy efficiency
Definitive intervention
to reduce overall
consumption
Assetsforconsumptionreduction
Assetsfordemandshaping

27. In-simulation: integration with CASSANDRA
• Developed models are implemented in an external simulator and
are available for CASSANDRA as a web-service
• A standardized interface for data exchange was designed
• In this way, models can be parameterized inside the platform and run
on an external server
MODEL
SERVER
web-server
DATA
EXCHANGE
INTERFACE
Java
Thermal
model
CASSANDRA
platform
Model parameters
Power consumption
Temperatures

28. Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions

29. In-field: current situation
• Current situation on feedback:
– Building: network analyzers
– Retail shops: monthly total expenses report
BUILDING
1217,64 kW
SHOP SHOP SHOP
SHOP SHOP SHOP
SHOP
SHOP
Bill Bill Bill Bill
Bill Bill Bill Bill

30. In-field: program target
• Provide building managers with energy KPIs → improved feedback
• Provide shop ownners with real-time information on electrical
consumptions (web application channel)
BUILDING
1217,64 kW
SHOP
7,41 kW
KPIs
SHOP
6,70 kW
KPIs
SHOP SHOP
SHOP SHOP
Bill Bill
Bill Bill
KPIs
SHOP
30,12 kW
KPIs
SHOP
5,23 kW
KPIs

31. In-field: main steps
• Program design:
– Participants: retail shops (11) and building managers
– Feedback information: total electrical consumptions and energy KPI
– Feedback channel: web application
• Information campaign with shop-owners:
– Visits and potentialities explaination
– Flyer design
– Promotion on Politecnico web-site
• Program deployment:
– Web-application coding
– Application release

32. In-field: web-app interface

33. In-field: web-app interface

34. In-field: web-app interface

35. In-field: monetary incentives
• Retail shops participants involvement is improved by monetary
incentives
• Criteria:
– Energy saving with respect to own consumption in pre-program period
– Energy saving with respect to the other shops (with similar consumption
profiles)
– Program involvement (access to website pages)
• Total amount:
– About 2500€
– Distributed in two periods

36. Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions

37. Conclusions
• Pilot case is designed to test CASSANDRA platform capabilities
considering both the building and the shops
• Both thermal and electrical consumptions are considered
• Building use and comfort principles are taken into account
• Both in-simulation and in-field activites are carried out
• Almost unique behavioral program in the commercial sector

38. Thank you for your attention!
Questions?